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DNA repair SNPs as genetic modulators of

individual susceptibility to differentiated thyroid

cancer and response to radioiodine therapy Luís Silva Santos

D.ICBAS 2021

INSTITUTO DE CIÊNCIAS BIOMÉDICAS ABEL SALAZAR

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Luís Silva Santos. DNA repair SNPs as genetic modulators of individual

susceptibility to differentiated thyroid cancer and response to radioiodine therapy

i

Luís Filipe de Sepúlveda Silva Santos

DNA repair SNPs as genetic modulators of individual

susceptibility to differentiated thyroid cancer and response to

radioiodine therapy

Tese de Candidatura ao grau de Doutor em Ciências Biomédicas;

Programa Doutoral da Universidade do Porto (Instituto de Ciências

Biomédicas de Abel Salazar).

Orientador – Professor Doutor José Rueff Tavares

Categoria – Professor catedrático

Afiliação – Universidade NOVA de Lisboa, NOVA Medical School.

Co-orientadora – Professora Doutora Susana Maria Nunes da Silva

Duarte Catana

Categoria – Professora Auxiliar Convidada

Afiliação – Universidade NOVA de Lisboa, NOVA Medical School.

Co-orientadora – Professora Doutora Maria Beatriz Beça

Gonçalves Porto e Vasconcelos

Categoria – Professora Auxiliar

Afiliação – Instituto de Ciências Biomédicas Abel Salazar da

Universidade do Porto.

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“Escrevo-te da Montanha,

do sítio onde medram as raízes deste livro.”

Miguel Torga,

in Novos Contos da Montanha

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Declaração de honra

Declaro que a presente tese é de minha autoria e não foi utilizada previamente noutro

curso ou unidade curricular, desta ou de outra instituição. As referências a outros

autores (afirmações, ideias, pensamentos) respeitam escrupulosamente as regras da

atribuição, e encontram-se devidamente indicadas no texto e nas referências

bibliográficas, de acordo com as normas de referenciação. Tenho consciência de que a

prática de plágio e auto-plágio constitui um ilícito académico.

______________________________________

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List of publications and communications

Complying with the terms of the relevant national legislation [n.º 2, alínea a) do artigo

31.º do Decreto -Lei n.º 230/2009], the author declares that the work developed in this

doctoral thesis is published in peer-reviewed scientific journals (detailed below). The

author participated actively in the conception and execution of the work that originated

that data, as well as in their interpretation, discussion and writing.

Original research articles published within the scope of this doctoral thesis

Santos LS, Branco SC, Silva SN, Azevedo AP, Gil OM, Manita I, Ferreira TC, Limbert

E, Rueff J and Gaspar JF (2012). Polymorphisms in base excision repair genes and

thyroid cancer risk. Oncol Rep. 28(5): 1859-68. (DOI: 10.3892/or.2012.1975)

Santos LS, Gomes BC, Gouveia R, Silva SN, Azevedo AP, Camacho V, Manita I, Gil

OM, Ferreira TC, Limbert E, Rueff J and Gaspar JF (2013). The role of CCNH Val270Ala

(rs2230641) and other nucleotide excision repair polymorphisms in individual

susceptibility to well-differentiated thyroid cancer. Oncol Rep. 30(5): 2458-66. (DOI:

10.3892/or.2013.2702)

Santos LS, Silva SN, Gil OM, Ferreira TC, Limbert E, Rueff J (2018). Mismatch repair

single nucleotide polymorphisms and thyroid cancer susceptibility. Oncol Lett. 15(5):

6715-6726. (DOI: 10.3892/ol.2018.8103)

Santos LS, Gomes BC, Bastos HN, Gil OM, Azevedo AP, Ferreira TC, Limbert E, Silva

SN, Rueff J (2019). Thyroid Cancer: The Quest for Genetic Susceptibility Involving DNA

Repair Genes. Genes (Basel). 10(8): E586. (DOI: 10.3390/genes10080586)

Santos LS, Gil OM, Silva SN, Gomes BC, Ferreira TC, Limbert E, Rueff J (2020).

Micronuclei Formation upon Radioiodine Therapy for Well-Differentiated Thyroid Cancer:

The Influence of DNA Repair Genes Variants. Genes. 11(9): 1083. (DOI:

10.3390/genes11091083)

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Oral communications within the scope of this doctoral thesis

Santos LS. A personalized medicine approach to thyroid cancer: the influence of DNA

repair polymorphisms in individual disease susceptibility and response to therapy. I

Jornadas Científicas da Primavera. Viseu, 20 de Março de 2015.

Poster presentations within the scope of this doctoral thesis

Gomes BC, Gouveia R, Silva SN, Bastos HN, Branco SC, Antão M, Azevedo AP, Gil

OM, Manita I, Santos LS, Ferreira TC, Limbert E and Gaspar JF. Polymorphisms in DNA

repair genes and non-familiar thyroid cancer risk. In: AACR Special Conference in

Cancer Research - The Future of Molecular Epidemiology: New Tools, Biomarkers, and

Opportunities; 2010 Jun 6-9; Miami, FL.

Santos LS, Gomes BC, Gouveia R, Silva SN, Azevedo AP, Camacho V, Manita I, Gil

OM, Ferreira TC, Limbert E, Rueff J and Gaspar JF. The role of CCNH Val270Ala and

other nucleotide excision repair polymorphisms on individual susceptibility towards

thyroid cancer. 6 th Santorini Conference Biologie Prospective 2012 (“Systems Biology

and Personalized Health Science and Translation”). 2012 Sep 30-Oct 02; Santorini

Island, Greece. In: Drug Metabol Drug Interact (2012); 27(3): A21-A22.

Santos LS. In silico analysis of SNPs in pharmacogenomic studies: predictive functional

analysis of SLC5A5 gene variants and potential impact on radioactive iodine (131-I)

therapy response. Second ESPT Conference "Pharmacogenomics: From Cell to Clinic".

2013 Sep 26-28; Lisbon, Portugal. In: Drug Metabol Drug Interact (2013); 28(3):A42–

A43.

Santos LS, Silva SN, Azevedo AP, Manita I, Gil OM, Ferreira TC, Limbert E, Rueff J and

Gaspar JF. Mismatch repair SNPs and thyroid cancer susceptibility: a potential role for

the MSH6 rs1042821 (Gly39Glu) polymorphism. Third ESPT Conference "Integration of

Pharmacogenomics in clinical decision support". 2015 Oct 07-09; Budapest, Hungary.

In: Drug Metabolism and Personalized Therapy (2015); 30(3):eA23.

Santos LS, Silva SN, Gomes BC, Gouveia R, Azevedo AP, Manita I, Gil OM, Ferreira

TC, Limbert E and Rueff J. The potential contribution of DNA repair SNPs to thyroid

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cancer susceptibility. 2º Simpósio de Ciências e Tecnologias da Vida e da Saúde -

Universidade Católica Portuguesa, Centro de Investigação Interdisciplinar em Saúde.

Porto, 30 de Setembro de 2016.

Santos LS, Silva SN, Gil OM, Ferreira TC, Limbert E, Rueff J. The potential contribution

of SNP-SNP interactions within the DNA mismatch repair pathway to thyroid cancer

susceptibility. Fourth ESPT Conference "Pharmacogenomics and Personalised

Medicine: research progress and clinical implementation". 2017 Oct 04-07; Catania,

Italy.

Santos LS, Silva SN, Gil OM, Gomes BC, Bastos HN, Ferreira TC, Limbert E, Rueff J.

The potential impact of DNA repair SNPs on DNA damage levels of lymphocytes from

131I-treated thyroid cancer patients. Fourth ESPT Conference "Pharmacogenomics and

Personalised Medicine: research progress and clinical implementation". 2017 Oct 04-07;

Catania, Italy.

Santos LS, Silva SN, Rueff J. Thyroid Cancer: The Quest for Genetic Susceptibility

Involving DNA Repair Genes. NOVA Science Day 2019 - 2o Encontro de Ciência da

NOVA. Universidade Nova de Lisboa, Reitoria. Lisboa, 18 de Setembro de 2019.

Complementary oral communications in fields related to the thesis

Marques AM, Martins D and Santos LS. Individual susceptibility to the toxic effects of

radiation therapy: a potential role for DNA repair SNPs? International Conference of

Environmental and Occupational Health / Ibero-American Meeting on Toxicology and

Environmental Health (ICOETOX/IBAMTOX) 2016. 2016 Jun 21-23. Porto, Portugal.

Complementary poster presentations in fields related to the thesis

Martins A, Santos LS, Rosa N, Barros M and Correia MJ. Identification of miRNAs with

potential utility as salivary biomarkers for type II diabetes. 8th Santorini Conference

Systems Medicine and Personalised Health and Therapy. 2016 Oct 03-05; Santorini

Island, Greece. In: Clin Chem Lab Med (2016); 54(11): eA529.

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Santos LS, Alves L, Martins D, Rosa N, Barros M, Correia MJ. miRNAs as potential

salivary biomarkers in periodontitis. 8th Santorini Conference Systems Medicine and

Personalised Health and Therapy. 2016 Oct 03-05; Santorini Island, Greece. In: Clin

Chem Lab Med (2016); 54(11): eA529.

Marques AM, Santos LS. Personalized cancer radiotherapy: a role for DNA repair SNPs

as radiogenomic biomarkers? 8th Santorini Conference Systems Medicine and

Personalised Health and Therapy. 2016 Oct 03-05; Santorini Island, Greece. In: Clin

Chem Lab Med (2016); 54(11): eA540.

Sousa S, Martins JE, Martins A, Rosa N, Santos LS, Correia MJ and Barros M. Salivary

Diagnosis: miRNA's new directions. 2º Simpósio de Ciências e Tecnologias da Vida e

da Saúde - Universidade Católica Portuguesa, Centro de Investigação Interdisciplinar

em Saúde. Porto, 30 de Setembro de 2016.

Martins A, Santos LS, Rosa N and Correia MJ. miRNAs salivares como biomarcadores

da Diabetes Mellitus Tipo II (DMTII). XXXVI Congresso Anual SPEMD 2016. Porto, 7-8

de Outubro de 2016.

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Collaborations and financial support

This work was developed at the Centre for Toxicogenomics and Human Health (NOVA

Medical School, Universidade Nova de Lisboa), with the collaboration of the Department

of Nuclear Medicine of the Portuguese Oncology Institute of Lisbon and the Department

of Clinical Pathology of the São Francisco Xavier Hospital, West Lisbon Hospital Centre.

Financial support was provided by FCT—Fundação para a Ciência e a Tecnologia

(Portuguese Foundation for Science and Technology) through Projects

UID/BIM/00009/2019, UID/BIM/00009/2016, Pest-E/SAU/UI0009/2011, PTDC/SAu-

ESA/102367/2008, PTDC/SAu-OSM/105572/2008 and PTDC/QUI/67522/2006 and by

Fundação Calouste Gulbenkian (Grant 76438/2006).

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Acknowledgements

22 de agosto de 2012. A data de publicação do artigo mais antigo desta tese. O meu

primeiro artigo enquanto primeiro autor. O fruto de um trabalho que começara anos

antes (já não sei precisar quantos, a memória atraiçoa-me e os registos da altura

perderam-se entretanto num qualquer disco duro danificado), quando o Jorge me

desafiou a dar continuidade a um outro trabalho que realizara com a Doutora Octávia

Gil. Na altura, a perspetiva do Doutoramento estava já presente, mas como algo ainda

longínquo, de fronteiras difusas. Havia terminado o Mestrado em Patologia

Experimental, em Coimbra, sob orientação do Professor Cabrita (que me abrira as

portas do mundo da Investigação Científica), e iniciado funções como assistente

estagiário no Curso de Medicina Dentária da Universidade Católica Portuguesa, em

Viseu, com o Professor Cabrita, a Professora Marlene Barros, a Professora Maria

José Correia e a Professora Conceição Egas. Havia também concluído um curso de

extensão universitária em Toxicologia Genética e Toxicogenómica, em Lisboa,

coordenado pela Doutora Teresa Chaveca e pelo Professor Rueff (que, mais tarde,

viria a ajudar-me a levar a bom porto este empreendimento, orientando, juntamente com

a Susana e a Doutora Beatriz Porto, esta dissertação). A minha formação de base em

Ciências Farmacêuticas e a minha curiosidade pela área da Genética cruzavam-se

naturalmente em campos como o da Farmacogenómica e da Toxicogenómica, campos

que sempre me haviam fascinado (desde os tempos da Faculdade, originalmente pela

mão do Professor Sérgio Simões) e nos quais me sentia compelido a aprofundar o

meu conhecimento e envolvimento. Foi por isso com grande satisfação e uma enorme

vontade de fazer que comecei, sob orientação do Jorge (um farol que além de mentor,

se veio a tornar um amigo como poucos), a colaborar em projetos de investigação do

Departamento de Genética da FCM-UNL, à data, na Rua da Junqueira. Saudade!

Recordo a Susana (que me ajudou como poucos e a quem devo, de resto, muito do que

aqui vos trago), o João, a Marta, o Bruno, a Ana Paula, a Célia, o Bernardo, o

Francisco, o João Paulo, a Daniela, a Rita, o Hélder e todos aqueles com quem fui

trabalhando e partilhando ideias e projetos, resultados e concretizações, dúvidas e

frustrações. Os sábios conselhos do Professor Rueff, do Sebastião, do Michel, do

Nuno, do Joaquim e o apoio inestimável da Dª Isabel e da Patrícia. E claro, os

momentos de descontração passados à volta da mesa do almoço, na cantina, ou a

fumar um cigarro lá fora, aproveitando o Sol da Primavera entre os ‘’eternos’’ ciclos de

PCR.

xiv

Mais de dez anos passaram desde então. E tanto mudou entretanto! Devagar,

imperceptível, insidioso. Os primeiros reveses, a pressão de conciliar uma vontade

férrea de fazer avançar o trabalho de doutoramento em Lisboa com o trabalho a tempo

integral na Universidade Católica, em Viseu, a 300 km de distância. Uma distância física

sempre lá, a moer devagarinho mas pendularmente, sem perdão. O comboio como

escritório, anos e anos a fio. Aulas para preparar. Artigos para escrever. Mais uma

viagem. Coimbra B. Lisboa Oriente. Linha Azul. ‘’Chego tarde. Ainda tenho jantar?’’ Esta

frase repetida vezes sem conta. Semana após semana. Mais uma semana a correr

contra o tempo. Não dá para parar nos apeadeiros. O tempo não estica. E aí fica aquele

amigo por visitar. E outro e mais outro. O Sérgio, o Mário, o Luís, a Teresa, tantos

mais. É a distância afectiva que também se instala. E cresce, devagar, imperceptível,

insidiosa. O jantar com os pais cancelado, o fim de semana com o André, a Catarina,

a Mia e a Lara – sobrinhas lindas! – ou as férias com a Joana adiados. Um após outro

e outro ainda. Projectos pessoais, familiares, profissionais e associativos abandonados,

interrompidos, adiados. Alguns cancelados. Um bicho voraz que tudo devora sem nunca

estar saciado. “É temporário!”, pensava, para me alentar. “É só mais este esforço e tudo

voltará ao normal. Em breve!” Mas depois de um esforço vinha outro, e outro e outro,

cada vez mais juntos até não mais ser possível distingui-los e se fundirem num esforço

contínuo insustentável. Os bravos, heróis, vão claudicando, um a um: os meus avós, o

Mira, o Professor Siest, o Jorge. Um farol que desaparece no Zêzere. A confiança que

dá lugar à dúvida. A vontade que cede ao medo. O chão que foge, o suporte que já lá

não está. A determinação que se esvai, a ansiedade que aumenta. A solidão no meio

da multidão. E o fim, esse tão desejado fim que não se vislumbra, ai! Tudo devagar,

imperceptível, insidioso.

29 de Junho de 2021. O dia em que defenderei esta tese. Presencialmente, no salão

nobre do ICBAS, no Porto, de capa e batina como manda a tradição (que não é a da

minha Coimbra mas também não lhe fica atrás). Enquanto escrevo estas linhas, o sol

de Primavera entra pela janela à minha frente, aquece-me o rosto e a alma. Ao fundo,

na encosta oposta, a palheira de pedra que comprei com a Joana, à nossa espera.

Paciente, sem pressa. É o nosso próximo projecto, temos muitas ideias. Em baixo, a

aldeia espraia-se ao longo da ribeira. Entre o chilrear da passarada e o ladrar dos cães,

imagino o som da água a correr. A Mica, a gata que nos adoptou, descansa aos meus

pés. Desgraçada, não tem tido vida fácil a criar os filhotes que teve há um mês! Temos

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aproveitado os fins de semana ensolarados para fazer caminhadas e descobrir esta

Serra que é cada vez mais minha e de todos. No fim de semana passado fomos comer

umas trutas ao viveiro, com uns amigos, companheiros de armas no Movimento Estrela

Viva. Na 5ª feira, tínhamos ido à sessão semanal do Cineclube de Viseu, há tanto

tempo que lá não ia. Estava tudo igual, a qualidade do costume. Aproveitei a viagem

para ligar a uma amiga de longa data com quem não falava há anos. Como é possível

tanto tempo? Já tenho alinhavado um jantar em Coimbra, com os meus amigos de

sempre. E alojamento marcado para um fim de semana em família aqui na Serra! Como

cresceram as miúdas, tanta saudade! A vida regressa. O fim, afinal, chegou.

A todos os que me acompanharam neste percurso, que me apoiaram e não me

deixaram desistir;

A todos os que comigo partilharam a ausência, os sacrifícios, os projectos adiados;

A todos os que com a sua sabedoria e disponibilidade me iluminaram o caminho a trilhar;

A todos os que me incutiram valores como justiça, honestidade e solidariedade e

contribuíram para o homem de causas, espírito lutador e resiliente que hoje sou;

A todos os que por mim plantaram as árvores que gostaria de ter plantado;

A todos, o meu profundo, sentido e afectuoso agradecimento que jamais palavra

alguma conseguirá traduzir em toda a sua magnitude. Bem hajam!

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Index of contents

List of abbreviations xxi

Abstract xxvii

Resumo xxxi

Chapter I 1

Introduction 3

Thyroid cancer (TC) 3

A brief overview on the anatomy and physiology of the thyroid gland 3

Classification of follicular cell-derived thyroid tumours 5

Molecular pathogenesis of follicular cell-derived thyroid tumours 8

Epidemiology of follicular cell-derived thyroid tumours 10

Aetiology and risk factors for the development of follicular cell-derived

thyroid tumours

12

Therapeutic options for the treatment of follicular cell-derived thyroid

tumours

16

Prognosis of follicular cell-derived thyroid tumours 20

DNA repair pathways 23

Base Excision Repair (BER) 23

Nucleotide Excision Repair (NER) 24

Mismatch Repair (MMR) 25

Homologous Recombination (HR) 26

Non-Homologous End-Joining Repair (NHEJ) 27

The impact of DNA repair gene variation in the context of thyroid cancer 30

Genetic diversity and its clinical implications 30

DNA repair SNPs and thyroid cancer susceptibility 31

References 33

Chapter II 51

Objectives 53

References 54

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Chapter III 59

Polymorphisms in base excision repair genes and thyroid cancer risk 61

Abstract 61

Introduction 61

Materials and methods 64

Study subjects 64

DNA extraction 64

Single nucleotide polymorphisms (SNP’s) selection 65

Genotyping 65

Statistical analysis 67

Results 68

Discussion 74

Acknowledgements 80

References 80

Chapter IV 85

The role of CCNH Val270Ala (rs2230641) and other nucleotide excision

repair polymorphisms in individual susceptibility to well-differentiated

thyroid cancer

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Abstract 87

Introduction 87


Study subjects 89

DNA extraction 90

SNP selection 90

Genotyping 91


Results 92

Discussion 98

Acknowledgements 101

References 101

Chapter V 107

Mismatch repair single nucleotide polymorphisms and thyroid cancer 109

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susceptibility

Abstract 109

Introduction 110


Ethical statement 112

Study subjects 112

SNP selection 113

DNA extraction and genotyping 113


Results 115

Discussion 128


References 134

Chapter VI 143

Thyroid Cancer: The Quest for Genetic Susceptibility Involving DNA

Repair Genes

145

Abstract 145

Introduction 145


Study subjects 147

SNP selection 148

Practical methodologies – brief description 150


Results 152

General analysis 152

All DTC cases 153

Stratified analysis 156

Combined genotypes 166

Discussion 176

Funding 182


References 183

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Chapter VII 197

Micronuclei Formation upon Radioiodine Therapy for Well-

Differentiated Thyroid Cancer: The Influence of DNA Repair Genes

Variants

199

Abstract 199

Introduction 199


Study population 202

Genotype analysis 203

Cytogenetic analysis 203


Results 205

Characteristics of the study population 205

Cytogenetic data 206

Characteristics of the study population and cytogenetic data 208

Distribution of DNA repair SNPs in the study population 209

DNA repair SNPs and cytogenetic data 211

Discussion 215

Conclusions 224

Funding 225


References 225

Chapter VIII 239

Final conclusions 241

References 245

Appendix I 253

Rights and permissions 255

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List of Abbreviations

·OH Hydroxyl radical

131I Iodine-131

6-4PPs (6-4) pyrimidine-pyrimidone photoproducts

8-oxo-dG 8-oxo-7,8-dihydro-2'-deoxyguanosine

AB Applied Biosystems

AID Activation-induced (cytidine) deaminase

AP Apurimidinic/apurinic site

AT Ataxia telangiectasia

ATA American Thyroid Association

ATC Anaplastic thyroid cancer

BASC BRCA1-associated genome surveillance complex

BER Base excision repair

BLAST Basic local alignment search tool

BNMN Binucleated cells carrying micronuclei

bp Base pairs

BRCT BRCA1 C terminus

BS Bloom syndrome

CAK Cyclin-activated kinase

CBMN Cytokinesis-blocked micronucleus assay

CBPI Cytokinesis-Block Proliferation Index

CGAS Candidate gene association study

CI Confidence interval

circRNA Circular RNA

CPDs Cyclobutane pyrimidine dimmers

CRC Colorectal cancer

CS Cockayne syndrome

CT Computed tomography

dbSNP Single Nucleotide Polymorphism Database

DMSO Dimethyl sulfoxide

DNA Deoxyribonucleic acid

dNTP Deoxyribonucleotide triphosphate

DPC DNA-protein crosslink

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DSB Double-strand break

DTC Well-differentiated thyroid cancer

DUOX2 Dual oxidase-2

EBRT External beam radiation therapy

EMA European Medicines Agency

FAP Familial adenomatous polyposis

FDA Food and Drug Administration

FNA Fine-needle aspiration

FTA Follicular thyroid adenoma

FTC Follicular thyroid cancer

FVPTC Follicular variant papillary thyroid cancer

GGR Global-genome repair

GI Gastrointestinal

GWAS Genome-wide association study

H2O2 Hydrogen peroxide

HIGM5 Hyper-IgM Syndrome Type 5

HNPCC Hereditary nonpolyposis colorectal cancer

HR Homologous recombination

HUGO Human Genome Organization

HUMN International Human MicroNucleus Project

HWE Hardy–Weinberg equilibrium

I Iodine

I- Iodide

IARC International Agency on Cancer Research

ICL Interstrand crosslink

IDLs Insertion–deletion loops

IPO Portuguese Oncology Institute

IR Ionizing radiation

K+ Potassium ion

LD Linkage disequilibrium

LET Linear energy transfer

LN Lymph node

lncRNA Long noncoding RNA

LOH Loss of heterozygosity

LS Lynch Syndrome

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MAF Minor allele frequency

MAP MUTYH-associated polyposis

MAPK Mitogen-activated protein kinase

mCi miliCurie

MEK Mitogen-activated protein kinase kinase

MgCl2 Magnesium chloride

miRNA microRNA

MMR Mismatch repair

MN Micronucleus/micronuclei

MRI Magnetic resonance imaging

MRN Mre11-Rad50-Nbn complex

mRNA Messenger RNA

MSI Microsatellite instability

MSI-L Low microsatellite instability

MSS Microsatellite stable

N.D. Not detected

Na+ Sodium ion

Na+/K+ ATPase Sodium-Potassium pump

NBS Nijmegen breakage syndrome

NCBI National Center for Biotechnology Information

NER Nucleotide excision repair

NHEJ Non-homologous end-joining

NIS Sodium-iodide symporter

NLS Nuclear localization sequence

NSCLC Non-small cell lung cancer

nsSNP Non-synonymous single nucleotide polymorphism

NTR N-terminal region

O2 Molecular oxygen

OR Odds ratio

PAH Polycyclic aromatic hydrocarbons

PCR Polymerase chain reaction

PDS Pendrin

PDTC Poorly-differentiated thyroid cancer

PET Positron emission tomography

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PI3K Phosphatidylinositol 3-kinase

PIP PCNA interacting protein

PTC Papillary thyroid cancer

PTMC Papillary thyroid microcarcinoma

RAI Radioactive iodine

RAIR Radioactive iodine-refractory disease

RFA Radiofrequency ablation

RFLP Restriction fragment length polymorphism

ROS Reactive oxygen species

RS Risk score

RT-PCR Real-time polymerase chain reaction

RTS Rothmund Thomson syndrome

S.D. Standard deviation

SCCHN Squamous cell carcinoma of the head and neck

SEER Surveillance, Epidemiology, and End Results Program

SNP Single nucleotide polymorphism

SSB Single-strand break

ssDNA Single-stranded DNA

T3 Triiodothyronine

T4 Thyroxine

TC Thyroid cancer

TCR Transcription-coupled repair

TFIIH Transcription factor IIH

Tg Thyroglobulin

Tg-DIT Diiodotyrosine

Tg-MIT Mono-iodotyrosine

Tg-T3 Thyroglobulin-triiodothyronine complex

Tg-T4 Thyroglobulin-thyroxine complex

TNBC Triple negative breast cancer

TNM Tumour, node, metastasis

TPO Thyroid peroxidase

TSH Thyroid-stimulating hormone

TTD Trichothiodystrophy

UICC Union for International Cancer Control

UTR Untranslated region

xxv

UV Ultra-violet

WHO World Health Organization

WNT Wingless-type

WS Werner syndrome

XP Xeroderma pigmentosum

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xxvii

Abstract

Thyroid gland tumours are a heterogeneous group of neoplasms that may virtually arise

from any of the different cell types that are present in the thyroid gland. Among malignant

thyroid tumours (TC) arising exclusively from follicular thyroid cells, papillary thyroid

cancer (PTC) and follicular thyroid cancer (FTC), often collectively referred to as well-

differentiated thyroid cancer (DTC), are the most common categories, representing 80-

85% and 10-15% of cases, respectively. These tumours share several characteristics

such as well differentiated status, favourable response to standard therapy and good

prognosis (in sharp contrast with anaplastic thyroid carcinoma, a less frequent but much

more aggressive form of TC), but differ in relation to histological and morphological

features, as well as in their molecular pathogenesis, MAPK pathway mutations being

mostly associated with PTC while PI3K pathway mutations predominate in FTC. From

an epidemiological standpoint, thyroid cancer is the most common endocrine

malignancy. Incidence is particularly relevant among women and younger age groups

(ages 15-39) and, importantly, has been rising over the last decades, raising concern.

Mortality rates, however, have not followed such trend as the majority of TC cases are

well-differentiated and thus have indolent behaviour and positive response to therapy.

Exposure to ionizing radiation (IR), particularly during childhood, remains the best-

established risk factor despite other environmental factors have also been suggested.

Importantly, genetic susceptibility factors may also play a relevant role as DTC as been

demonstrated to exhibit high heritability. Nevertheless, despite several susceptibility

biomarkers have recently been proposed and replicated through recent genome-wide

association studies (GWAS), these are still largely insufficient to explain the estimated

heritability of DTC, suggesting that other genetic variants (either alone or in combination

with other genetic or environmental factors) may also contribute to DTC susceptibility.

These genetic variants remain yet unidentified.

Standard DTC treatment involves a combination of surgical, hormonal, and nuclear

medicine therapies. Despite of a recent revision of the clinical practice guidelines, 131I-

based radioiodine (RAI) therapy remains widely used and an indispensable tool in the

management of DTC. 131I is preferentially taken up by and trapped in thyroid follicular

cells (mimicking the physiological process of iodide uptake), undergoes [beta] decay and

thus induces therapeutic useful DNA damage and IR-induced cytotoxicity. Other cells,

however, may also concentrate 131I and suffer its DNA-damaging effects. Treatment with

131I has therefore been associated with an increased relative risk of developing

xxviii

secondary malignancies such as leukaemia. Among other recommendations, the current

ATA guidelines thus advocate a reduction in the use of radioactive iodine and the use of

molecular testing to improve risk stratification for therapeutic decisions.

Several DNA repair pathways exist, dedicated to the correction of different DNA lesions

such as those induced by IR. If unrepaired or misrepaired, such lesions may give rise to

stable oncogenic mutations and cancer initiation. DNA repair deficiencies (e.g. arising

from germline mutations) thus often result in genetic instability and cancer proneness.

Common DNA repair SNPs may therefore, if functional (i.e. if interfering with the

expression or activity of DNA repair enzymes), increase sensitivity to DNA damaging

agents such as IR.

Considering the dual role that IR plays in both DTC aetiology and therapy, DNA repair

SNPs could thus contribute both to DTC risk and to the extent of the DNA damaging

effects of 131I therapy. In order to verify these hypotheses, we undertook 1) a hospital-

based case-control study in a Caucasian Portuguese population to evaluate the potential

modifying role of a panel of DNA repair SNPs on the individual susceptibility to DTC and

2) a pilot longitudinal study in DTC patients submitted to 131I-based RAI therapy to

correlate individual DNA repair SNPs with the micronuclei (MN) frequency (a marker of

DNA damage) in peripheral blood lymphocytes from these patients, at several time

points.

Significant associations with DTC risk were observed for CCNH rs2230641, MSH6

rs1042821, XPC rs2228001 and XRCC3 rs861539. The association of XRCC3 rs861539

with DTC susceptibility had been frequently reported in prior studies and was confirmed

in this work. This was not the case, however, for XRCC1 rs1799782 and rs25487, also

investigated here and previously reported to be associated with DTC susceptibility.

Additional genotype-disease associations were observed upon stratification according to

histological, gender or age criteria (XRCC3 rs861539, NBN rs1805794, XPC rs2228001,

ERCC5 rs2227869 and MUTYH rs3219489 in PTC; MSH6 rs1042821, MLH3 rs175080

and XRCC2 rs3218536 in FTC; XRCC3 rs861539, MSH6 rs1042821, XPC rs2228001,

CCNH rs2230641, ERCC5 rs2227869 and ERCC5 rs17655 in women; XPC rs2228001

and XRCC5 rs2440 in younger patients; XRCC3 rs861539, CCNH rs2230641, ERCC6

rs2228529 and RAD51 rs1801321 in older patients). More importantly, when

investigating the joint effect of multiple SNPs, a clear-cut gene-dosage effect between

the number of risk genotypes and DTC risk was observed, together with a high number

of significant results on paired SNP analysis. Finally, significant associations were also

observed between HR and MMR SNPs (MLH1 rs1799977, MSH3 rs26279, MSH4

xxix

rs5745325, and NBN rs1805794) and MN levels in peripheral lymphocytes from DTC

patients submitted to 131I-based RAI therapy. Of notice, the association with MLH1

rs1799977 with 131I-induced MN levels one month after therapy was particularly robust,

as a highly significant p value was observed and independently replicated across two 131I

dose groups.

Overall, this work suggests an involvement of DNA repair SNPs across different

pathways on DTC susceptibility, possibly through cumulative effects, and in the extent

of 131I-induced DNA damage in peripheral lymphocytes from DTC patients, hence 131I

sensitivity. If confirmed and validated through additional, well-powered studies, these

results may contribute both to the identification of individuals who are at increased risk

for DTC (allowing the optimization of cancer prevention policies) and to the

personalization of RAI therapy according to the individual profile of the patient (thus

improving the risk-benefit ratio of this therapy and the overall outcome in DTC patients).

xxx

xxxi

Resumo

Os tumores da tiróide são um grupo heterogéneo de neoplasias que podem surgir,

virtualmente, a partir de qualquer um dos diferentes tipos de células presentes na

glândula tiroideia. Entre os tumores malignos decorrentes da transformação de células

foliculares da tiróide, o carcinoma papilar da tiróide (PTC) e o carcinoma folicular da

tiróide (FTC), muitas vezes referidos coletivamente como carcinoma bem diferenciado

da tiróide (DTC), são as categorias mais comuns, representando respetivamente 80-

85% e 10-15% dos casos. Esses tumores têm várias características em comum, como

o estatuto bem diferenciado, uma resposta positiva à terapêutica padrão e um bom

prognóstico (em contraste nítido com o carcinoma anaplásico da tiróide, uma forma

menos frequente, mas muito mais agressiva de TC), mas diferem em relação às suas

características histológicas e morfológicas, bem como em relação à sua patogénese

molecular, com a presença de mutações da via MAPK associada, principalmente, ao

PTC, enquanto as mutações da via PI3K predominam no FTC. Do ponto de vista

epidemiológico, o carcinoma de tiróide é a neoplasia endócrina mais comum. A

incidência é particularmente relevante entre mulheres e grupos de idades mais jovens

(15 a 39 anos) e, mais importante, tem aumentado nas últimas décadas, causando

preocupação. As taxas de mortalidade, no entanto, não acompanham esta tendência,

uma vez que a maioria dos casos de TC são bem diferenciados, apresentando por isso

comportamento indolente e resposta terapêutica favorável.

A exposição à radiação ionizante (IR), principalmente durante a infância, é ainda o fator

de risco mais bem estabelecido, não obstante outros fatores ambientais terem também

sido sugeridos como fatores de risco. Importa ressaltar que os fatores de suscetibilidade

genética também podem desempenhar um papel relevante, como o demonstra a

elevada heritabilidade exibida pelo DTC. No entanto, apesar de terem já sido propostos

(e replicados em diferentes populações) vários biomarcadores de suscetibilidade

através de estudos de associação genome-wide (GWAS), estes são ainda largamente

insuficientes para explicar a toda a heritabilidade estimada do DTC, o que sugere a

existência de outras variantes genéticas que (isoladamente ou em combinação entre si

ou com fatores ambientais) podem também contribuir para a suscetibilidade ao DTC.

Tais variantes genéticas não foram ainda identificadas.

A terapêutica padrão do DTC envolve uma combinação de tratamentos cirúrgicos,

hormonais e de medicina nuclear. Apesar das diretrizes para a prática clínica em

carcinoma da tiróide terem sido recentemente revistas, a terapêutica baseada na

xxxii

administração de iodo radioativo (131I) continua a ser amplamente utilizada e uma

ferramenta indispensável no tratamento do DTC. O 131I é preferencialmente absorvido e

aprisionado pelas células foliculares da tiróide (mimetizando o processo fisiológico de

captação de iodeto), sofre decaimento β e induz desta forma dano local no ADN e

citotoxicidade induzida por IR (terapeuticamente útil). Todavia, outras células podem

também concentrar 131I e sofrer assim esses mesmos danos no ADN. O tratamento com

131I tem, por essa razão, sido associado a um aumento no risco de cancro secundário,

como a leucemia. Entre outras recomendações, as atuais diretrizes da American Thyroid

Association (ATA) defendem por isso uma redução no uso de iodo radioativo e o

desenvolvimento de estratégias de estratificação de risco com base em testes

moleculares para suportar o processo de decisão terapêutica.

Existem várias vias de reparação de ADN, específicas para diferentes lesões, como as

induzidas pela IR. Se não reparadas ou reparadas incorretamente, estas lesões podem

dar origem a mutações oncogénicas estáveis e iniciar o processo de transformação

maligna. As deficiências em vias de reparação de ADN (decorrentes, por exemplo, de

mutações na linha germinativa) resultam por isso, frequentemente, em instabilidade

genética e suscetibilidade ao cancro. A presença de polimorfismos de base única

(SNPs) em genes de reparação de ADN pode, por isso, caso estes sejam funcionais (ou

seja, se interferirem com a expressão ou atividade das enzimas de reparação de ADN),

aumentar a sensibilidade a agentes que danificam o ADN, como a IR.

Considerando o duplo papel que a IR desempenha tanto na etiologia como na

terapêutica do DTC, é possível que os SNPs em enzimas de reparação de ADN

contribuam tanto para a suscetibilidade a DTC como para a extensão dos danos

genéticos induzidos pela terapêutica com 131I. Por forma a verificar estas hipóteses,

realizámos 1) um estudo caso-controlo de âmbito hospitalar, numa população

caucasiana portuguesa, para avaliar o potencial papel modulador de um painel de SNPs

em genes de reparação de ADN na suscetibilidade individual para DTC e 2) um estudo

piloto longitudinal em pacientes com DTC submetidos a terapêutica com 131I para

correlacionar a presença de determinados SNPs em genes de reparação de ADN com

a frequência de micronúcleos (MN, um marcador de dano ao ADN) em linfócitos do

sangue periférico desses pacientes, a vários momentos.

Observámos associações significativas entre os SNPs CCNH rs2230641, MSH6

rs1042821, XPC rs2228001 e XRCC3 rs861539 e o risco de DTC. A associação do SNP

XRCC3 rs861539, previamente reportada para TC, manteve a significância estatística

ao restringirmos a análise exclusivamente a DTC. Não foi todavia possível confirmar as

xxxiii

associações sugeridas na literatura para os SNPs XRCC1 rs1799782 e rs25487,

também aqui investigados mas com resultados negativos. Após estratificação de acordo

com critérios histológicos, de género ou de idade, observámos associações adicionais

(XRCC3 rs861539, NBN rs1805794, XPC rs2228001, ERCC5 rs2227869 e MUTYH

rs3219489 em PTC; MSH6 rs1042821, MLH3 rs175080 e XRCC2 rs3218536 em FTC;

XRCC3 rs861539, MSH6 rs1042821, XPC rs2228001, CCNH rs2230641, ERCC5

rs2227869 e ERCC5 rs17655 em mulheres; XPC rs2228001 e XRCC5 rs2440 em

pacientes mais novos; XRCC3 rs861539, CCNH rs2230641, ERCC6 rs2228529 e

RAD51 rs1801321 em pacientes mais velhos). Ao investigar o efeito conjunto dos SNPs

analisados, é de destacar a observação de uma relação clara entre o número de alelos

de risco e a suscetibilidade para DTC, juntamente com um elevado número de

resultados significativos na análise emparelhada de SNPs. Por fim, observámos

também associações significativas entre SNPs em genes das vias de reparação HR e

MMR (MLH1 rs1799977, MSH3 rs26279, MSH4 rs5745325 e NBN rs1805794) e os

níveis de MN em linfócitos de pacientes DTC submetidos a terapia com 131I. É de

salientar aqui que a associação do SNP MLH1 rs1799977 com os níveis de MN

induzidos por 131I um mês após a terapia foi particularmente robusta, uma vez que o

valor p desta associação apresentou elevada significância e que esta associação foi

replicada em dois grupos independentes sujeitos a doses distintas de 131I.

Globalmente, este trabalho sugere um envolvimento de SNPs em diferentes vias de

reparação de ADN na suscetibilidade a DTC (possivelmente com efeitos cumulativos) e

também na extensão do dano genético induzido por 131I em linfócitos de pacientes com

DTC (ou seja, na sensibilidade destes pacientes ao 131I). Se confirmados e validados

através de estudos adicionais com maior poder resolutivo, estes resultados poderão

contribuir tanto para a identificação de indivíduos com risco aumentado de DTC

(permitindo a otimização das políticas de prevenção do cancro) como para a

personalização da terapêutica com 131I de acordo com o perfil individual do paciente

(melhorando assim a relação risco-benefício desta terapêutica e os resultados clínicos

finais em pacientes DTC).

xxxiv

Chapter I

Introduction

2

3

Chapter I - Introduction

Thyroid cancer (TC)

A brief overview on the anatomy and physiology of the thyroid gland

The thyroid gland is one of the largest endocrine glands, commonly weighing between

15 to 20 grams. It is located in the neck, bellow the larynx, anterior to the trachea and

consists of two lobes on either side of this organ (Figure 1.1). The thyroid gland is

organized in follicles that comprise a single layer of follicular cells lining a colloid-filled

luminal cavity where thyroid hormones are stored. Besides these follicular cells – which

are the most abundant thyroid cells and synthesize the thyroxine and triiodothyronine

hormones (also called T4 and T3, respectively) – the thyroid gland is also composed of

larger but less abundant parafollicular (or C) cells that are organized in clusters between

the follicles and produce calcitonin (Figure 1.2). While calcitonin is an important hormone

for calcium metabolism, T4 and T3, which contain 4 and 3 atoms of iodine, respectively,

increase the metabolic rate in most body cells. The production of T4 and T3 by thyroid

follicular cells (also known as thyrocytes) is controlled mainly by thyroid-stimulating

hormone (TSH, secreted by the anterior pituitary gland) and requires the uptake of iodide

(I-, the ionized form of iodine) from the bloodstream into the thyrocytes (1).

Figure 1.1. Anatomy of the thyroid gland, graphic representation.

Trachea

Thyroid gland, right lobe

Thyroid gland, left lobe

Thyroid gland, isthmus

Cricothyroid muscle

Cricoid cartilage

Thyroid cartilage

4

Figure 1.2. Histology of the thyroid gland, graphic representation.

Thyroid follicle

Follicle lumen (coloid)

Folliclular cell

Blood capillary

Parafollicular (C) cell

Extracellular matrix

Thyrocytes possess a specialized mechanism for iodide uptake and accumulation that

allow it to be preferentially taken up by these cells and trapped in the follicular lumen

where it accumulates. This specialized mechanism, depicted in Figure 1.3, involves 1)

the sodium-iodide symporter (NIS), a trans-membrane transporter encoded by the

SLC5A5 gene, highly expressed on the basolateral membrane of thyroid follicular cells

where it promotes the active transport of iodide into thyrocytes (2-4); 2) pendrin (PDS),

a transporter located at the apical surface of thyrocytes that promotes the passive

transport of iodide to the lumen; 3) thyroid peroxidase (TPO), that oxidizes iodide with

hydrogen peroxide (H2O2) produced mainly by dual oxidase-2 (DUOX2); and 4)

thyroglobulin (Tg), a glycoprotein accumulated in the lumen, to whose tyrosine residues

iodine is conjugated in a process termed “organification” (2-4). Secretion of T4 and T3 by

the thyroid gland requires the uptake of thyroglobulin complexes back to the thyrocytes

by pinocytosis, release of free T4 and T3 from thyroglobulin in digestive vesicles and

secretion of the free hormones into the bloodstream (1, 3, 4).

5

Figure 1.3. The thyrocyte: mechanisms for the uptake/accumulation of Iodide and for the

production and release of thyroxine (T4) and triiodothyronine (T3), graphic representation.

I-

I-

I-

Tg

Na+

Na+

K+

K+

H2O2

O2

T3

T4

T3

T4

Tg-T3

Tg-T4

Tg-T3

Tg-T4

Tg-DITTg-MIT

I-

T3

T4

Tg

I-, Iodide; Na+, Sodium; K+, Potassium; NIS, Sodium-iodide symporter; Na+/K+ ATPase,

Sodium-Potassium pump; PDS, Pendrin; DUOX2, Dual oxidase-2; TPO, Thyroid

peroxidase; Tg, Thyroglobulin; O2, Molecular oxygen; H2O2, Hydrogen peroxide; Tg-MIT,

mono-iodotyrosine; Tg-DIT, diiodotyrosine; Tg-T4, Thyroglobulin-thyroxine complex; Tg-

T3, Thyroglobulin-triiodothyronine complex; T4, Thyroxine; T3, Triiodothyronine.

Classification of follicular cell-derived thyroid tumours

Thyroid gland tumours are a heterogeneous group of neoplasms that may virtually arise

from any of the different cell types that are present in the thyroid gland. Such diversity is

evident even when restricting our attention to malignant tumours of follicular cell origin,

the most abundant type of cell in the thyroid gland. The latest World Health Organization

(WHO) classification of tumours of the thyroid gland (5), which incorporates the most

recent advances in this field (including important developments in the molecular-genetic

characterization of follicular cell derived thyroid tumours), reflects such complexity:

6

compared to the previous edition (6), among other changes, new borderline categories

such as “Other encapsulated follicular-patterned thyroid tumours” have been introduced,

Hürthle (oncocytic) cell tumours have been established as a distinct category and the

range of variants in the long-existent papillary (PTC) and follicular (FTC) thyroid

carcinoma categories has been expanded, reorganized and better characterized in order

to emphasize differences in tumour biological behaviour, aggressiveness and prognostic

(7).

Among malignant thyroid tumours arising exclusively from follicular thyroid cells (Table

1.1), PTC and FTC are the most common categories, representing 80-85% and 10-15%

of cases, respectively (8). A set of diagnostic nuclear features are observable in PTC but

not in FTC and contribute to the histological distinction of these malignancies that also

differ in regard to other aspects. Nevertheless, since morphological features of

differentiated follicular cells are retained in both tumour categories, these are often

considered together and collectively referred to as well-differentiated thyroid carcinoma

(DTC). Despite important differences exist between tumour variants and subtypes, DTC

most frequently presents with indolent behaviour and remains iodine-avid, which results

in an excellent prognosis and low mortality rate. Anaplastic thyroid carcinoma (ATC),

despite also of thyroid follicular cell origin, is in sharp contrast with DTC: ATC represents

only a small fraction of TC cases (less than 2%) but is extremely aggressive and lethal.

Its poorly- or undifferentiated cells are often refractory to treatment, resulting in high

treatment failure rate, poor median survival (around 6 months from the time of diagnosis)

and high mortality rate (almost 100% disease-specific mortality and approximately half

of TC deaths). ATC frequently arises in patients with pre-existing DTC (most commonly,

PTC), suggesting that it may arise from de-differentiation of DTC. Finally, poorly

differentiated thyroid carcinoma (PDTC), which also arises from thyroid follicular cells,

presents as an intermediate tumour between DTC and ATC in terms of morphology and

biological behaviour: cell differentiation is limited, invasiveness is high, response to

radioiodine therapy is poor and prognosis is variable, depending on a number of

clinicopathological, histological and molecular features. Like ATC, PDTC represents less

than 2% of TC cases (5, 9, 10).

7

Table 1.1. Follicular cell-derived malignant tumours of the thyroid gland, according to the latest WHO classificationa.

WHO category Papillary thyroid carcinoma

(PTC)

Follicular thyroid carcinoma

(FTC)

Poorly differentiated thyroid

carcinoma (PDTC)

Anaplastic thyroid

carcinoma (ATC)

Variants Papillary carcinoma

Follicular variant

Encapsulated variant

Papillary microcarcinoma

Columnar cell variant

Oncocytic variant

Minimally invasive

Encapsulated, angioinvasive

Widely invasive

Differentiation status Well-differentiated Well-differentiated Poorly-differentiated Undifferentiated

Relative frequency 80-85% 10-15% <2% <2%

Common mutations BRAF (40-45%)

RAS (15-20%)

TERT (10%)

RET/PTC (5-10%)

NTRK3 (<5%)

NTRK1 (<5%)

ALK (2%)

RAS (30-40%)

PPARG (30-35%)

TERT (10-20%)

PIK3CA (<10%)

PTEN (<10%)

TERT (30-40%)

RAS (20-40%)

TP53 (20-30%)

BRAF (10-20%)

ALK (10%)

CTNNB1 (<10%)

AKT1 (5-10%)

PIK3CA (5-10%)

TP53 (50-80%)

TERT (40-50%)

BRAF (30-40%)

RAS (20-30%)

CTNNB1 (<20%)

PIK3CA (10-20%)

ALK (5%)

aOnly categories exclusively composed of malignant tumours were considered. Additional categories comprising mostly benign tumours

(“Hyalinizing trabecular tumour”), tumours with uncertain malignant potential (“Other encapsulated follicular-patterned thyroid tumours”) and mixed

benign and malignant tumours (“Hürthle cell tumours”) are also listed in the WHO classification but were not included in this review.

8

Molecular pathogenesis of follicular cell-derived thyroid tumours

The diversity observed in histological and clinical features of follicular cell-derived thyroid

tumours is paralleled by an equally important heterogeneity in their genetic and

molecular profile. Indeed, research performed over the last few decades has shed light

on the mutational landscape of thyroid carcinogenesis and allowed a better

characterization and understanding of the molecular pathogenesis of this complex

disease. Such knowledge is of utmost value as these mutations may be used as

molecular biomarkers to improve diagnostic accuracy, prognostic predictions and

therapeutic decisions, paving the way, for example, for personalizing TC therapy though

specifically targeting the disease-causing mutated gene or the pathways involving it. The

incorporation of such genetic and molecular information into the latest versions of the

WHO classification of tumours of the thyroid gland (5) and important clinical guidelines

such as the one published by the American Thyroid Association (ATA) (11) reflect their

importance in current day clinical medicine.

According to recent reviews on the subject (8, 12-16), PTC appears to be driven mostly

by early genetic events in genes encoding effectors of the mitogen-activated protein

kinase (MAPK) pathway: BRAF and RAS mutations as well as RET/PTC and NTRK gene

rearrangements thus predominate in PTC while, in turn, mutations activating the

phosphatidylinositol 3-kinase (PI3K) pathway – in the RAS oncogene (a dual activator of

both the MAPK and PI3K pathways) or to a lesser extent, in PIK3CA or PTEN (a negative

regulator of PI3K signalling) – are, together with PAX8/PPARG rearrangements, the

early genetic changes most commonly observed in FTC. The mutational signature of

DTC also appears to deviate according to the specific cancer variant and aetiological

factors as, among PTC, for example, activating RAS mutations (and, to a less extent,

PAX8/PPARG rearrangements) are rarely observed in classical papillary carcinoma

cases but are much more frequent in follicular variant PTC (whose mutational profile thus

approximates to that of FTC). The opposing pattern is observed for the BRAF V600E

activating mutation, which is essentially the single most common genetic event in the

onset of PTC and often associated with more aggressive, therapy-resistant disease.

Also, gene rearrangements such as those involving the RET, NTRK3, NTRK1, BRAF

and PPARG genes present a much higher frequency among radiation-induced PTC than

among sporadic PTC cases which, in turn, present mostly with either BRAF V600E or

RAS point mutations. Interestingly, RAS mutations are also commonly observed in

9

follicular thyroid adenomas (FTA), suggesting 1) the premalignant nature of FTA and 2)

the early role of RAS mutations in thyroid carcinogenesis.

Progressive accumulation of genetic (and/or epigenetic) alterations in both MAPK and

PI3K signalling pathways (as well as in other pathways) leads to TC progression and

dedifferentiation into PDTC and, eventually, ATC (Figure 1.4). Co-occurrence of BRAF

and RAS mutations is common in ATC (unlike in DTC), as are point mutations in TP53

(the most frequently mutated gene in ATC), TERT (mutations in the telomerase reverse

transcriptase promoter region are strongly associated with a worse outcome), CTNNB1

(activating mutations lead to aberrant activation of the WNT-β-catenin signalling pathway

which is involved in the regulation of cell growth and proliferation) and PIK3CA (which

encodes a catalytic subunit of PI3K). Except for ALK and PIK3CA mutations (which can

already be observed in PTC and FTC, respectively, but occur more frequently in ATC),

these genetic alterations (and other less frequent mutations, rearrangements and copy-

number gains in genes such as AKT1, EGFR, VEGFR1, PDGFRB, NF1, MTOR or

EIF1AX) appear to be late events, associated with dedifferentiation and progression from

DTC as well as disease aggressiveness (8, 12-16).

Figure 1.4. Molecular pathogenesis of follicular cell-derived thyroid tumours (adapted

from (13)).

Follicular

cell

PTC

FTA FTC

PDTC ATC

MAPK

pathway

PI3K

pathway

PI3K

pathway

MAPK

pathway

MAPK pathway

PI3K pathway

PI3K

pathway

PI3K

pathway

MAPK

pathway

PTC, Papillary thyroid cancer; FTA, Follicular thyroid adenoma; FTC, Follicular thyroid

cancer; PDTC, Poorly-differentiated thyroid cancer; ATC, Anaplastic thyroid cancer;

MAPK, Mitogen-activated protein kinase; PI3K, phosphatidylinositol 3-kinase.

10

Finally, a growing body of evidence [reviewed elsewhere (13, 15, 17-19)] suggests that

epigenetic events (e.g. PTEN promoter hypermethylation) and alterations in the

expression of microRNAs (miRNA, e.g. miR-187, miR-221, miR-222, miR-146b, miR-

155, miR-181b, miR-224 and miR-197), long non-coding RNAs (lncRNA) and circular

RNAs (circRNA) may also contribute to TC pathogenesis. Through modulation of gene

expression, such events can drive the aberrant activation of oncogenic signalling

pathways and the downregulation of thyroid-specific genes, thus contributing – alongside

with genetic mutations – to TC development, progression and dedifferentiation. These

events are common in TC and their importance to the pathogenesis of this disease is

increasingly recognized. Nevertheless, as they fall out of the scope of this work, such

aspects will not be further detailed here.

Epidemiology of follicular cell-derived thyroid tumours

The incidence of TC is far from that observed for other malignancies such as lung, breast

and colorectal cancer: according to the latest data from the International Agency on

Cancer Research (IARC), TC accounts for only 3.1% of new cancer cases diagnosed all

over the world and presents with an overall low mortality rate (20). It is, nevertheless, the

most common endocrine malignancy and presents some distinctive features that are

worth of notice, as they may potentially constitute reason for concern. TC is unevenly

distributed between sexes, incidence being about two to four times higher in women than

in men. This results in a high 5-year prevalence in women, where TC is even ranked as

the third most common malignancy, only after breast and colorectal cancers (20). Such

sex distribution difference is particularly apparent for PTC (it is not observed, for

example, in the more aggressive ATC) and has been consistently observed across time

and space (21). Furthermore, despite most cases are diagnosed after the age of 30

years, TC is (along with breast cancer) one of the two most common malignancies in

adolescents and young adults (ages 15–39 years), placing the median age at diagnosis

below that for most other types of cancer (10, 20-23).

But perhaps the most striking epidemiological feature of TC is its fast-rising incidence

(Figure 1.5): despite a slight reduction over the last few years - possibly driven by the

latest revision of the ATA clinical guidelines for TC diagnosis, treatment and follow-up

(11, 24) (see below) - TC incidence has been rapidly and steadily increasing over the

last three decades, more and faster than any other malignancy (9, 25-27). Such dramatic

11

increase in incidence rates is observed globally (according to data from the Cancer

Registries of the USA, Canada, Australia, Europe, China and other parts of Asia and

South America) (21, 26, 28) and is largely driven by the rising incidence of small size

papillary thyroid microcarcinomas (PTMC; PTC ≤1.0 cm maximum diameter) – the least

aggressive variant of TC – and, in particular, of its follicular variant (FVPTC) (9, 21, 26,

27, 29). Incidence rates of other TC histological subtypes have increased only very

modestly or not at all (FTC) or have even shrunk (ATC) (9, 26, 29). Since the increase

in incidence is mostly due to small papillary tumours and these are the most treatable

ones, the rising incidence of TC is unaccompanied by disease-specific mortality rates

(21, 25, 27, 28). The underlying causes of this steep increase in TC incidence are still a

matter of debate: many experts argue that this increase may be only apparent, mostly

reflecting increased detection of small, localized, asymptomatic and stationary tumours

(PTMC), clinically irrelevant lesions that, if undetected like in the past, would be of no

consequence for the patient’s health or survival (9, 21, 25, 27, 28). Increased medical

surveillance and more intense diagnostic scrutiny resulting from the introduction in the

1980s (and subsequent widespread use) of more detailed diagnostic techniques – high-

resolution neck ultrasonography and fine-needle aspiration (FNA) biopsy (followed by

detailed histologic examination) of all suspicious benign thyroid nodules – and sensitive

imaging procedures – computed tomography (CT), positron emission tomography (PET)

and magnetic resonance imaging (MRI) – may have contributed to the incidental

discovery of such subclinical lesions (“surveillance bias”) which, undoubtedly, account

for at least some of TC diagnoses in the last decades (9, 21, 27, 28). Such overdiagnosis

hypothesis is therefore generally accepted and has even prompted the revision of the

ATA clinical guidelines for TC diagnosis, treatment and follow-up (11, 24, 25, 27),

reflecting concern that TC overdiagnosis will result in potentially harmful overtreatment

of subclinical lesions. Other authors argue, however, that despite higher detection rates

associated with overdiagnosis likely contribute to the rising incidence of TC, it may not

be the only, exclusive, explanation. In fact, many epidemiological, biological and clinical

evidences suggest that a true rise in the number of TC cases may also be occurring, the

changing trend in TC incidence probably being multifactorial and influenced by several

recent environmental factors (21, 25, 27-30). Increasing exposure to ionizing radiation

(IR) – mainly from medical sources (e.g. 131I), obesity, cigarette smoking, iodine

fortification and supplementation as well as increased exposure to xenobiotics of

industrial (e.g. solvents, plastic constituents and heavy metals), agroindustrial (e.g.

pesticides, repellents and preservatives) or natural (e.g. volcanic) origin have been

12

suggested as potential contributors to the worldwide increase in TC incidence (21, 27-

30). It is yet unclear which (if any) of such potential risk factors are truly involved.

Figure 1.5. Long-term (1975-2017), age-adjusted incidence rates of thyroid cancer and

its main histological categories (PTC and FTC) in the US population, according to the

SEER 9 database (adapted from (23)).

1970 1980 1990 2000 2010 2020

0

50

100

150

200

Year of diagnosis

Ra

te p

er

10

0,0

00

Thyroid cancer (all types)

Follicular thyroid cancer (FTC)

Papillary thyroid cancer (PTC)

Data Source: SEER 9 areas [http://seer.cancer.gov/registries/terms.html] (San

Francisco, Connecticut, Detroit, Hawaii, Iowa, New Mexico, Seattle, Utah, and Atlanta).

Rates are per 100,000 and are age-adjusted to the 2000 US Population.

Aetiology and risk factors for the development of follicular cell-derived thyroid tumours

Despite recent progress, our knowledge of TC aetiology is still limited and remains

largely unexplained (not very different from what was known 3-4 decades ago), as non-

modifiable risk factors (such as patient age, sex, ethnicity and family history) remain the

strongest risk predictors (21). DTC aetiology is probably multifactorial, with both genetic

and environmental factors being involved (Figure 1.6).

IR exposure (a DNA-damaging agent), particularly during childhood and adolescence,

has long been demonstrated to increase the risk of DTC (PTC in particular) and remains

the most robust modifiable risk factor for this malignancy (9, 21, 25, 26, 28, 30-32).

Thyroid exposure to IR may occur either from external sources (environmental and

therapeutic irradiation of the head and neck with X-rays and gamma radiation - e.g.

dental X-rays and head–neck CT scans) or by ingestion or inhalation of radioactive

material (e.g. radon and radioiodine) (9, 26, 28, 30). Recent studies, however, have

13

suggested other modifiable risk factors for TC (21, 25, 28-30). These include dietary

habits and nutritional factors (e.g. Iodine intake, carbohydrate consumption, fish and

vegetable ingestion, Selenium and Vitamin D deficiency) (21, 26-29, 33), obesity (21, 28,

33), tobacco smoking (21, 26, 28), living in volcanic areas (possibly due to

biocontamination with nonanthropogenic pollutants such as heavy metals which are

increased in water, atmosphere, ground and food of volcanic origin) (26-30) and

exposure to environmental carcinogens (e.g. nitrite and nitrate from processed meat and

from fertilizer-contaminated drinking water) (26, 27, 29, 30) and to other endocrine-

disrupting chemicals (e.g. polybrominated diphenyl ethers from flame retardants,

phthalates, bisphenol A, polychlorinated biphenyls, pesticides, perfluorinated

compounds, perchlorates) (26, 28-30). The latter could contribute to TC through

interference with hormone homeostasis or with the detoxification system, leading to

follicular cell proliferation, hypertrophy and hyperplasia or to increased susceptibility to

environmental carcinogens, respectively (27, 29, 30). Increased exposure to some of

these factors in recent decades may have contributed to the increasing incidence of DTC

observed worldwide but confirmatory studies are still needed.

Figure 1.6. Modifiable factors suggested to modulate TC risk (adapted from (21, 26-30,

33)).

Ionizing radiation:

• Natural sources

• Nuclear accidents

• Medical irradiation

Diet and nutrition:

• Iodine

• Carbohydrates

• Fish

• Red and processed meat

• Fruit and vegetables

• Selenium

• Vitamin D

Environmental

chemical exposure:

• Heavy metals

• Nitrates

• Endocrine-disrupting

chemicals

Clinical conditions:

• Obesity

Lifestyle habits:

• Tobacco smoking

• Betel quid chewing

• Alcohol consumption

Hereditary factors could also constitute important predisposing factors for TC: DTC is

typical of several inherited tumour syndromes (e.g. Cowden syndrome, familial

adenomatous polyposis, Carney complex) and, despite no specific mutation has been

associated with familial predisposition, familial DTC risk (particularly among first-degree

14

relatives) is actually one of the highest among cancers not showing typical Mendelian

inheritance (28, 34). Such high heritability strongly suggests that hereditary factors, most

probably multiple common low-penetrance or rare moderate-penetrance alleles, are also

involved in DTC susceptibility, especially if considered together with exposure to

environmental risk factors such as IR (DTC as the result of the interplay between different

genetic and environmental risk factors).

Identifying such genetic variants so that these may be used as susceptibility markers for

DTC is therefore an important challenge to which much effort has been put. So far,

multiple single nucleotide polymorphisms (SNPs) have been suggested to affect DTC

susceptibility (implicated as TC risk factors). The most robust evidence – provided by

several genome-wide association studies (GWASs) (35-39), with independent replication

across different populations – establishes markers at 9q22.33 (FOXE1), 14q13.3 (NKX2-

1), 2q35 (DIRC3) and 8p12 (NRG1) as the strongest genetic susceptibility markers for

sporadic DTC (especially in European populations) (reviewed in (14, 34, 40-42)). Despite

additional markers (still requiring confirmation and replication) have recently been

suggested (37-39, 43-45), the DTC risk alleles proposed to date by GWAS (Table 1.2)

are still largely insufficient to explain the estimated heritability of DTC (34). Numerous

candidate gene association studies (CGASs) have yielded further potential DTC risk

markers, namely germline SNPs within genes involved in cell-cycle control and apoptosis

(e.g. TP53, WDR3, MDM2 and BCL2), DNA repair (see below), intracellular signalling

(e.g. RET, HRAS and PDGFRA), endobiotic or xenobiotic metabolism (e.g. NAT2,

SOD1, FMO3, along with several members of the GST and CYP superfamilies), thyroid

physiology (e.g. TG, THRA and TPO) or immune/inflammatory response (e.g. ALOX12,

TICAM1 and IL11RA) (reviewed in (46-49)). Again, many of these findings have not been

properly replicated. It is possible that other, yet unidentified, genetic variants (either alone

or in combination with other genetic or environmental factors) have a relevant impact on

DTC susceptibility and thus explain part of the missing heritability of the disease. Their

identification is therefore highly desirable.

15

Table 1.2. Single nucleotide polymorphisms (SNPs) proposed by genome-wide

association studies (GWASs) as genetic susceptibility markers for sporadic DTC (only

markers replicated in different populations are shown).

Locus Genea Marker (SNP rs no) Ref.b Replication studiesc

Strong evidence (independent replication through a separate GWAS or CGAS)

9q22.33 FOXE1 rs965513 (35)d (36-39, 50, 51)d, (52-61)e

rs1867277 (52)e (38, 50)d, (54, 55, 59-62)e

14q13.3 NKX2-1 rs944289 (35)d (36-39, 51)d, (53, 54, 56, 57,

59-61)e

rs116909374 (51)d (36)d, (57, 61)e

8p12 NRG1 rs2439302 (51)d (36, 37, 39)d, (56, 57, 59)e

2q35 DIRC3 rs966423 (51)d (36)d, (56, 57)e

5p15.33 TERT rs2736100 (63)e (36)d

Moderate evidence (replication through the same GWAS)

9q22.33 FOXE1 rs7037324 (38)d --

2q35 DIRC3 rs6759952 (37)d --

1q42.2 PCNXL2 rs12129938 (36)d --

1p31.3 NFIA rs334725 (51)d --

7q21 IMMP2L rs10238549, rs7800391 (37)d --

3q25.32 RARRES1 rs7617304 (37)d --

9q34.3 CARD9 rs10781500 (37)d --

14q24.3 BATF rs10136427 (43)d --

20q11.22 DHX35 rs7267944 (43)d --

3q26.2 TERC rs6793295 (36)d --

5q22.1 NREP rs73227498 (36)d --

10q24.33 OBFC1 rs7902587 (36)d --

15q22.33 SMAD3 rs2289261, rs56062135 (36)d --

aFor markers in intergenic regions, the most likely nearest gene is indicated; bboth GWAS

and GWAS-based studies (mixed design, reanalysing or extending data from prior

GWAS) are considered; cmarkers in complete or strong linkage disequilibrium with the

originally reported are also considered; dGWAS; eCCAS. DTC, well-differentiated thyroid

cancer; GWAS, genome-wide association study; CGAS, candidate-gene association

study; SNP, single nucleotide polymorphism; Ref., original study (reference).

16

Therapeutic options for the treatment of follicular cell-derived thyroid tumours

Standard treatment of DTC involves a combination of surgical, hormonal, and nuclear

medicine therapies. Initial management of the disease consists of surgical resection by

way of lobectomy or total thyroidectomy (with or without dissection of involved regional

lymph nodes), frequently accompanied by adjuvant radioactive iodine (RAI) therapy to

ablate remnant normal thyroid tissue and to eradicate potentially persistent microscopic

tumour foci. Since TSH may stimulate the growth of tumour cells, TSH suppression

therapy after initial surgery may also be recommended, especially for patients with

persistent structural disease or with incomplete or indeterminate response to treatment

(12, 64, 65). The minority of patients with advanced and metastatic disease (iodine-

resistant in most cases) may also benefit from the use of external beam radiation therapy

(EBRT) or other locoregional therapies, as well as systemic therapies involving

conventional cytotoxic agents (e.g. doxorubicin, of limited benefit) or novel

chemotherapeutics such as multikinase inhibitors, which increase progression-free

survival: most of these were initially used only as “salvage” therapy but clinical trials

confirming the usefulness of these targeted agents in the treatment of metastatic TC are

accumulating. Levantinib and Sorafenib, for example, are approved by both the US Food

and Drug Administration (FDA) and the European Medicines Agency (EMA) and are

currently considered first-line therapy for 131I-resistant metastatic DTC (12, 64-66). An

overview of the currently approved intervention options for the management of DTC

patients is depicted in Figure 1.7. Other promising approaches are currently under study

but remain yet unapproved in the context of DTC: the use of kinase inhibitors directed

against specific oncoproteins of the MAPK pathway (e.g. dabrafenib, a BRAF inhibitor,

to be used – alone or in combination with Trametinib, a MEK inhibitor – in BRAF-mutated

DTC patients) appears to be effective, with the additional advantage of inducing the

redifferentiation of the tumour thus re-sensitizing it to 131I. Further developments on the

field are awaited soon, depending on whether ongoing clinical trials confirm (or not) these

promising findings (64, 66).

17

Figure 1.7. Intervention options for the management of DTC (adapted from (64, 65)).

DTC

Primary tumour

management

Follow-up and management of residual

and advanced/metastatic disease

Active

surveillanceSurgeryb RAIc

Active

surveillance

TSH

supressionRAId

Locoregional

therapye

Systemic

therapy

- 30 mCi

- 30-100 mCi

- ≥100 mCi

- Lobectomy

- Total thyroidectomy

- Neck dissection

- Levothyroxine - ≥100 mCi

- Surgery

- EBRT

- Percutan. ablation(RFA/laser)

- Embolization

- Bone resorption

inhibitors (e.g.bisphosphonates)

- Multikinase

inhibitors (e.g.Levantinib,Sorafenib)

- Conventionalcytotoxictherapy (e.g.doxorubicin)

RAI-responsive

patientsRAI-refractory patients

Patients with

persistent disease,

incomplete response

to treatment or high

risk of recurrence

Patients with low to high risk of recurrencePatients with very low

risk of recurrencea

Patients with stable

assymptomatic

disease

aUnifocal papillary microcarcinomas with no evidence of extracapsular extension or

lymph node metastasis; bFor patients with T4b tumours (TNM staging system) – Tumour

invades prevertebral fascia or encasing the carotid artery or mediastinal vessels from a

tumour of any size – EBRT should be considered instead of surgery; cRAI therapy should

be preceded by TSH stimulation – either by recombinant human TSH administration or

by levothyroxine withdrawal – to optimise 131I uptake; din RAI-responsive disease, RAI

administration should be repeated every 6-12 months until a maximal cumulative activity

of 600 mCi (higher doses evaluated on a case-by-case basis); eThe recommended

locoregional approach is site-specific and will vary whether the patient presents with

bone, lung, liver or other metastases or with local invasion of the upper aerodigestive

tract. DTC, well-differentiated thyroid carcinoma; RAI, radioactive iodine; TSH, thyroid-

stimulating hormone; EBRT, External beam radiotherapy; RFA, radiofrequency ablation.

18

Despite the current clinical practice guidelines for the management of DTC patients (11,

65) advocate, for safety reasons, a reduction in RAI use (more stringent eligibility criteria,

lower 131I doses) in low-risk DTC cases (see below), 131I-based RAI therapy remains

widely used and an indispensable tool in the management of DTC. Its mechanism of

action, efficacy and safety concerns thus merit a more in-depth view: as illustrated in

Figure 1.8, the efficacy (and usefulness) of 131I on DTC therapy relies on its ability to be

preferentially taken up by and trapped in normal or neoplastic thyroid follicular cells,

where it accumulates. 131I uptake and accumulation into thyrocytes takes advantage of

these cells’ specialized mechanism for iodide uptake, mimicking this physiological

process. 131I trapped in the thyroid gland undergoes decay, releasing both beta and

gamma radiation. The high-energy β- electrons thus released are able to interact with

matter while passing through it. While doing so, they transfer their energy, causing

multiple ionizations and atom excitation. Breakage of chemical bonds ensues, resulting

in direct and indirect damage to proteins, DNA and other cell components. Indirect

damage is caused by highly reactive free radicals released from IR-induced water

radiolysis. In face of the devastating DNA damage (mostly, oxidative lesions, single and

double strand breaks and DNA crosslinks) locally inflicted by these high-energy

electrons, the DNA damage response is activated, leading to radiation-induced

apoptosis (possibly p53-mediated), hence thyroid cell death. Necrotic cell death may

also occur, especially for higher radiation doses. Because the capacity of 131I-released

electrons to penetrate soft tissues is limited (about 1 mm), 131I cytotoxicity is restricted to

cells that are able to uptake iodine and those in their immediate vicinity. Radiation

cytotoxicity localized to the thyroid gland thus allows for effective remnant thyroid tissue

ablation and persistent tumour foci eradication (9, 67-69).

19

Figure 1.8. Mechanism of 131I-induced thyroid cell death, graphic representation

(adapted from (67)).

131I

131I

131I

β particles

raysWater

radiolysis

•OH

MRN

ATM / ATR activation

p53 nuclear accumulation

PUMA / NOXA

transcription

Bcl2 inactivation / Bax

activation

Mitochondrial release of

cytochrome c

Caspase activation

Apoptotic cell death

131I, radioactive iodine; NIS, Sodium-iodine symporter; •OH, hydroxyl radicals; MRN,

Mre11-Rad50-Nbn complex.

Thyroid follicular cells abundantly express the sodium-iodide symporter (NIS) and thus

concentrate most of the 131I administered. However, to a minor extent, other tissues (e.g.

exocrine glands, stomach, kidney and breast) may also express NIS and thus

concentrate 131I (27, 70). Treatment with 131I may therefore result in acute side effects

such as mild and transient nausea, sialadenitis, ageusia, epigastralgia, xerophthalmia,

sperm abnormalities and, eventually, radiation-associated thyroiditis (correlated to the

size of the remnant thyroid tissue) (9, 64, 70, 71). More importantly, the use of 131I,

especially in high cumulative doses (>500 mCi), is significantly associated with an

increased risk of developing secondary malignancies (e.g. leukaemia, salivary tumours,

colorectal cancer and soft tissue tumours) (9, 21, 27, 64, 70, 71). This is especially

relevant since - given the particular characteristics of TC (younger age at diagnosis, high

long-term survival and indolent behaviour for most TC cases) – the majority of TC

patients have many years to experience the negative effects of TC diagnosis and

20

treatment (21). Reflecting concern over the potential problem of overdiagnosis and

overtreatment of DTC, a typically indolent disease where serious treatment-related

morbidity such as secondary malignancies may not be justified, the ATA clinical practice

guidelines for the management of DTC patients (11) were revised in 2016, now

recommending a more cautious approach in the diagnosis and treatment of such

patients. In line with such concerns, the current ATA guidelines, among other

recommendations, now define more stringent criteria to initiate the diagnostic work-up

upon thyroid nodule detection, propose the use of molecular testing (e.g. next-generation

sequencing) to improve risk stratification for treatment decisions, suggest alternatives to

surgical resection (or less extensive surgery) in selected patients and advocate a

reduction in RAI use (less frequent use and use of lower 131I doses, e.g. 30-50mCi) in

very low and low-risk DTC cases, especially in younger individuals (11, 12, 21, 24, 64).

Accordingly, higher 131I dose regimens (100-200 mCi) should be reserved for special

cases such as those with incomplete resection, invasive primary tumours, tumours of

intermediate differentiation, or distant metastasis). It should be mentioned, however, that

these recommendations have not been fully endorsed by other scientific societies (72,

73). A joint statement on the issue was recently published (74) and two large prospective

randomized clinical trials (NCT01837745-ESTIMABL2 and NCT01398085-ION) are

ongoing to clarify whether postoperative 131I should be used in low-risk DTC patients or

not (64, 65). A consensus statement from the Japan Association of Endocrine Surgery

on the use of active surveillance in low-risk PTMC has also been published recently (75).

Prognosis of follicular cell-derived thyroid tumours

Two staging systems based on distinct prognostic endpoints are widely used in current

practice for the management of DTC: the Union for International Cancer Control (UICC)

tumour, node, metastasis (TNM) classification of malignant tumours (76) estimates the

risk of cancer-related death while the ATA risk stratification (11) estimates the likelihood

of persistent or recurrent DTC after initial treatment. Both the ATA risk stratification

system, which categorizes patients into low (<5%), intermediate (5-20%) or high (>20%)

risk of recurrence groups, and the TNM classification, which is summarized in Table 1.3,

use clinico-pathological data available at the time of initial surgery to define the most

appropriate management strategy. Moreover, according to the ATA risk stratification

system, risk estimates may be adjusted during follow-up to reflect the evolution of the

disease and the extent of therapy.

21

Table 1.3. UICC TNM staging system for tumours of the thyroid glanda, with estimates

of TC-related death at 10 years (adapted from (64, 65)).

Disease

stage

Tumour size

(T)

Lymph node

involvement (N)

Metastases

(M)

Risk of TC-related

death (10 years)

Age <55 years

I Any T Any N M0 <2%

II Any T Any N M1 ~5%

Age ≥years

I T1 or T2 N0 or Nx M0 <2%

II T1 or T2 N1 M0 ~5%

II T3a or T3b Any N M0 ~5%

III T4a Any N M0 5-20%

IVa T4b Any N M0 >50%

IVb Any T Any N M1 >80%

aIncluding papillary, follicular, Hürthle cell and poorly differentiated carcinomas. T1,

tumour of ≤2 cm limited to the thyroid; T2, tumour of >2 cm and ≤4 cm limited to the

thyroid; T3a, tumour of >4 cm limited to the thyroid or with microscopic extrathyroidal

extension to perithyroidal soft tissue; T3b, tumour with gross extrathyroidal extension

invading only perithyroidal strap muscles; T4a, tumour with gross extrathyroidal

extension invading subcutaneous soft tissues, larynx, trachea, oesophagus, or recurrent

laryngeal nerve with/without lymph node metastases; T4b, tumour with gross

extrathyroidal extension invading prevertebral fascia or encasing the carotid artery or

mediastinal vessels; N0, absence of lymph node metastases; Nx, lymph node status

unknown; N1, presence of regional lymph node metastases; M0, absence of distant

metastases; M1, presence of distant metastases. UICC, Union for International Cancer

Control; TNM, tumour, node, metastasis; TC, thyroid cancer;

Overall, TC prognosis is generally good: the majority of cases (PTC and FTC, mostly)

have indolent behaviour and usually respond favourably to standard therapy (9, 10, 21),

translating into survival rates higher than 95% at 20 years (10). However, despite such

generally high long-term survival and low disease-specific mortality, the recurrence rate

is still high (10) – around 10-30% in DTC patients, mostly locoregional recurrence (9) –

and approximately 10-15% of DTC patients present distant metastasis at the time of

diagnosis or during long-term surveillance (9). Also, an estimated 5% of TC cases fails

22

to respond adequately to 131I (radioactive iodine-refractory - RAIR - disease) (10, 77).

Also, PDTC and ATC typically present more aggressive behaviour and poorer prognosis,

in sharp contrast with most DTC (5, 12, 65, 66). Despite other therapeutic options are

available (e.g. novel therapies, such as multikinase inhibitors) (12, 64-66), high risk

patients such as those presenting with surgically inoperative recurrence, RAIR disease,

PDTC and ATC will most likely die of their disease (10). Management of such high risk

cases remains challenging, thus requiring careful identification (based on specific

prognostic factors) so that individual recurrence and survival rates may be estimated,

patients may be allocated to different risk categories and personalized long-term

oncologic surveillance strategies may be implemented (9).

23

DNA repair pathways

Base Excision Repair (BER)

Base excision repair (BER) (Table 1.4, Figure 1.9) is the main pathway responsible for

the recognition, excision and repair of small nonbulky lesions that do not introduce

significant distortions to the DNA double helix. Such lesions occur at the single base level

and typically arise from oxidation, methylation, deamination, alkylation or hydroxylation

reactions that often occur spontaneously or as a result of endogenously formed by-

products of cellular metabolism (e.g. reactive oxygen species). Nevertheless, exposure

to exogenous agents such as IR may also contribute. The process, which is mostly active

in the G1 phase of the cell cycle, aims to remove and replace a damaged nucleotide and

thus restore the correct DNA sequence. It involves several proteins that act via a number

of coordinated sequential ‘cut-and-patch’-type reactions to detect the lesion, remove the

damaged nucleotide (creating, temporarily, an apurimidinic/apurinic (AP) or abasic site)

and fill in the resulting single-stranded gap using the intact complementary strand as

template (78-82).

The initial step, lesion recognition, is performed by a DNA glycosylase that further breaks

the N-glycosidic bond between the damaged DNA base and the sugar-phosphate

backbone, thus excising the damaged base and creating an abasic site. A battery of

substrate-selective DNA glycosylases, recognizing a broad spectrum of DNA lesions, is

constantly scanning the DNA for altered bases. Glycosylases can be monofunctional

(only with glycosylase activity, e.g. MUTYH), bifunctional (with an additional β-lyase

activity, e.g. NEIL1, NEIL2) or both (e.g. OGG1, NEIL3) (78, 81). Depending on whether

the abasic site is created by a monofunctional or a bifunctional glycosylase, two distinct

BER subpathways may ensue, the short-patch and the long-patch BER. The short patch

pathway, which involves the incorporation of a single nucleotide, proceeds through

APEX1 processing of the apurinic/apyrimidinic (AP) site, gap filling by POLβ or POLλ

and ligation by LIG1 or LIG3. The XRCC1 scaffold protein and PARP1 are also involved.

The long patch pathway, in turn, incorporates more than one nucleotide (frequently, 2-

13 nucleotides) through PCNA-mediated POLβ or POLδ/ε repair synthesis, followed by

FEN1-mediated removal of the displaced multi-nucleotide flap and DNA ligation by LIG1.

The short patch pathway predominates in mammals (80, 82).

The vital importance of the BER pathway is illustrated by studies with homozygous

knockout mice demonstrating that inactivation of key components of the BER pathway

24

induces embryonic lethality. This suggests that severe deficiency in such core BER

proteins is not compatible with life. This does not appear to be the case, however, with

glycosylases, whose gene knockout in mouse models does not result in an overt disease

phenotype, possibly because of partial redundant activity (78, 80). In humans, two

important exceptions are worth mentioning: MUTYH-associated polyposis (MAP) and

Hyper-IgM Syndrome Type 5 (HIGM5). MAP is an autosomal recessive form of familial

adenomatous polyposis (FAP) originating from MUTYH missense mutations such as

Tyr176Cys and Gly393Asp and characterized by the appearance of multiple

adenomatous colon polyps or colorectal cancer. The mutation-derived impairment of

MUTYH glycosylase activity interferes with the capacity to repair 8-oxo-7,8-dihydro-2'-

deoxyguanosine (8-oxo-dG), a major oxidative lesion, presumably giving rise to G:C to

T:A transversions, commonly observed in MAP patients. HIGM5, in turn, is a primary

immunodeficiency disorder that has been associated with mutations in another DNA

glycosylase, UNG. Besides its main role in the repair of uracil residues from genomic

DNA, UNG also contributes to the Activation-induced (cytidine) deaminase (AID)-

directed isotype switching during the immune response. Mutation-derived UNG

dysfunction therefore interferes with B cell class switching, hence with the production of

IgG and IgA, the hallmark of hyper-IgM syndromes (80). Genetic defects in the other

BER-associated proteins (e.g. POLβ) have also been linked to neurodegenerative

diseases, aging and cancer risk (80, 81).

Nucleotide Excision Repair (NER)

Nucleotide excision repair (NER) (Table 1.4, Figure 1.9), is a versatile DNA repair

pathway that is capable of repairing: 1) Ultra-violet (UV) light-induced lesions such as

cyclobutane pyrimidine dimmers (CPDs) and (6-4) pyrimidine-pyrimidone photoproducts

(6-4PPs); 2) bulky DNA adducts caused by chemicals such as large polycyclic aromatic

hydrocarbons, benzo[a]pyrene diol-epoxide and nitrosamines; 3) distorting interstrand

crosslinks induced by chemotherapeutic agents (e.g. cisplatin) and even 4) certain

oxidative lesions induced by cyclopurines and lipid peroxidation products (83-85).

The NER DNA repair mechanism involves the action of over 30 proteins and consists of

several sequential steps: lesion detection, opening of a denaturation bubble, incision of

the damaged strand, damaged oligonucleotides displacement, gap filling and ligation

(83, 85, 86). Two NER subpathways are usually defined: global-genome repair (GGR),

detecting and removing lesions throughout the genome (86, 87), and transcription-

25

coupled repair (TCR), that manages the repair of lesions in transcribed strands of

expressed genes (86, 88). GGR and TCR differ mainly in their mode of lesion detection;

the subsequent steps are common to both repair subpathways.

Deficiencies in the NER pathway are associated with rare autosomal recessive human

disorders, such as xeroderma pigmentosum (XP), Cockayne syndrome (CS) and

trichothiodystrophy (TTD) (83, 84, 89).

Mismatch Repair (MMR)

The DNA mismatch repair (MMR) pathway (Table 1.4, Figure 1.9) plays a crucial role in

post-replication repair of errors that, in spite of the proofreading function of DNA

polymerases, inevitably arise during replication: by recognizing and removing such

mispaired nucleotides and insertion–deletion loops (IDLs), MMR prevents base

substitutions or repeat sequence instability thus greatly increasing DNA replication

fidelity and safeguarding genomic integrity (90-92). Briefly, MMR operates through

replication error recognition, performed by the MutS or MutSβ complexes (MSH2-

MSH6 and MSH2-MSH3 heterodimers, respectively), followed by recruitment of MutL

homologs (MLH1–PMS2, MLH1-MLH3 and MLH1-PMS1 heterodimers) to the damage

site. There, the MutL homologs act in coordination with other proteins such as PCNA,

EXO1, polymerase δ and LIG1 to excise the mismatch from the nascent strand,

resynthesize the missing segment and seal the nick (79, 90, 91, 93). Additionally, MMR

appears to contribute to several other cellular processes such as mitotic and meiotic

recombination, immunoglobin class switching and coactivation of oestrogen receptor

alpha (90, 91, 94). Of relevance in relation to cancer susceptibility and therapeutics, the

MMR pathway also cooperates with other repair pathways in the recognition and

subsequent repair of DNA damage induced by IR, UV light, oxidative stress or chemical

carcinogens (e.g., oxidative lesions, double strand breaks, pyrimidine dimers and inter-

strand crosslinks), as well as in the downstream signalling for cell cycle arrest and

apoptosis in response to such lesions, thus contributing to damage-induced cytotoxicity

(90-96). MMR’s role in suppressing genetic instability is therefore critical to

carcinogenesis: loss of MMR (e.g. inactivating mutation) greatly increases the rate of

spontaneous mutation (mutator phenotype) and results in microsatellite instability (MSI),

a hallmark of MMR defects and hereditary nonpolyposis colorectal cancer (HNPCC). Not

surprisingly, germline mutations in MMR genes (e.g. MLH1, MSH2, MSH6 or PMS2) give

rise to HNPCC and Lynch syndrome. MMR mutations and epigenetic silencing have also

26

been associated with a significant fraction of sporadic cancers (colorectal and others)

(90, 91, 93, 97, 98).

Homologous Recombination (HR)

Despite also participating in the correction of complex lesions such as interstrand

crosslinks, the homologous recombination repair (HR) pathway (Table 1.4, Figure 1.9)

is mostly dedicated to the repair of double-strand breaks (DSBs). Such lesions arise,

directly or indirectly, upon exposure to various exogenous DNA damaging agents, either

of chemical (e.g. chemotherapeutic drugs and environmental mutagens) or physical

nature (e.g. ionizing radiation), but also upon exposure to endogenous agents such as

reactive oxygen species (ROS). They may also be generated from incomplete repair of

other DNA lesions, upon replication of single-strand breaks or during the process of

V(D)J recombination in lymphocytes (79, 99, 100). DSBs are highly deleterious lesions,

frequently implicated in the tumourigenic process, and especially difficult to repair since

no undamaged template strand is available. Among the two mechanisms that organisms

have evolved to resolve DSBs – homologous recombination (HR) and non-homologous

end-joining (NHEJ) – HR is the major and preferable one as it is considered an error-

free process. HR uses the undamaged homologous sequence of the newly synthesized

sister chromatid (after DNA replication) as a template, allowing for highly accurate DSB

repair, necessary to re-establish DNA integrity, ensure genomic stability and avoid

cancer-initiating mutations. Unfortunately, however, since a second copy of the damaged

sequence is required for DNA strand invasion and template-directed DNA repair, the

action of HR is limited to the S and G2 phases of cell cycle (79, 82, 99, 101, 102).

The HR repair of DSBs initiates with damage recognition by the ATM protein kinase and

formation of the MRE11/RAD50/ NBN (MRN) complex at the damaged site. Among other

effects (e.g. indirect contribution for BRCA1 recruitment), ATM activation allows for p53-

mediated cell cycle arrest and targeted phosphorylation of histone H2AX in the DNA

domain next to the DSB. Halting the cell cycle machinery is necessary to provide time

for repair, while histone phosphorylation is required for chromatin unfolding which, in

turn, allows the assembly of the repair factors at the damaged site. With the help of other

proteins (e.g. CtIP, EXO1 and DNA2) and thanks to its 5’–3’ exonuclease activity, the

MRN complex resects the 3’ DNA ends, creating long ssDNA overhangs on both ends

of the break. This commits cells to HR repair and allows for strand invasion into

homologous sequences. RPA1 is then recruited to protect both 3’ overhangs from

27

nuclease attack, until it is displaced by the DNA recombinase RAD51. Together and/or

with the aid of its paralogs (RAD51B, RAD51C, RAD51D, XRCC2, and XRCC3) and

several other proteins (e.g. RAD52, RAD54L, BRCA2 and PALB2), RAD51 forms a

nucleoprotein filament that invades the nearby sister chromatid to form a D-loop. Upon

identification of an homologous sequence on the intact double-stranded sister chromatid,

DNA polymerases δ, κ and ν initiate the synthesis of DNA to heal the broken ends using

the intact invaded strand as template. Finally, the Holliday-junctions formed in this way

are resolved by several protein complexes with endonuclease activity (e.g. BLM-

TOPOIII-RMI1-RMI2 complex, GEN1 endonuclease, MUS81-EME1 complex and SLX1-

SLX4 complex) and the DNA strands are re-ligated by a DNA ligase (78, 81, 82, 99, 101).

Null mutations in HR genes often result in gross chromosomal rearrangements and early

embryonic lethality, as evidenced by animal studies. In humans, inherited defects in the

NBN, ATM and MRE11 give rise to the highly cancer-prone Nijmegen breakage

syndrome, ataxia telangiectasia and an ataxia telangiectasia-like disorder, respectively.

Besides increased cancer predisposition, chromosomal instability, hypersensitivity to X-

rays and immunodeficiency are also characteristic of these syndromes. Other HR-

defective conditions such as the Werner, Bloom and Rothmund Thomson syndromes,

all of which involving RecQ-like helicases, also present with increased cancer

predisposition and chromosomal instability. Likewise, a strong increase in breast cancer

risk is observed among patients presenting inherited defects in BRCA1 and BRCA2.

Overall, these conditions highlight the important role that HR plays in the preservation of

genomic stability and cancer avoidance (78, 103, 104).

Non-Homologous End-Joining Repair (NHEJ)

DSBs may also be repaired by the NHEJ repair pathway (Table 1.4, Figure 1.9), a

mechanism that involves the direct ligation of the two DNA broken ends without any

template. Because no homology guidance is involved in the repair process, NHEJ is

often accompanied by the gain or loss of a few nucleotides and thus considered an error

prone, potentially mutagenic, repair pathway. Despite it can operate throughout most of

the cell cycle, it is during the G1 phase that its action predominates: during this cell cycle

phase, no second DNA copy is available to guide, through homology, the repair process

so the cell has to rely on the error prone NHEJ-mediated re-joining of the broken ends

to repair DSBs. Despite the risk, the threat is possibly lower than that associated with

entering the S phase or mitosis with an unrepaired DSB (78, 79, 99, 102).

28

Briefly, NHEJ is initiated by the recognition and high affinity binding of the Ku heterodimer

(composed of XRCC6 and XRCC5 proteins, also known as Ku70 and Ku80, respectively)

to the broken DNA ends. Besides approximating the ends and protecting them from

resection, this complex acts as a scaffold to recruit other NHEJ proteins such as DNA-

dependent protein kinase catalytic subunit (DNA-PKcs) whose DNA-dependent activation

results in kinase activity, autophosphorylation and phosphorylation of other NHEJ

components, thus allowing them access to the DNA ends. A synaptic complex tethering

both DNA ends is formed and stabilized with the help of XRCC4 that also reinforces the

recruitment of additional NHEJ factors. The DNA ends are then, if necessary, processed

and remodelled through removal of blocking groups and resection of the naked strands

by endonucleases and other enzymes such as DCLRE1C (also known as Artemis),

APLF, PNKP and WRN. DNA polymerases POLµ or POLλ then adjoin nucleotides to fill

the resulting gaps and LIG4, in complex with XRCC4 and NHEJ1 (also known as XLF),

re-joins the DNA ends to complete NHEJ repair (81, 82, 99-101, 105, 106).

XRCC4 and LIG4 gene knockout causes late embryonic lethality in animal models,

whereas inactivating mutations in core NHEJ proteins such as XRCC5, XRCC6 and

DNA-PKcs result in increased sensitivity to DSB-inducing agents, genomic instability,

increased cancer risk, immunological defects (because of the involvement of these

proteins in V(D)J recombination in lymphocytes), premature aging and increased neural

apoptosis. Despite more limited evidence, such effects also appear to affect humans with

mutations in genes coding for DNA-PKcs, LIG4, XRCC4 or NHEJ1 (78, 100, 105-107).

Figure 1.9. DNA damage and repair: schematic representation (adapted from (78)).

ROS, IR,

oxidizing and

alkylating agents

UV light, PAH,

cisplatin

Error-prone

polymerases

IR, cisplatin,

ROS, oxidizing

agents

IR, cisplatin,

ROS, oxidizing

agents

Oxidized,

alkylated or

deaminated

bases

Bulky adducts,

ICLs, UV

photoproducts

Replication errors DSBs, ICLs DSBs

Base Excision

Repair (BER)

Nucleotide

Excision Repair

(NER)

Mismatch Repair

(MMR)

Homologous

Recombination

(HR)

Non-Homologous

End-Joining

Repair (NHEJ)

Damaging agent

(example)

DNA lesion

(example)

Repair pathway

ROS, Reactive oxygen species; IR, Ionizing radiation; UV, Ultra-violet; PAH, Polycyclic

aromatic hidrocarbons; ICLs, Interstrand crosslinks; DSBs, Double-strand breaks.

29

Table 1.4. DNA repair pathways: a comprehensive overviewa.

Repair

pathway

Target lesions Damaging agents

(e.g.)

Mechanism (brief description) Core proteins involvedb Associated

diseases

BER Oxidized, alkylated

methylated or

deaminated bases.

ROS, oxidizing and

alkylating agents,

IR.

‘Cut-and-patch’ replacement of the

damaged nucleotide, using the

complementary strand as template.

MUTYH, NEIL1/2/3, OGG1,

APEX1, FEN1, PARP1, XRCC1,

POLB/L/D1/E, LIG1/3.

MAP,

HIGM5.

NER Bulky adducts, UV

photoproducts,

ICLs.

UV light, PAH,

cisplatin.

Similar to BER but involving

different enzymes and the removal

of a larger DNA sequence.

RAD23B, XPA/C, CETN2, DDB1/2,

ERCC1/2/3/4/5/6/8, RPA1, LIG1/3,

POLD1/K/E.

XP, CS.

MMR Replication errors. Error-prone

polymerases.

Replication error excision and

missing segment replacement.

MSH2/3/6, MLH1/3, PMS1/2,

EXO1, POLD1, LIG1.

HNPCC,

LS.

HR DSBs and ICLs. IR, cisplatin, ROS,

oxidizing agents.

Sister chromatid invasion and use

of the homologous sequence as

template (S/G2 phase).

ATM, MRE11, NBN, RPA1,

BRCA1/2, RAD51 and its paralogs,

RAD50/52/54L, POLD1, LIG1/3.

AT, NBS,

WS, BS and

RTS.

NHEJ DSBs IR, cisplatin, ROS,

oxidizing agents.

Direct ligation of the two DNA

broken ends, without any template.

XRCC4/5/6, PRKDC, NHEJ1,

DCLRE1C, POLM/L, LIG4.

LIG4

syndrome.

aThe information included in the table is, by no means, exhaustive. The complete picture is far more complex with the different DNA repair

pathways cooperating in the repair of different types of lesions, cross talking with other DNA damage response pathways and participating in

other physiological processes. bCore proteins involved identified by their coding gene official name (HUGO gene nomenclature committee,

https://www.genenames.org/). BER, Base excision repair; NER, Nucleotide excision repair; MMR, Mismatch repair; HR, Homologous

recombination repair; NHEJ, non-homologous end-joining repair; UV, Ultraviolet; ICLs, interstrand crosslinks; DSBs, Double-strand breaks; ROS,

reactive oxygen species; IR, ionizing radiation; PAH, polycyclic aromatic hydrocarbons; MAP, MUTYH-associated polyposis; HIGM5, Hyper-IgM

Syndrome Type 5; XP, Xeroderma pigmentosum; CS, Cockayne syndrome; HNPCC, Hereditary nonpolyposis colorectal cancer; LS, Lynch

syndrome; AT, Ataxia telangiectasia; NBS, Nijmegen breakage syndrome; WS, Werner syndrome; BS, Bloom syndrome; RTS, Rothmund

Thomson syndrome.

https://www.genenames.org/

30

The impact of DNA repair gene variation in the context of thyroid cancer

Genetic diversity and its clinical implications

The completion of the Human Genome Project in 2001 (108, 109) was a major

achievement, a breakthrough hallmark of modern biomedical sciences that paved the

way to a plethora of new research directions of potential clinical utility for the 21st century.

Among other important developments and applications, it allowed the mapping and initial

characterization of genetic variation, its frequency, geographic distribution and relation

with human health and disease, thus creating the basis for personalized medicine.

According to the map published in 2001 by the International SNP Map Working Group

(110), over 1.4 million SNPs exist throughout the genome. This number has been

repeatedly updated as new and more complete variation maps have been published,

including the one by the 1000 Genomes Project which includes over 84.7 million SNPs

(111). Irrespectively, SNPs, defined as substitutions of one nucleotide that occur in >1%

of a sampled population (112), are by far the most frequent form of genetic variation in

humans, well above other types of variation such as base insertion/deletion, copy

number variations and structural variants (e.g. chromosomal rearrangements) (110-112).

SNPs can virtually occur in any part of the genome, from large intergenic regions to

coding gene exonic and intronic sequences and their corresponding 3’ downstream and

5’ upstream untranslated regions (UTR). SNPs may therefore interfere with critical

processes such as recognition and binding of transcription factors to promoter regions,

epigenetic transcription regulation, splicing of pre-mRNA transcripts and, importantly,

they may alter the amino acid sequence of the protein through introduction of premature

stop codons (nonsense substitutions) or point substitutions (missense substitutions).

Both the expression and the structure of the final protein may thus be altered, with

potential impact on protein activity. The same applies to untranslated transcripts with

important functional significance such as miRNAs or lncRNAs (112-114).

Despite functional studies are still lacking for the majority of SNPs, a significant impact

on expression or activity levels has been demonstrated for multiple SNPs (115-122),

providing proof-of-concept and a solid rationale for the putative association of SNPs with

susceptibility to human disease and sensitivity to therapeutic drugs and toxic chemicals.

Much effort has been put into the validation and clarification of such genotype-phenotype

associations (114, 123-128) and, despite doubts subside in many cases, it is now clear

from many studies (CGAS and, more recently, GWAS) that such associations do exist.

31

DNA repair SNPs and thyroid cancer susceptibility

Because of their critical role in the correction of DNA lesions, damage response and

maintenance of genomic stability, DNA repair SNPs have been widely investigated in

relation to cancer susceptibility (121, 129-137) and sensitivity to DNA damaging agents,

either of therapeutic use (mainly chemo (137-146) and radiotherapeutic agents (146-

156)) or of environmental or occupational exposure (120, 157-159).

In the context of TC, more than 30 original CGASs and at least 5 meta-analysis focusing

on DNA repair SNPs as susceptibility biomarkers have been published so far. The main

results of these studies, i.e., SNPs presenting significant findings replicated through at

least one independent study, are depicted in Table 1.5. According to these studies,

XRCC3 rs861539 appears to be consistently associated with TC or DTC susceptibility:

increased risk has been repeatedly associated with the variant genotype in several

independent studies across different populations (160-166) and such association was

confirmed by the only meta-analysis performed to date (167). XRCC1 SNPs (rs25487,

rs1799782, rs25489) have also been frequently associated with TC or DTC susceptibility,

despite results are somehow less consistent: rs25487 appears to exert a protective effect

(164, 168, 169), also evident from meta-analysis (48, 170-172) in Caucasian and mixed

ethnicity populations, while rs1799782 and rs25489, despite mostly associated with

increased risk (164, 165, 169, 170, 172-174), present conflicting results (171, 175, 176).

ATM rs1801516 (58, 62, 168), BRCA1 rs16941 (177, 178) and PRKDC rs7830743 (48,

179, 180) have also been associated with TC or DTC susceptibility in independent

studies. Moreover, ATM (62, 168), BRCA1 (177), XRCC3 ((48, 166) and other DNA

repair SNPs (NEIL3 (181), OGG1 (182), PARP (182, 183), RAD52 (180), RPA1 (181),

XRCC5 (182), ERCC5 (182), MLH1 (184), PMS2 (182), PCNA (182), MGMT (182) (185,

186), HUS1 (48, 185, 186) and ALKBH3 (186)), have also been associated with TC or,

more specifically, DTC susceptibility but the associations have not yet been replicated.

The vast number of studies investigating the association between DNA repair SNPs and

TC susceptibility is not paralleled, however, by studies focusing on therapeutic response:

to our knowledge, the potential impact of DNA repair SNPs on the response of DTC

patients to radioiodine therapy has not been investigated so far. Nevertheless,

considering the demonstrated impact of some of these SNPs on in vitro IR sensitivity

(115-121, 187), on response to radiotherapy (147-156, 188, 189) and on the effects of

IR upon in vivo occupational or environmental exposure (120, 157-159, 190, 191), the

existence of such association is, at the very least, plausible.

32

Table 1.5. DNA repair SNPs associated with susceptibility to TC – a literature review.

Gene SNP Association (OR [95%CI],

p-value)a

Country

Sample

sizeh

Ref.


XRCC1 rs1799782

(Arg194Trp)

1.85 [1.11-3.07], 0.018b Taiwan 283/469i (173)

10.40 [1.00-105.50], 0.048b USA 251/503i (169)

0.55 [0.31-0.98], 0.044c Korea 111/100j (175)

1.53 [1.10-2.12], <0.05d China 276/552k (165)

2.33 [1.36-3.96], 0.0018b China 276/403i (164)

0.55 [0.38-0.81], 0.002d Pakistan 456/400k (176)

XRCC1 rs25487

(Arg399Gln)

0.70 [0.59-0.93], 0.03d Rus/Blrus 255/595j (168)

0.70 [0.50-1.00], 0.049d USA 251/503i (169)

0.69 [0.50-0.93], 0.0191d China 276/403i (164)

XRCC1

rs25489

(Arg280His)

1.58 [1.05-2.40], 0.027d Spain 398/473i (174)

0.53 [0.39-0.72], 0.0001d Pakistan 456/400k (176)


ATM rs1801516

(Asp1853Asn)

0.69 [0.45-0.86], 0.03e Rus/Blrus 254/596j (168)

0.34 [0.16-0.73], 0.0017f Belarus 70/250j (62)

3.13 [1.17-8.31], 0.02c Polynesia 175/270i (58)

BRCA1 rs16941

(Glu1038Gly)

0.71 [0.52-0.98], <0.05c USA 303/511i (177)

1.16 [1.04-1.28], 0.005e Poland 1635/2021j (178)

XRCC3 rs861539

(Thr241Met)

2.10 [1.30-3.40], 0.004d USA 134/161i (162)

2.00 [1.10-3.60], 0.026g Portugal 109/214k (160)

1.58 [1.03-2.42], 0.05d Iran 161/182i (161)

1.65 [1.24-2.19], 0.001e China 183/367j (163)

1.36 [1.01-1.85], <0.05d China 276/552k (165)

1.60 [1.17-2.18], 0.0033d China 276/403i (164)

1.40 [1.12-1.75], 0.003e Pakistan 456/400k (166)

Non-Homologous End-Joining (NHEJ)

PRKDC rs7830743

(Ile3434Thr)

4.97 [1.06-23.44], p<0.05b S. Arabia 39/229j,l (180)

2.32 [1.49-3.61], 0.0002d Iran 173/204i (179)

aOnly significant findings with independent replication are shown. When multiple

associations are reported for a SNP, only the most relevant is presented; bhomozygous

variant genotype, codominant model; cheterozygous genotype, codominant model;

dheterozygous or homozygous variant genotype, dominant model; evariant allele, per

33

allele model; fvariant allele, log-additive model; ghomozygous variant genotype,

recessive model; hcases/controls; iDTC; jPTC; kTC; lassociation observed in the

screening phase but not confirmed in the verification phase. TC, Thyroid cancer; SNP,

single nucleotide polymorphism; OR, odds ratio; CI, confidence interval; Rus/Blrus,

Russia/Belarus.

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polymorphisms and haplotypes in hMLH1 and hMSH3 gene with the risk of papillary

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B, et al. Common genetic variants related to genomic integrity and risk of papillary thyroid

cancer. Carcinogenesis. 2011;32(8):1231-7.

187. Toprani SM, Das B. Radio-adaptive response, individual radio-sensitivity and

correlation of base excision repair gene polymorphism (hOGG1, APE1, XRCC1, and

49

LIGASE1) in human peripheral blood mononuclear cells exposed to gamma radiation.

Environmental and molecular mutagenesis. 2020;61(5):551-9.

188. Boige V, Mollevi C, Gourgou S, Azria D, Seitz J-F, Vincent M, et al. Impact of

single-nucleotide polymorphisms in DNA repair pathway genes on response to

chemoradiotherapy in rectal cancer patients: Results from ACCORD-12/PRODIGE-2

phase III trial. International journal of cancer. 2019;145(11):3163-72.

189. Bodei L, Schöder H, Baum RP, Herrmann K, Strosberg J, Caplin M, et al.

Molecular profiling of neuroendocrine tumours to predict response and toxicity to peptide

receptor radionuclide therapy. The Lancet Oncology. 2020;21(9):e431-e43.

190. Djansugurova L, Altynova N, Cherednichenko O, Khussainova E, Dubrova YE.

The effects of DNA repair polymorphisms on chromosome aberrations in the population

of Kazakhstan. International journal of radiation biology. 2020;96(5):614-21.

191. Soliman AHM, Zaki NN, Fathy HM, Mohamed AA, Ezzat MA, Rayan A. Genetic

polymorphisms in XRCC1, OGG1, and XRCC3 DNA repair genes and DNA damage in

radiotherapy workers. Environmental Science and Pollution Research.

2020;27(35):43786-99.

50

Chapter II

Objectives

52

53

Chapter II – Objectives

Considering 1) the high heritability of DTC, yet not fully explained despite numerous

efforts (GWAS and CCAS) (1, 2), 2) the important contribution of exposure to DNA

damaging agents such as IR to DTC aetiology (3-5), 3) the critical role of DNA repair

processes in the preservation of genomic stability and cancer avoidance (6-8) and 4)

the impact that genetic variation, namely SNPs, may have on DNA repair capacity (9-

13) and, hence, on cancer susceptibility (14-17) and sensitivity to DNA damaging

agents (13, 17-24), it is possible that DNA repair SNPs may contribute to DTC

susceptibility. Prior studies support this hypothesis but evidence is yet scarce and

relevant associations may remain to be identified.

Moreover, further considering that 131I-based RAI therapy remains the mainstay of DTC

management (25, 26), that the ability of 131I to induce thyroid cell death relies on the

local emission of DNA-damaging IR (hence, radiation cytotoxicity) (27, 28) and that 131I,

despite preferentially accumulating in the thyroid gland, may also be taken up by other

tissues (29), it is also possible that DNA repair SNPs may interfere with the extent of

DNA damage induced by 131I in peripheral lymphocytes from DTC patients submitted to

131I-based RAI therapy. To our knowledge, no prior study has explored such

hypothesis. Nevertheless, it is supported by existing evidence demonstrating that DNA

damage levels in peripheral lymphocytes increase upon therapeutic exposure to 131I

(30-32) and that functional DNA repair SNPs, through interference with DNA repair

capacity, may influence the extent of DNA damage upon IR exposure (IR sensitivity)

(11, 12, 19, 33-35).

Therefore, this work aims 1) to evaluate, through a hospital-based case-control study in

a Caucasian Portuguese population, the potential modifying role of a panel of DNA

repair SNPs (e.g. BER, NER, MMR pathways) on the individual susceptibility to non-

familial DTC and 2) to correlate individual DNA repair SNPs with the micronuclei (MN)

frequency (a marker of DNA damage) in peripheral blood lymphocytes from non-

familial DTC patients submitted to 131I-based RAI therapy (Figure 2.1).

The definition and characterization of genetic susceptibility biomarkers for DTC is

desirable as it will allow the identification of individuals who are at increased risk for

DTC and, eventually, the optimization of cancer prevention policies. Likewise,

understanding the potential modulating effect that DNA repair SNPs may have on 131I-

induced DNA damage will allow the identification of potential radiogenomic markers of

131I-sensitivity with clinical significance: such genetic markers may influence the

54

individual response to 131I-based RAI therapy, impact its risk-benefit ratio and thus

affect therapy outcome in individual DTC patients. Their identification and validation

through subsequent clinical pharmacogenomic studies is therefore highly desirable so

that a more personalized approach to DTC treatment may be developed.

Figure 2.1. Study hypotheses.

β-emitting131I (RAI

therapy)

IR and other

DNA

damaging

agents

DNA repair SNPs

activity or expression of

DNA repair enzymes

DNA repair capacity

sensitivity to DNA

damaging agents

DTC susceptibility?

131I-induced DNA damage

upon RAI therapy

RAI therapy efficacy? RAI therapy safety?

IR, Ionizing radiation; DNA, Deoxyribonucleic acid; SNPs, Single nucleotide

polymorphisms; RAI, Radioactive iodine; DTC, Well-differentiated thyroid cancer.

References




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12. Gdowicz-Klosok A, Widel M, Rzeszowska-Wolny J. The influence of XPD,

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rays. Mutation research. 2013;755(1):42-8.

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17. Al-Shaheri FN, Al-Shami KM, Gamal EH, Mahasneh AA, Ayoub NM.

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acid substitution variants of APE1 and XRCC1 genes associated with ionizing radiation


21. Xiong Y, Huang B-Y, Yin J-Y. Pharmacogenomics of platinum-based

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23. Borchiellini D, Etienne-Grimaldi M-C, Thariat J, Milano G. The impact of

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Predictive factors of cytotoxic damage in radioactive iodine treatment of differentiated

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34. Djansugurova L, Altynova N, Cherednichenko O, Khussainova E, Dubrova YE.

The effects of DNA repair polymorphisms on chromosome aberrations in the population

of Kazakhstan. International journal of radiation biology. 2020;96(5):614-21.

35. Soliman AHM, Zaki NN, Fathy HM, Mohamed AA, Ezzat MA, Rayan A. Genetic

polymorphisms in XRCC1, OGG1, and XRCC3 DNA repair genes and DNA damage in

radiotherapy workers. Environmental Science and Pollution Research.

2020;27(35):43786-99.

58

Chapter III

Polymorphisms in base excision repair genes and thyroid cancer risk

[Research Paper]

The content of this chapter was published in the following research paper:

Santos LS, Branco SC, Silva SN, Azevedo AP, Gil OM, Manita I, Ferreira TC,

Limbert E, Rueff J and Gaspar JF (2012). Polymorphisms in base excision repair

genes and thyroid cancer risk. Oncol Rep. 28(5): 1859-68. (DOI:

10.3892/or.2012.1975)

This is an original research article and it is presented for the first time in a thesis.

Santos LS was a main contributor, through participation in the execution and validation

of the methodologies, data analysis, draft manuscript preparation and final editing.

60

61

Chapter III - Polymorphisms in base excision repair genes and thyroid cancer

risk

Abstract

Thyroid cancer (TC) is the most frequent endocrine malignancy, accounting however

for only 1-2% of all human cancers, and the best-established risk factor for TC is

radiation exposure, particularly during childhood. Since the BER pathway seems to

play an important role in the repair of DNA damage induced by IR and other

genotoxicants, we carried out a hospital-based case-control study in order to evaluate

the potential modifying role of 6 BER polymorphisms on the individual susceptibility to

non-familial TC in 109 TC patients receiving iodine-131, and 217 controls matched for

age (±2 years), gender and ethnicity. Our results do not reveal a significant

involvement of XRCC1 Arg194Trp and Arg399Gln, OGG1 Ser326Cys, APEX1

Asp148Glu, MUTYH Gln335His and PARP1 Val762Ala polymorphisms on the

individual susceptibility towards TC, mostly in agreement with the limited available

evidence. By histological stratification analysis, we observed that the association

between the presence of heterozygozity in the MUTYH Gln335His polymorphism and

TC risk almost reached significance for the papillary subtype of TC. This was the first

time that the putative association between this polymorphism and TC susceptibility was

evaluated. However, since the sample size was modest, the possibility of a type I error

should not be excluded and this result should, therefore, be interpreted with caution.

More in-depth studies involving larger populations should be pursued in order to further

clarify the potential usefulness of the MUTYH Gln335His genotype as a predictive

biomarker of susceptibility to TC and the role of the remaining BER polymorphisms on

TC susceptibility.

Key words: SNPs polymorphisms, DNA base excision repair, thyroid cancer, cancer

susceptibility

Introduction

Thyroid cancer (TC) is the most frequent endocrine malignancy, accounting however

for only 1-2% of all human cancers. In contrast with most malignancies, increasing

incidence rates have been consistently reported worldwide over recent decades,

although mortality due to TC does not seem to follow this trend (1). TC arises mostly

from the epithelial elements of the gland and is usually classified according to

62

histological and clinical criteria (1). Papillary and follicular thyroid carcinomas are the

most common histological varieties, with papillary TC representing about 85% of all

cases. TC is unusual during childhood but incidence increases with age. Also, women

are afflicted three times as often as men, particularly during reproductive years (1).

Overall prognosis is generally good, except for undifferentiated (anaplastic)

carcinomas, which account for <5% of TC cases (1).

TC aetiology remains an obscure subject: inherited familial factors such as germline

mutations seem to be responsible for only a minor percentage of TC cases (2, 3).

Hormonal and dietary factors (e.g. iodine intake) have also been suggested to be

implicated in the aetiology of the disease but evidence is limited and inconsistent or, in

the best of cases, limited to specific subtypes of TC (1, 2). Clearly, the best-established

risk factor for TC is radiation exposure, particularly during childhood: risk of TC is

increased after exposure to ionizing radiation (IR) doses as low as 0.1 Gy and is both

dose- and age- dependent, being maximal about 20-30 years after exposure (1, 2).

This long latency period between radiation exposure and TC diagnosis is expected

since IR induces mostly recessive mutations, therefore, requiring a second event for

tumour initiation (4). Even so, radiation exposure is estimated to account for <10% of

all TC, suggesting that other risk factors could also have a relevant impact in the

aetiology of this malignancy.

Since TC risk and frequency is significantly higher in relatives (particularly first-degree)

of TC patients compared to the general population (2, 3, 5), it is possible that high-

prevalence, low-penetrance genetic variations could also constitute predisposing

factors for TC, especially when considered together with exposure to environmental

risk factors such as IR. Germ-line DNA polymorphisms in genes involved in regulation

of apoptosis and control of the cell cycle (e.g. TP53), in kinase-dependent signalling

pathways (e.g. RET), in endobiotic or xenobiotic metabolism (e.g. GST and CYP

superfamilies), in hormonal and iodine metabolism (e.g. TG) and in DNA repair (among

others) have been associated with interindividual differences in TC risk (reviewed in

refs. (3, 5)). Also, in the first genome-wide association study ever performed on TC,

two polymorphisms located near the FOXE1 (TTF-2) and NKX2-1 (TTF-1) genes

(which encode for thyroid-specific transcription factors) were identified as strong

genetic risk markers of sporadic papillary TC in European populations (6).

IR is considered mutagenic since it can cause damage to DNA either directly,

introducing single and double-strand breaks (DSB) to the DNA helix, or indirectly,

promoting the radiolysis of water to yield radicalar DNA-reactive species that cause

63

oxidative base damage (4). Such DNA lesions can activate specific checkpoints,

triggering cell cycle arrest, in order to allow for DNA damage repair or, ultimately,

inducing apoptotic cell death. Cell replication in the presence of genetic errors can

cause irreversible mutations, leading to malignant transformation (7). In line with this,

significant increase in DNA damage was found in patients with TC (8), suggesting that

DNA repair mechanisms are important in correcting DNA damage and that defective

DNA repair capacity might contribute to the risk of TC.

Base excision repair (BER) and DSB repair pathways are especially important in re-

establishing DNA integrity after irradiation (7, 9). The latter can be accomplished

through homologous recombination, in which the double helix of the homologous,

undamaged partner DNA molecule is used as a model, or through non-homologous

end-joining repair, which involves direct ligation of the two double-strand-break ends (7,

9). The BER pathway, in turn, is the main pathway responsible for recognizing,

excising, and repairing small chemical alterations of a single base (e.g. oxidative DNA

damage) caused by free radicals formed endogenously or after exposure to exogenous

agents such as IR (7, 9, 10). Briefly, BER is a multistep process involving several

proteins, such as 8-oxoguanine DNA glycosylase (OGG1), APEX nuclease

(multifunctional DNA repair enzyme) 1 (APEX1), X-ray repair complementing defective

repair in Chinese hamster cells 1 (XRCC1) or poly (ADP-ribose) polymerase (PARP1),

that act via a number of coordinated sequential ‘cut-and-patch’-type reactions to detect

the lesion, remove the single damaged base, and fill in the resulting single-stranded

gap using the intact complementary strand as template (7, 9-11).

As such, DNA repair polymorphisms that modulate the DNA repair capacity may

contribute to individual susceptibility to DNA damaging agents and, hence, modify

cancer risk. In fact, polymorphic variants in virtually all DNA repair pathways have been

associated with susceptibility for several types of cancer (7), including TC: regarding

the latter, for example, polymorphisms in DNA repair genes such as ERCC2 (12) (NER

pathway), Ku80 (13) (NHEJ pathway), XRCC3 (14), BRCA1 (15) and possibly RAD51

(14) (HR pathway) have been associated with TC risk (reviewed in refs. (3, 5, 9, 16)).

Considering the BER pathway, in particular, several of the genetic variants identified in

the XRCC1, OGG1, MUTYH, APEX1 and PARP1 genes have been reported to be

associated with individual susceptibility to a variety of cancers, including breast, lung,

colorectal and skin cancers (7, 10, 11). Some of these polymorphisms also seem to

affect IR sensitivity (17, 18). However, only a very limited number of studies have been

published focusing on a possible role of BER pathway SNPs on TC susceptibility,

64

mostly with negative or inconclusive results, except for XRCC1 polymorphisms

(reviewed in refs. (3, 9, 16)).

Since the BER pathway seems to play an important role in the repair of DNA damage

induced by IR (the most well-known risk factor for TC) and other genotoxicants, we

carried out an hospital-based case-control study in a Caucasian Portuguese population

in order to evaluate the potential modifying role of 6 BER polymorphisms on the

individual susceptibility to non-familial TC.

Materials and methods

Study subjects

One hundred and nine TC patients receiving iodine-131 treatment at the Department of

Nuclear Medicine of the Portuguese Oncology Institute of Lisbon were recruited. None

of the patients enrolled in this study presented familiar history of TC. The TC diagnosis

was confirmed histologically. For each case (except for one), two controls were

recruited at São Francisco Xavier Hospital (Department of Laboratory Medicine),

matched for age (±2 years), gender and ethnicity. Inclusion criteria for the control group

included absence of cancer or thyroid disease and no familiar history of thyroid

pathology. All study subjects were Caucasian, Portuguese, with Portuguese

ascendants and no previous history of oncologic disease.

The anonymity of the patients and control population was guaranteed. Both patient and

control participants groups were submitted to a questionnaire, performed by trained

interviewers, in order to collect information on demographic characteristics, family

history of cancer, lifestyle habits (smoking and alcohol drinking) and exposure to IR. In

respect to smoking habits, former smokers were considered as non-smokers if they

gave up smoking either 2 years before TC diagnosis or 2 years before the inclusion

date as control.

For all eligible participants, written informed consent was obtained prior to blood

withdrawal. The response rate was > 95% for cases and controls. This study was

approved by the ethics board of the involved institutions.

DNA extraction

Peripheral blood samples from all study participants were collected into 10 ml

heparinized tubes and kept thereafter at -80˚C. Genomic DNA was extracted from 250

μl of each blood sample using a commercially available kit (QIAamp® DNA mini kit;

65

Qiagen), according to the manufacturer's instructions. All DNA samples were stored at

-20˚C until further analysis.

Single nucleotide polymorphisms (SNP’s) selection

Publicly available on-line databases such as NCBI (http://www.ncbi.nlm.nih.gov/snp/),

GeneCards (http://www.genecards.org) and SNP500Cancer

(http://variantgps.nci.nih.gov/cgfseq/pages/snp500.do) were used to search for SNPs

reported to date on genes coding for DNA repair proteins of the BER pathway. Eligible

SNPs had to be located in a coding region, give rise to an amino acid change (non-

synonymous) and exhibit a minor allele frequency > 0.1 in Caucasian populations.

According to these criteria, 6 common nsSNPs were selected for genotyping:

Arg194Trp [reference SNP no. (rs) 1799782] and Arg399Gln (rs25487) for XRCC1;

Ser326Cys (rs1052133) for OGG1; Asp148Glu (rs1130409) for APEX1; Gln335His

(rs3219489) for MUTYH and Val762Ala (rs1136410) for PARP1 (Table 3.1).

Table 3.1. Selected SNPs and detailed information on the corresponding base and

amino acid exchanges as well as minor allele frequency.

Gene Region Codon Base (amino acid)

exchange

Minor allele frequency,

MAF (%)a

XRCC1 Exon 6 194 C ➝ T (Arg ➝ Trp) 13.1

Exon 10 399 G ➝ A (Arg ➝ Gln) 26.6

OGG1 Exon 6 326 C ➝ G (Ser ➝ Cys) 29.9

APEX1 Exon 5 148 T ➝ G (Asp ➝ Glu) 44.0

MUTYH Exon 12 335 G ➝ C (Gln ➝ His) 31.9

PARP1 Exon 17 762 T ➝ C (Val ➝ Ala) 24.4

aAccording to http://www.ncbi.nlm.nih.gov/projects/SNP/.

Genotyping

PCR-RFLP – XRCC1 Arg194Trp, XRCC1 Arg399Gln and OGG1 Ser326Cys

polymorphisms were genotyped by polymerase chain reaction (PCR) followed by

restriction fragment length polymorphism (RFLP). Primer design and PCR conditions

were optimized in order to achieve the best possible results: OligoAnalyzer 3.1

(http://eu.idtdna.com/analyzer/Applications/OligoAnalyzer/) was used to determine

melting temperatures, GC contents, hairpins, and dimmer formation. Basic local

alignment search tool (BLAST) resource (http://blast.ncbi.nlm.nih.gov/Blast.cgi) was

http://www.ncbi.nlm.nih.gov/projects/SNP/

66

used to confirm low similarity with other human sequences. All PCR reactions were

performed in a 50 μl final volume, comprising 3 μl genomic DNA, 1X ImmoBuffer, 2.5

mM MgCl2, 0.8 mM of each dNTP (Bioline), 0.6 μM of each primer (Stabvida), 0.909 μl

DMSO and 0.75 U of Immolase (Bioline). Amplification was accomplished in a

GeneAmp® PCR system 2700 thermal cycler (Applied Biosystems): the initial enzyme

activation step (95˚C, 7 min) was ensued by a variable number of amplification cycles

consisting of denaturation (94˚C, 30 sec), annealing (variable temperature, 30 sec) and

extension (72˚C, 30 sec); amplification was concluded with a final extension step at

72˚C for 10 min. Primer sequences, annealing temperatures, number of amplification

cycles (PCR conditions) and PCR product size (bp) specific for both XRCC1

polymorphisms have been described elsewhere (19). Specific primer sequences

(forward: 5'-ggt ggc cct aaa gga ctc tcc-3'; reverse: 5'-cca tcc tta gcg ctg tct ccc-3') and

PCR conditions (35 PCR cycles, with an annealing temperature of 64˚C) were used for

the determination of OGG1 Ser326Cys genotype, yielding a 456 bp PCR product.

After amplification, 10 μl of each PCR product were incubated with 5 units of an

appropriate restriction enzyme and 1.25 μl of the 10X buffer recommended by the

enzyme manufacturer, to a final volume of 12.5 μl. The choice of the restriction enzyme

and reaction conditions were optimized as follows: to genotype the XRCC1 Arg194Trp

polymorphism, the previously amplified fragment was digested with MspI (Fermentas)

for 2 h at 37˚C. The exact same conditions were applied to the restriction analysis of

the XRCC1 Arg399Gln polymorphism while for the OGG1 Ser326Cys polymorphism

the digestion was performed overnight at 37˚C with the SatI restriction enzyme

(Fermentas).

After restriction enzyme inactivation (20 min at 65˚C), the resulting digested fragments

were electrophoresed in an ethidium bromide-stained 4% agarose gel and visualized

under ultraviolet light. HyperLadder V (Bioline) was used as molecular marker. The

expected digestion pattern for each genotype of the XRCC1 Arg194Trp and XRCC1

Arg399Gln polymorphisms has been previously described (19). For the OGG1

Ser326Cys polymorphism, fragment length after SatI digestion was 456 bp for the C/C

genotype, 456, 258, 198 bp for the C/G genotype and 258, 198 bp for the G/G

genotype.

All the genotype determinations were carried out twice in independent experiments and

inconclusive samples were re-analysed.

Real-time PCR – APEX1 Asp148Glu, MUTYH Gln335His and PARP1 Val762Ala

polymorphisms were genotyped by real-time PCR, using the TaqMan fluorogenic 5'

67

nuclease assay (Applied Biosystems). In order to assure uniformity in genomic DNA

content (2.5 ng.μl-1) in all samples analysed through this method, DNA was pre-

quantified by fluorimetry with the Quant-iT™ PicoGreen® dsDNA Assay kit (Invitrogen)

and a Zenyth 3100 plate reader (Anthos Labtech Instruments), according to the

manufacturer's instructions.

Amplification was carried out in a 7300 Real-Time PCR System thermal cycler (Applied

Biosystems), with 96-well microplates containing 10 ng of genomic DNA, 1X SNP

genotyping assay mix (APEX1 assay ID: C___8921503_10; MUTYH assay ID:

C__27504565_10; PARP1 assay ID: C___1515368_1_) and 1X TaqMan Universal

PCR Master mix per well (final volume, 10 μl/well). Initial enzyme activation (10 min, at

95˚C) was ensued by 40 cycles of denaturation (15 sec at 92˚C) and probe

annealing/extension (1 min at 60˚C). Allelic discrimination was then performed by

measuring fluorescence emitted by both VIC and FAM dyes in each well (60 sec) and

computing the results into the System SDS software version 1.3.1. All reactions were

performed twice in independent experiments and repeated for all inconclusive samples.

Statistical analysis

Exact probability tests available in Mendel software (V5.7.2) were used to analyse the

Hardy-Weinberg frequencies for XRCC1, OGG1, APEX1, MUTYH and PARP1 alleles

in patient and control populations, considered separately (20).

The differences in genotype frequency and smoking status between patient and control

populations were evaluated by the Chi-square test. The normality of continuous

variables, such as age, and the homogeneity of variances were analysed with

Kolmogorov-Smirnov and Levene tests, respectively. The Student's t-test was used in

the statistical analysis of the homogeneity of age distribution between patient and

control populations, while the Chi-square test was applied to the analysis of the

homogeneity of gender distribution.

When assessing the genetic effects, logistic regression analysis was performed to

determine the crude and adjusted odds ratio (OR) and the corresponding 95%

confidence intervals (CI). Adjusted OR calculations took into account gender, age at

diagnosis (≤30, 31-49, 50-69 and ≥70 years) and smoking habits (smokers/non-

smokers), with female gender, lower age group and non-smokers being considered as

the reference groups for each of these variables. For the purpose of these calculations,

age at diagnosis for controls was the age at enrolment.

68

All analyses were performed using the Statistical Package for the Social Sciences for

Windows 15.0 version (SPSS, Inc., Chicago IL, USA).

Results

This study comprised 109 TC patients and 217 age- and gender-matched controls.

According to histological criteria, 71% TC cases were classified as papillary TC (78

patients), 26% as follicular TC (28 patients) and 3% as poorly differentiated TC (3

patients). Previous exposure to IR sources, with the exception for diagnostic medical X-

rays, was denied by all cases.

The baseline characteristics (gender, age and smoking habits) of both case and control

populations are listed in Table 3.2. The case group included 17 male and 92 female

patients, with an overall mean age of 53 years. In agreement with the gender

distribution usually observed in this type of cancer, the frequency of females in the

case group was significantly higher than the frequency of males. No significant

difference was found between the case and control groups concerning age distribution

(p = 0.997), gender (p = 0.839) or smoking habits (p = 0.117).

Table 3.2. General characteristics for the TC cases (n = 109) and control population (n

= 217).

Characteristics Cases, n (%) Controls, n (%) p-valuec,d

Gender

Female 92 (84.4) 185 (85.3) 0.839

Male 17 (15.6) 32 (14.7)

Agea,b

≤30 4 (3.7) 9 (4.1) 0.997

31-49 39 (35.8) 77 (35.5)

50-69 52 (47.7) 104 (47.9)

≥70 14 (12.8) 27 (12.4)

Smoking habits

Non-smoker 97 (89) 177 (82.3) 0.117

Smoker 12 (11) 38 (17.7)

Missing 0 2 (0.6)

aAge at diagnosis for cases. bAge at enrollment for each of the case-matched controls.

cSee Materials and methods; dcases vs. control group.

69

The genotype frequencies of the 6 polymorphisms, in both TC cases and controls, are

shown in Table 3.3. The frequency of minor allele homozygotes for the OGG1

Ser326Cys and PARP1 Val762Ala polymorphisms was null both in case and control

study groups. The same was observed for the XRCC1 Arg194Trp polymorphism in the

control group. The genotypic frequencies of the XRCC1 Arg399Gln, APEX1 Asp148Glu

and PARP1 Val762Ala polymorphisms in control and cancer groups were in agreement

with the expectations of the Hardy-Weinberg law (p > 0.1, exact probability test). The

same was not observed, however, for the OGG1 Ser326Cys and MUTYH Gln335His

polymorphisms in the control group nor for the XRCC1 Arg194Trp polymorphism in the

cancer group.

Table 3.3. Genotype frequencies for each of the selected BER polymorphisms in TC

case and control populations.

Genotype frequency

Polymorphism

Refe-

rence

forma

n

Reference

homozygote,

n (%)

Heterozygote,

n (%)

Variant

homozygote,

n (%)

p-

valueb

XRCC1 (Arg194Trp)

Control group Arg 217 196 (90.3) 21 (9.7) 0 (0.0) 0.109

Case group 108 98 (90.7) 8 7.4) 2 (1.9)

XRCC1 (Arg399Gln)

Control group Arg 217 87 (40.1) 105 (48.4) 25 (11.5) 0.911

Case group 109 46 (42.2) 50 (45.9) 13 (11.9)

OGG1 (Ser326Cys)

Control group Ser 217 139 (64.1) 78 (35.9) 0 (0.0) 0.335

Case group 108 75 (69.4) 33 (30.6) 0 (0.0)

APEX1 (Asp148Glu)

Control group Asp 217 56 (25.8) 103 (47.5) 58 (26.7) 0.810

Case group 109 31 (28.4) 52 (47.7) 26 (23.9)

MUTYH (Gln335His)

Control group His 216 106 (49.1) 102 (47.2) 8 (3.7) 0.195

Case group 109 64 (58.7) 40 (36.7) 5 (4.6)

PARP1 (Val762Ala)

Control group Val 216 168 (77.8) 48 (22.2) 0 (0.0) 0.270

Case group 108 78 (72.2) 30 (27.8) 0 (0.0)

70

aReference form was defined as the residue corresponding to the most frequent

genotype in the TC case population. bChi-square test for distribution of genotypic

frequencies.

The genotypic frequencies that were observed in the control group for the XRCC1

Arg194Trp and XRCC1 Arg399Gln polymorphisms are similar to those previously

reported by Kiuru et al (21) for a Caucasian Northern European population. The

genotypic frequencies of the OGG1 Ser326Cys, APEX1 Asp148Glu and PARP1

Val762Ala polymorphisms are also in agreement with those reported in a larger study

(n > 1000) carried out in a Caucasian American population (22). As for the MUTYH

Gln335His polymorphism, the genotypic frequencies reported are in agreement with

those reported by Conde et al (23), for a similar Caucasian Portuguese population

(Table 3.4).

Table 3.4. Comparison of genotypic frequencies observed in the control group of this

study with those previously published in the literature for Caucasian populations.

SNP Genotype frequency Population

Arg/Arg, n (%) Trp/Arg, n (%) Trp/Trp, n (%)

XRCC1

(Arg194Trp)

196 (90.3) 21 (9.7) 0 (0.0) Caucasian Portuguese

(study data)

1377 (88.5) 177 (11.4) 2 (0.1) Caucasian Northern

European (n=1556) (21)

Arg/Arg, n (%) Arg/Gln, n (%) Gln/Gln, n (%)

XRCC1

(Arg399Gln)


(study data)

645 (41.6) 728 (47.0) 176 (11.4) Caucasian Northern

European (n=1549) (21)

Ser/Ser, n (%) Ser/Cys, n (%) Cys/Cys, n (%)

OGG1

(Ser326Cys)


(study data)

760 (61.1) 424 (34.1) 60 (4.8) Caucasian American

(n=1244) (22)

Asp/Asp, n (%) Asp/ Glu, n (%) Glu/Glu, n (%)

APEX1 56 (25.8) 103 (47.5) 58 (26.7) Caucasian Portuguese

71

(Asp148Glu) (study data)


(n=1207) (22)

Gln/Gln, n (%) Gln/His, n (%) His/His, n (%)

MUTYH

(Gln335His)


(study data)


(n=547, only women) (23)

Val/Val, n (%) Val/Ala, n (%) Ala/Ala, n (%)

PARP1

(Val762Ala)


(study data)


(n=1371) (22)

Since TC incidence is recurrently reported to be higher in women (which was also the

predominant gender in our case group), we also compared genotypic frequencies

according to gender among TC patients (in order to examine for any gender-specific

genetic effect). The frequency of the different genotypes considered did not differ

significantly with gender in TC patients (Chi-square test with Yates correction), even

after TC stratification according to histological criteria (data not shown). For this

reason, no further gender stratification of the population was considered in the

statistical analysis.

As shown in Table 3.5, no significant differences in genotypic frequencies were

observed for any of the 6 selected polymorphisms, between cases and controls (p >

0.05, Chi-square test with Yates correction). Stratifying the data according to the

histological classification of the tumours (papillary and follicular tumours) did not yield

any significant results, irrespective of the polymorphism considered. Therefore, the

results obtained concerning the genotype distributions for any of the selected

polymorphisms in TC patients, when compared to controls, do not support an

association between the presence of one genotype of any of these polymorphisms and

individual susceptibility towards TC.

72

Table 3.5. Genotypic frequencies and associated crude and adjusted ORs (95% CI) for thyroid cancer cases in relation to the XRCC1 Arg194Trp,

XRCC1 Arg399Gln, OGG1 Ser326Cys, APEX1 Asp148Glu, MUTYH Gln335His and PARP1 Val762Ala genotypes.

All thyroid cancers Papillary carcinoma Follicular carcinoma

Genotype

n (%)

Crude OR

(95% CI)

Adjusted OR

(95% CI)b

n (%)

Crude OR

(95% CI)

Adjusted OR

(95% CI)b

n (%)

Crude OR

(95% CI)

Adjusted OR

(95% CI)b

XRCC1

Arg194Trp 108 (100) 77 (100) 28 (100)

Arg/Arga 98 (90.7) 1 (Reference) 1 (Reference) 71 (92.2) 1 (Reference) 1 (Reference) 24 (85.7) 1 (Reference) 1 (Reference)

Arg/Trp 8 (7.4) 0.76 (0.33-1.78) 0.76 (0.32-1.79) 4 (5.2) 0.53 (0.17-1.59) 0.52 (0.17-1.6) 4 (14.3) 1.56 (0.49-4.91) 1.59 (0.49-5.15)

Trp/Trp 2 (1.9) N.D. N.D. 2 (2.6) N.D. N.D. 0 (0) N.D. N.D.

XRCC1

Arg399Gln 109 (100) 78 (100) 28 (100)

Arg/Arga 46 (42.2) 1 (Reference) 1 Reference) 29 (37.2) 1 (Reference) 1 (Reference) 15 (53.6) 1 (Reference) 1 (Reference)

Arg/Gln 50 (45.9) 0.90 (0.55-1.47) 0.91 (0.55-1.49) 38 (48.7) 1.09 (0.62-1.90) 1.10 (0.62-1.93) 12 (42.9) 0.66 (0.30-1.49) 0.65 (0.28-1.49)

Gln/Gln 13 (11.9) 0.98 (0.46-2.10) 0.99 (0.46-2.14) 11 (14.1) 1.32 (0.58-3.01) 1.35 (0.59-3.12) 1 (3.6) 0.23 (0.03-1.84) 0.23 (0.03-1.83)

OGG1

Ser326Cys 108 (100) 77 (100) 28 (100)

Ser/Sera 75 (69.4) 1 (Reference) 1 (Reference) 53 (68.8) 1 (Reference) 1 (Reference) 20 (71.4) 1 (Reference) 1 (Reference)

Ser/Cys 33 (30.6) 0.78 (0.48-1.29) 0.72 (0.43-1.19) 24 (31.2) 0.81 (0.46-1.41) 0.72 (0.41-1.28) 8 (28.6) 0.72 (0.30-1.69) 0.67 (0.28-1.63)

APEX1

Asp148Glu 109 (100) 78 (100) 28 (100)

73

Asp/Aspa 31 (28.4) 1 (Reference) 1 (Reference) 23 (29.5) 1 (Reference) 1 (Reference) 7 (25.0) 1 (Reference) 1 (Reference)

Asp/Glu 52 (47.7) 0.91 (0.53-1.58) 0.91 (0.52-1.60) 39 (50.0) 0.92 (0.50-1.70) 0.92 (0.50-1.70) 12 (42.9) 0.81 (0.28-2.31) 0.98 (0.35-2.71)

Glu/Glu 26 (23.9) 0.81 (0.43-1.53) 0.80 (0.42-1.52) 16 (20.5) 0.67 (0.32-1.40) 0.64 (0.30-1.36) 9 (32.1) 0.75 (0.30-1.89) 1.30 (0.43-3.88)

MUTYH

Gln335His 109 (100) 78 (100) 28 (100)

Gln/Gln 5 (4.6) 0.63 (0.19-2.03) 1.14 (0.35-3.73) 3 (3.8) 0.83 (0.21-3.26) 0.91 (0.23-3.66) 2 (7.1) 1.77 (0.34-9.12) 2.16 (0.38-12.39)

Gln/His 40 (36.7) 0.97 (0.30-3.08) 0.68 (0.42-1.10) 27 (34.6) 0.59 (0.34-1.01) 0.62 (0.36-1.07) 11 (39.3) 0.76 (0.33-1.74) 0.83 (0.36-1.92)

His/Hisa 64 (58.7) 1 (Reference) 1 (Reference) 48 (61.5) 1 (Reference) 1 (Reference) 15 (53.6) 1 (Reference) 1 (Reference)

PARP1

Val762Ala 108 (100) 78 (100) 27 (100)

Val/Vala 78 (72.2) 1 (Reference) 1 (Reference) 57 (73.1) 1 (Reference) 1 (Reference) 19 (70.4) 1 (Reference) 1 (Reference)

Val/Ala 30 (27.8) 1.35 (0.79-2.29) 0.79 (0.46-1.35) 21 (26.9) 1.29 (0.71-2.34) 1.21 (0.66-2.21) 8 (29.6) 1.47 (0.61-3.58) 1.53 (0.61-3.83)

aIndividuals with this genotype were considered as referent class. bORs were adjusted, by means of multivariate logistic regression analysis, for

gender (male and female), age (<30, 30-46, 50-69 and ≥70 years) and smoking status (non-smoker and smoker).

74

In addition, logistic regression analysis concerning the effect of the different

polymorphisms on TC risk (adjusted for age at diagnosis, smoking habits and gender)

was performed. No significant change in crude or adjusted OR was observed for any of

the genotypes considered (Table 3.5), further suggesting that none of the

polymorphisms, individually considered, is associated with TC risk. Again, after

stratifying data according to histological subtype, no significant change in crude or

adjusted OR was revealed in either papillary or follicular TC subgroups. However,

when considering only the papillary subtype of TC, OR values for the MUTYH

Gln335His polymorphism almost reached significance: a borderline decrease in the risk

of papillary TC was apparent for heterozygous (Gln/His) individuals (adjusted OR = 0.6,

95% CI: 0.4-1.1, p = 0.080; Table 3.5).

Finally, we evaluated whether the presence of variant forms in any of the selected

polymorphisms was associated with early-age at diagnosis (i.e., predisposal to early

development of the disease) or not. The observed results (data not shown) do not

support this hypothesis since the age at TC diagnosis did not differ significantly with

genotype, for any of the polymorphisms.

Discussion

In this study, we report the role of genetic polymorphisms XRCC1 Arg194Trp (C➝T)

and Arg399Gln (G➝A), OGG1 Ser326Cys (C➝G), APEX1 Asp148Glu (T➝G),

MUTYH Gln335His (G➝C) and PARP1 Val762Ala (T➝C) on the individual

susceptibility for TC. The frequencies of the different genotypes observed in the control

population are similar to those reported in other Caucasian populations.

XRCC1 is a nuclear protein that, despite lacking any enzymatic activity, plays an

important role in the efficient repair of SSBs and in the BER pathway: it acts as a

scaffold protein that facilitates the recruitment of multiple DNA repair enzymes (such as

Pol β, hOGG1, APEX1, PARP1 and LIG3) to lesion sites and coordinates the DNA

damage repair response. Arg194Trp and Arg399Gln are among the most extensively

studied XRCC1 coding region SNPs. Both polymorphisms have been shown to alter

the functional activity of the resulting protein in vitro and to interfere with cancer

susceptibility: the 194Trp allele has been associated with increased protein function

(hence, enhanced DNA repair capacity and lower sensitivity to genotoxicants) and

decreased risk of certain cancers, particularly among smokers; on the contrary, the

399Gln allele is suggested to be associated with decreased DNA repair capacity and

higher sensitivity to genotoxicants. Epidemiological evidence for an association

75

between the Arg399Gln polymorphism and cancer susceptibility is weaker (often

negative, inconsistent or conflicting) and associations in opposite directions depending

on cancer type and smoking status have been suggested. Other gene-environment

(e.g. drinking status or menopausal age) and gene-gene interactions (e.g. other DNA

repair or chemical metabolizing enzymes) have also been reported for both SNPs.

Numerous other well-powered studies and meta-analyses have not, however,

confirmed these putative effects (reviewed in refs. (10, 24). Overall, in face of the

disparity in the results reported thus far, these amino acid substitutions appear to have

only a modest (if any) impact on XRCC1 activity and cancer susceptibility (unless when

considered together with other relevant environmental or genetic factors). The

epidemiological studies performed thus far in respect to the contribution of these SNPs

to TC susceptibility have yielded conflicting results. Our results do not support an

association between TC risk and the XRCC1 Arg399Gln polymorphism, in agreement

with the majority of the studies (25-28). This hypothesis should not be ruled out,

however, since two other groups have recently reported a protective effect for the

399Gln allele in well-powered cohorts: in both studies, the 399Gln allele was

associated with decreased risk of differentiated TC [OR = 0.70, 95% CI: 0.50-1.00, p =

0.049; (29)] or papillary TC [OR = 0.70, 95% CI: 0.59-0.93, p = 0.03; (30)]. On the

contrary, the 194Trp allele has been shown to increase the risk of developing

differentiated TC [OR = 1.4, 95% CI: 0.9-2.1, for the heterozygous genotype (29); OR =

1.85, 95% CI: 1.11-3.07 (25)]. Furthermore, Chiang et al (25) observed that this genetic

effect came primarily from the subjects with LN metastasis (OR = 4.54, 95% CI: 2.11-

9.79, p = 0.0001), and was also higher when the XRCC1 and PARP1 genotypes were

considered together. The results in our study do not reveal a significant association

between the XRCC1 Arg194Trp variant genotype and TC risk in a Caucasian

Portuguese population. It is possible that the differences in 194Trp allelic frequency

between Caucasian and Asian populations obscured a possible association in our

study. However, one must also recall that the 194Trp allele is often associated with

enhanced DNA repair capacity, lower sensitivity to genotoxicants and decreased risk of

other cancers (see above). In line with this, Sigurdson et al (28) observed, in a large

cohort, that the minor allele of the XRCC1 Arg194Trp polymorphism was associated

with decreased thyroid nodule risk (OR = 0.5, 95% CI: 0.3-0.9, p = 0.03), describing a

similar pattern of association for a small number of papillary TC (n = 25) (28). Also, in a

small case-control study in a Korean population (27), the 194Trp heterozygous

genotype was significantly associated with a decreased risk of papillary TC (OR = 0.55,

76

95% CI: 0.31‑0.98). The results presented by Ho et al (29) and Chiang et al (25) should

therefore be interpreted with caution. It is possible that the XRCC1 Arg194Trp

polymorphism may have opposing effects depending on the disease development

stage, on the presence of different environmental risk factors or on different genetic

backgrounds among populations. Larger studies and/or a meta-analysis are needed in

order to further clarify the role of the XRCC1 polymorphisms in TC susceptibility.

Concerning our data, the results do not reveal a significant involvement of OGG1

Ser326Cys polymorphism on the individual susceptibility towards TC, since the

genotype frequencies are similar in control and cancer patient populations (Table 3.3),

and no increase in TC risk was associated with this polymorphism (Table 3.5). These

results are in agreement with those recently reported by Garcia-Quispes et al (26) in

the only other case-control study where the influence of the OGG1 Ser326Cys

genotype on TC risk was also evaluated. The OGG1 Ser326Cys polymorphism has

been demonstrated to impair protein function (10) and, as such, has been widely

evaluated in different case-control studies: the available evidence supporting an

association with cancer susceptibility is scarce, however, with significant results being

limited, mainly, to lung cancer (11, 31). Of notice, three recently performed meta-

analysis (31-33) did not reveal any significant association between the OGG1

Ser326Cys polymorphism and breast cancer risk: these studies, taken together,

suggest a minor role for the OGG1 Ser326Cys polymorphism in endocrine cancer

susceptibility (as is the case of TC).

The MUTYH protein is a BER glycosylase that is involved in the repair of oxidative

DNA lesions such as 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxo-dG), a stable

oxidation product of guanine: if left unrepaired, 8-oxo-dG can mispair with adenine

during DNA replication, leading to a G:C➝T:A transversion. The MUTYH protein

prevents these transversions by excising any adenine residue misincorporated in the

newly synthesized DNA strand opposite to 8-oxo-dG, thus allowing a second

opportunity for OGG1 to repair the lesion (34). MUTYH dysfunction may, therefore, be

especially problematic for tumorigenesis in humans since there are no other

mechanisms for repairing 8-oxo-dG/adenine mismatches. Accordingly, as excellently

reviewed elsewhere (35), two germline missense mutations in the MUTYH gene that

result in a catalytically compromised protein, Tyr165Cys and Gly382Asp, have been

unequivocally demonstrated to be associated with a colorectal adenoma and

carcinoma predisposition syndrome that is now referred to as MUTYH-associated

polyposis (MAP): MAP phenotypically resembles the classic or the attenuated forms of

77

familial adenomatous polyposis (FAP) but is transmitted as an autosomal recessive

trait associated with inherited biallelic defects in the MUTYH gene. MAP tumours

display an unusually high proportion of somatic G:C➝T:A transversion mutations in the

APC and K-ras genes, probably reflecting defective MUTYH protein activity and

consequent failure to correct A:8-oxo-dG mispairs. It is worth mentioning that, as it has

been firmly established for FAP patients, MAP patients may also be at increased risk of

developing extra-colonic tumours such as TC: TC has sporadically been observed in

MAP patients (36, 37) but, for the time being, evidence is insufficient to establish an

association between MAP and TC. Besides the Tyr165Cys and Gly382Asp variants,

many other MUTYH germline mutations and SNPs have been described to date, most

of them rare and/or of ‘uncertain pathogenicity’ (35). MUTYH Gln335His is a common

polymorphism located on exon 12 (35), more frequently detected in Japanese and

Chinese than in European populations. The enzyme encoded by this variant has been

demonstrated to have partially impaired glycosylase activity in vitro (compared to the

wild-type, the variant enzyme was 34% less active in removing adenine from

substrates containing an A:GO mismatch) (38) and could therefore contribute to cancer

susceptibility. The possible association between the MUTYH Gln335His polymorphism

and cancer risk has been extensively studied in Asian (mainly Japanese) and other

populations: the 335His variant allele has been suggested to be associated with

increased risk of colorectal cancer (mainly when limited to specific anatomical

locations) (39, 40) and, less consistently, lung cancer (41). For the latter, however,

existing evidence is conflicting or significant only when taking gene-gene interactions

into account (42). To our knowledge, no significant correlation between the MUTYH

Gln335His genotype and cancer risk has been described for any other type of cancer.

Interestingly, an almost significant decrease in breast cancer risk (OR = 0.80, 95% CI:

0.59-1.07) in MUTYH Gln335His heterozygotes (Gln/His) was reported in a Portuguese

Caucasian population (23). Also, in a bladder cancer susceptibility study, gene-gene

interactions among BER polymorphisms (including MUTYH Gln335His) were observed

in ever smokers (43), suggesting that BER genetic variation might contribute to cancer

risk through gene-gene and gene-environmental interactions. To the best of our

knowledge, no clinical association studies have been performed thus far to evaluate

the role of the MUTYH Gln335His polymorphism on TC susceptibility. The results

reported here for the MUTYH Gln335His polymorphism suggest that it is not associated

with TC risk (Table 3.5). However, when considering only the papillary subtype of TC,

OR values for the MUTYH Gln335His polymorphism almost reached significance: a

78

borderline effect associated to a decreased risk of papillary TC was apparent for

heterozygous (Gln/His) individuals (Table 3.5). However, it should not be excluded that

this effect could be related to sample size. This is the first time that the putative

association between the MUTYH Gln335His polymorphism and TC susceptibility has

been evaluated. The results reported here strongly suggest that its role in papillary TC

susceptibility be further evaluated in a larger study population, in order to verify its

potential usefulness as a predictive biomarker of genetic susceptibility to TC.

APEX1, the major human AP endonuclease, plays a central role in the BER pathway

due to its ability to process abasic sites and other 3' DNA termini that may result, for

example, from exposure to IR or direct attack by free radicals (11). The APEX1

Asp148Glu polymorphism is the most common and most studied non-synonymous

APEX1 coding region variant (10, 11). Despite the enzyme encoded by the variant form

of this polymorphism has been demonstrated in vitro to possess no significant impact

on endonuclease and DNA binding activities, its potential role on cancer susceptibility

has been frequently studied: as expected, the largest and strongest body of evidence

(including four recent GWAS on breast cancer susceptibility and a meta-analysis on

both lung and aerodigestive tract cancers) suggests no association between the

148Glu allele and cancer risk (reviewed in ref. (10). On the contrary, Hu et al have

demonstrated that the variant form of the enzyme is associated with cell cycle G2 delay

in response to IR, therefore contributing to IR hypersensitivity (17). Also, the APEX1

Asp148Glu polymorphism was not shown to be associated with the non-medullary form

of TC (25) in the only association study concerning TC that came to our knowledge, nor

was it associated with thyroid nodules in a well-powered study involving IR-exposed

populations (28). In agreement with this overwhelming evidence, our results do not

support an association between APEX1 Asp148Glu polymorphism and TC risk, since

neither the differences in genotypic frequencies observed between case and control

groups nor ORs are statistically significant.

PARP1 is an abundant nuclear protein that can bind to DNA and promote the

poly(ADP-ribosyl)ation of a variety of proteins (including itself). Among other roles,

PARP1 has a major signalling role in DNA damage detection and repair, acting as a

molecular nick sensor to initiate the recruitment of XRCC1 and other DNA repair

proteins: transient binding of PARP1 to DNA single or double strand breaks allows for

autoribosylation and subsequent interaction with XRCC1 and, possibly, a number of

other DNA repair proteins (44). One common non-synonymous SNP, PARP1

Val762Ala, results in an amino acid substitution within the COOH-terminal catalytic

79

domain of the enzyme. This variant has been associated with reduced enzymatic

activity (44) and limited capacity for interaction with XRCC1 (45). This may result in

attenuated BER capacity and thus increased cancer predisposition in PARP1 Ala762

carriers. In fact, the variant form of the PARP1 Val762Ala polymorphism has been

associated, in several well-powered clinical association studies, with increased cancer

susceptibility, namely lung (44) and GI tract (45) cancers. Studies regarding other types

of cancer, namely breast cancer (22, 46), have failed to demonstrate an association

between PARP1 Val762Ala genotype and cancer susceptibility. The results obtained in

this study do not suggest any association between PARP1 Val762Ala polymorphism

and TC risk (Table 3.5), in agreement with the results reported by Chiang et al (25) in

the only other clinical association study where the role of PARP1 Val762Ala

polymorphism on TC risk was assessed, suggesting that this polymorphism may not

play a significant role in the disease. However, given the evidence available and the

possibility for interaction with smoking status and/or XRCC1 genotype (25, 44, 45),

more in depth studies should be pursued in order to further clarify this issue.

Concluding, our results do not reveal a significant involvement of XRCC1 Arg194Trp

and Arg399Gln, OGG1 Ser326Cys, APEX1 Asp148Glu, MUTYH Gln335His and

PARP1 Val762Ala polymorphisms on the individual susceptibility towards TC, mostly in

agreement with the limited evidence that is available specifically for TC risk. This was

the first time that the putative association between the MUTYH Gln335His

polymorphism and TC susceptibility was evaluated: when the histological stratification

analysis was performed, we observed that the association between the presence of

heterozygosity in the MUTYH Gln335His polymorphism and TC risk almost reached

significance for the papillary subtype of TC. Since the sample size was modest, the

possibility of a type I error should not be excluded and this result should, therefore, be

interpreted with caution. More in-depth studies involving larger populations should be

pursued in order to further clarify this issue and to verify the potential usefulness of the

MUTYH Gln335His genotype as a predictive biomarker of susceptibility to TC. Also,

since BER genetic variation alone seems to have, at best, only a modest impact on TC

susceptibility (unless when considered together with other relevant risk factors), future

studies regarding the putative role of BER polymorphisms on TC risk should be

powered to allow for the study of gene-environment (e.g. smoking and drinking status,

IR exposure) and gene-gene (e.g. other DNA repair or chemical metabolizing

enzymes) interactions as well as stratified analysis according to histological subtype

and disease developmental stage. Haplotype analysis should also be considered.

80

Acknowledgements

We wish to thank Luísa Manso Oliveira, Lylliane Luz, Silvia Morgado Amaro and Maria

Catarina Soveral for technical support. This study was supported by the Center for

Research in Human Molecular Genetics (CIGMH), Projects PTDC/SAU-

OSM/105572/2008, PTDC/SAU-ESA/102367/2008 and PTDC/QUI/67522/2006 from

Fundação para a Ciência e Tecnologia (FCT) and Fundação Calouste Gulbenkian

(Grant 76438/2006). The grants to M. Pingarilho (SFRH/BD/22612/2005) from FCT are

also acknowledged.

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Chapter IV

The role of CCNH Val270Ala (rs2230641) and other nucleotide excision repair

polymorphisms in individual susceptibility to well-differentiated thyroid cancer

[Research Paper]


Santos LS, Gomes BC, Gouveia R, Silva SN, Azevedo AP, Camacho V, Manita I,

Gil OM, Ferreira TC, Limbert E, Rueff J and Gaspar JF (2013). The role of CCNH

Val270Ala (rs2230641) and other nucleotide excision repair polymorphisms in

individual susceptibility to well-differentiated thyroid cancer. Oncol Rep. 30(5):

2458-66. (DOI: 10.3892/or.2013.2702)




86

87

Chapter IV - The role of CCNH Val270Ala (rs2230641) and other nucleotide

excision repair polymorphisms in individual susceptibility to well-differentiated

thyroid cancer

Abstract

Well-differentiated thyroid cancer (DTC) is the most common form of thyroid cancer

(TC); however, with the exception of radiation exposure, its aetiology remains largely

unknown. Several single nucleotide polymorphisms (SNPs) have previously been

implicated in DTC risk. Nucleotide excision repair (NER) polymorphisms, despite

having been associated with cancer risk at other locations, have received little attention

in the context of thyroid carcinogenesis. In order to evaluate the role of NER pathway

SNPs in DTC susceptibility, we performed a case-control study in 106 Caucasian

Portuguese DTC patients and 212 matched controls. rs2230641 (CCNH), rs2972388

(CDK7), rs1805329 (RAD23B), rs3212986 (ERCC1), rs1800067 (ERCC4), rs17655,

rs2227869 (ERCC5), rs4253211 and rs2228529 (ERCC6) were genotyped using

TaqMan® methodology, while conventional PCR-RFLP was employed for rs2228000

and rs2228001 (XPC). When considering all DTC cases, only rs2230641 (CCNH) was

associated with DTC risk; a consistent increase in overall DTC risk was observed for

both the heterozygous genotype (OR = 1.89, 95% CI: 1.14-3.14) and the variant allele

carriers (OR = 1.79, 95% CI: 1.09-2.93). Histological stratification analysis confirmed

an identical effect on follicular TC (OR = 2.72, 95% CI: 1.19-6.22, for heterozygous; OR

= 2.44, 95% CI: 1.07‑5.55, for variant allele carriers). Considering papillary TC, the

rs2228001 (XPC) variant genotype was associated with increased risk (OR = 2.33,

95% CI: 1.05-5.16), while a protective effect was observed for rs2227869 (ERCC5)

(OR = 0.26, 95% CI: 0.08‑0.90, for heterozygous; OR = 0.25, 95% CI: 0.07-0.86, for

variant allele carriers). No further significant results were observed. Our results suggest

that NER polymorphisms such as rs2230641 (CCNH) and, possibly, rs2227869

(ERCC5) and rs2228001 (XPC), may influence DTC susceptibility. However, larger

studies are required to confirm these results.

Key words: CCNH, DNA repair, genetic susceptibility, nucleotide excision repair, single

nucleotide polymorphisms, well-differentiated thyroid cancer

Introduction

88

Thyroid cancer (TC) is a rare neoplasia, but is the most frequent endocrine malignancy

(1). In general, it originates from thyroid follicular cells and its most common

histological types are papillary carcinoma (≈70-80%) and follicular carcinoma

(≈10‑20%) (2). Papillary and follicular TC are often categorized together as non-

medullary well-differentiated thyroid cancer (DTC), and, in contrast to undifferentiated

(anaplastic) TC, have indolent behaviour and can be treated with high survival rates,

particularly if they are localized and small-sized (1). TC can occur in any age group but

its incidence increases with age (1). This type of cancer (particularly DTC) is 3 times

more likely to occur in women than in men and, in the past 2 decades, its incidence has

increased (1). The best-established cause of thyroid carcinogenesis is exposure to

ionizing radiation, although other candidate risk factors such as dietary iodine

deficiency, hormonal factors, benign thyroid conditions and familial history have also

been noted (2).

DTC frequency is significantly higher in relatives (particularly first-degree) of DTC

patients compared to the general population (2, 3). However, familial DTC accounts for

only a minor percentage of cases (2), suggesting that other genetic risk factors could

be involved. Identifying such individual genetic differences so that these may be used

as genetic susceptibility markers for DTC in the remaining sporadic cases is therefore

an important challenge. In line with this, several DNA polymorphisms in genes involved

in endobiotic or xenobiotic metabolism (including GST and CYP superfamilies), in

hormonal and iodine metabolism (such as TG), in cell-cycle control and regulation of

apoptosis (such as TP53), in kinase-dependent signalling pathways (such as RET) and

in DNA repair (among others) have been associated with differential susceptibility to

DTC [reviewed in reference (3)]. The first genome-wide association study (GWAS)

performed on TC identified 2 other polymorphisms located near the FOXE1 (TTF-2)

and NKX2-1 (TTF-1) genes (which encode for thyroid-specific transcription factors) as

strong genetic risk markers of sporadic DTC in European populations (4).

Since patients with papillary TC present a significant increase in DNA damage (5) and

DNA repair mechanisms are important in correcting such damage, it is reasonable to

assume that defective DNA repair capacity may contribute to DTC risk. Variants in

DNA repair genes may affect the DNA repair capacity and, in fact, several single

nucleotide polymorphisms (SNPs) in almost all DNA repair pathways have been shown

to incrementally contribute to cancer risk (6). Regarding TC, polymorphisms in DNA

repair genes such as XRCC1 (7-9) and possibly MUTYH (10) (BER pathway), Ku80

(11) (NHEJ pathway), BRCA1 (12), XRCC3 and possibly RAD51 (13) (HR pathway)

89

have been associated with either TC or, more specifically, DTC risk [reviewed in

references (3, 14, 15)].

Nucleotide excision repair (NER) is a versatile DNA repair mechanism capable of

repairing UV light-induced lesions, bulky DNA adducts, distorting interstrand crosslinks

and even certain oxidative lesions (16). A significant association between an ERCC2

haplotype (rs13181/rs1799793) and TC risk (mainly papillary) was previously reported

by our team (17), suggesting that NER polymorphisms may also be relevant for thyroid

carcinogenesis. However, to our knowledge, no other published study has thus far

focused on a possible role of NER pathway SNPs in DTC susceptibility.

Therefore, we carried out an exploratory hospital-based case-control study in a

Caucasian Portuguese population to evaluate the potential modifying role of a panel of

11 NER pathway SNPs (CCNH rs2230641, CDK7 rs2972388, RAD23B rs1805329,

ERCC1 rs3212986, ERCC4 rs1800067, ERCC5 rs17655 and rs2227869, ERCC6

rs4253211 and rs2228529 and XPC rs2228000 and rs2228001) on the individual

susceptibility to non-familial DTC.


Study subjects

This study included 106 Caucasian Portuguese DTC patients without familial history of

TC, previous neoplastic pathology and recent blood transfusion. Patients were

recruited in the Department of Nuclear Medicine of the Portuguese Oncology Institute

of Lisbon, where they received Iodine-131 treatment. Histological diagnosis was

confirmed for all cases. For each case, 2 age- (±2 years) and gender-matched controls

were recruited. Controls (n = 212), with no previous or current malignant disease and

no personal or familiar history of thyroid pathology, were recruited at São Francisco

Xavier Hospital, where they were observed for non-neoplastic pathology. Information

on demographic characteristics, family history of cancer, lifestyle habits (such as

smoking, alcohol drinking) and exposure to ionizing radiation was collected using a

questionnaire administered by trained interviewers. Former smokers were considered

as non-smokers if they had given up smoking either 2 years before DTC diagnosis or 2

years before their inclusion as controls. The response rate was > 95% for cases and

controls. The anonymity of patients and controls was guaranteed and written informed

consent was obtained from all those involved, prior to blood withdrawal, in agreement

with the Declaration of Helsinki. Approval by the institutional ethics boards of the

involved institutions was mandatory.

90

DNA extraction

Peripheral blood samples of all patients and controls were collected into 10 ml

heparinized tubes and kept at -80˚C. Genomic DNA was obtained from each sample

using a commercially available kit (QIAamp® DNA mini kit; Qiagen) according to the

manufacturer's instructions. All DNA samples were stored at -20˚C until analysis.

SNP selection

Publicly available databases such as NCBI (http://www.ncbi.nlm.nih.gov/snp/),

Genecards (http://www.genecards.org) and SNP500Cancer

(http://variantgps.nci.nih.gov/cgfseq/pages/snp500.do) were used to search for NER

polymorphisms. Eligible SNPs had to be located either in a coding or splice region and

had to exhibit minor allele frequency (MAF) > 0.05 in Caucasian populations. Despite

being located on the 3'UTR region, rs3212986 (ERCC1) was also selected since it is

one of the most extensively studied ERCC1 SNPs and evidence exists for functional

significance (18, 19). In total, 9 common nsSNPs, 1 synonymous SNP and 1 SNP

located on 3'UTR were selected (Table 4.1).


amino acid exchanges, minor allele frequency and AB assay used for genotyping.

Gene Location dbSNP cluster

ID (rs no.)

Base

change

Amino acid

change

MAF

(%)a

AB assay ID

CCNH 5q13.3-q14 rs2230641 T→C Val270Ala 13.8 C_11685807_10

CDK7 5q12.1 rs2972388 T→C Asn33Asn 40.5 C_1191757_10

RAD23B 9q31.2 rs1805329 C→T Ala249Val 16.7 C_11493966_10

ERCC1 19q13.32 rs3212986 C→A -b 29.4 C_2532948_10

ERCC4 16p13.3 rs1800067 G→A Arg415Gln 3.1 C_3285104_10

ERCC5 13q22-q34 rs17655 G→C Asp1104His 37.7 C_1891743_10

ERCC5 13q22-q34 rs2227869 G→C Cys529Ser 4.9 C_15956775_10

ERCC6 10q11 rs4253211 G→C Arg1230Pro 6.4 C_25762749_10

ERCC6 10q11 rs2228529 A→G Gln1413Arg 15.6 C_16171343_10

XPC 3p25 rs2228000 C→T Ala499Val 24.8 -c

XPC 3p25 rs2228001 A→C Lys939Gln 34.4 -c

aMinor allele frequency, according to http://www.ncbi.nlm.nih.gov/projects/SNP/; bSNP

located on 3'UTR; cnot applicable (genotyping performed by PCR-RFLP). SNPs, single

nucleotide polymorphisms.

http://www.ncbi.nlm.nih.gov/projects/SNP/%3B

91

Genotyping

rs2230641 (CCNH), rs2972388 (CDK7), rs1805329 (RAD23B), rs3212986 (ERCC1),

rs1800067 (ERCC4), rs17655 and rs2227869 (ERCC5), rs4253211 and rs2228529

(ERCC6) were genotyped by real-time PCR, using TaqMan SNP Genotyping Assays

(Applied Biosystems). To assure uniformity in genomic DNA content (2.5 ng/μl) in all

samples, DNA was quantified using the fluorimetric Quant-iT™ Picogreen® dsDNA

Assay kit (Invitrogen Life Technologies) and a Zenyth 3100 plate reader (Anthos

Labtec Instruments), according to the manufacturer's recommendations. PCR was

performed in a 7300 Real-Time PCR system thermal cycler (Applied Biosystems).

Genotyping assays used are identified in Table 4.1. The amplification conditions

consisted of an initial activation step (10 min, 95˚C), followed by ≥ 40 amplification

cycles of denaturation (15 sec, 92˚C) and annealing/extension (60 sec, 60˚C). Allelic

discrimination was performed by measuring fluorescence emitted by VIC and FAM

dyes in each well (60 sec) and computing the results into the System SDS software

version 1.3.1.

rs2228000 and rs2228001 (XPC) genotyping was performed by PCR-RFLP. Primer

sequences, PCR conditions, PCR product sizes, restriction analysis conditions and

expected digestion pattern for each XPC genotype have been described elsewhere

(20).

Genotyping was repeated for all inconclusive samples. Also, genotype determinations

were carried out twice in independent experiments (100% of concordance between

experiments) for all samples when SNPs were genotyped by PCR-RFLP and for 10-

15% of samples when SNPs were genotyped by real-time PCR.


Hardy-Weinberg frequencies for all alleles in patients and controls were analysed using

exact probability tests available in Mendel software (V5.7.2) (21). The Kolmogorov-

Smirnov and Shapiro-Wilk tests were used to verify the normality of continuous

variables and the Levene's test was used to analyse the homogeneity of variances.

Differences in genotype frequency, smoking status, age class and gender distributions

between patients and controls were evaluated by the χ2 test. Adjusted odds ratio (OR)

and corresponding 95% confidence interval (CI) were calculated using unconditional

multiple logistic regression. The model for adjusted OR included terms for gender, age

at diagnosis (≤30, 31-49, 50-69 and ≥70 years) and smoking habits

92

(smokers/non‑smokers). Male gender, lower age group and non-smokers were

considered the reference groups for these variables. For controls, age at diagnosis was

defined as the matched case age of diagnosis. All analyses were performed using

SPSS 15.0 (SPSS, Inc.).

Results

This study comprised 106 DTC patients and 212 age- and gender-matched controls.

The histological classification of DTC cases was 73.6% papillary tumours (78 patients)

and 26.4% follicular tumours (28 patients). Table 4.2 lists the general characteristics of

both case and control populations. In the case group, the frequency of females (90

patients) was significantly higher than the frequency of males (16 patients), in

accordance with the worldwide estimation for gender distribution in DTC (1). Case and

control populations are not statistically different in respect to age distribution, gender

and smoking habits.

Table 4.2. General characteristics for the DTC cases (n = 106) and control population

(n = 212).

Characteristics Controls, n (%) Cases, n (%) p-valuec

Gender

Male 31 (14.6) 16 (15.1) 0.91

Female 181 (85.4) 90 (84.9)

Agea,b

≤30 9 (4.2) 4 (3.8)

0.99 31-49 77 (36.3) 39 (36.8)

50-69 100 (47.2) 49 (46.2)

≥70 26 (12.3) 14 (13.2)

Smoking habits

Non-smokers 172 (81.1) 94 (88.7)

0.12 Smokers 38 (17.9) 12 (11.3)

Missing 2 (0.9) 0 (0.0)

aAge of diagnosis, for cases; bage at the time of diagnosis of the matched case, for

controls; cp-value determined by χ2 test (cases vs. control group). DTC, well-

differentiated thyroid cancer.

93

This report includes a set of 11 SNPs in 8 NER pathway genes (Table 4.1). The MAF

and genotypic frequencies of these SNPs, in both DTC cases and controls, are

depicted in Table 4.3. All SNPs considered are in Hardy-Weinberg equilibrium (p ≥

0.05), both in case and control populations, except for rs2972388 (CDK7) and

rs2228000 (XPC) that show a significant deviation in the control (rs2972388) or case

population (rs2228000).

Genotypic distributions were compared among cases and controls (Table 4.3). A

significant difference was observed only for rs2230641 (CCNH) (p = 0.04). When

considering a dominant model of inheritance, the difference in rs2230641 (CCNH)

genotypic frequency between cases and controls was even more significant (p = 0.02).

Through logistic regression analysis (Table 4.3), we observed that the rs2230641

(CCNH) heterozygous genotype was significantly associated with increased DTC risk

(adjusted OR = 1.89, 95% CI: 1.14-3.14, p = 0.01). Similar results were verified when

considering at least one variant allele (adjusted OR = 1.79, 95% CI: 1.09-2.93, p =

0.02), further supporting an association between rs2230641 (CCNH) and DTC risk.

Also, an almost significant association between the rs2227869 (ERCC5) heterozygous

genotype and reduced DTC risk was observed (adjusted OR = 0.39, 95% CI:

0.16‑1.00, p = 0.05).

Table 4.3. Genotype distribution in case (n = 106) and control (n = 212) populations

and associated DTC risk (adjusted ORs).

MAF Genotype frequency

Genotype Controls Cases Controls,

n (%)

Cases, n

(%)

p-

valuea

Adjusted OR

(95% CI)b

CCNH rs2230641 212 (100) 106 (100)

Val/Val C: 0.17 C: 0.23 148 (69.8) 60 (56.6) 1 (Reference)

Val/Ala 56 (26.4) 43 (40.6) 0.04c 1.89 (1.14-3.14)c

Ala/Ala 8 (3.8) 3 (2.8) 1.01 (0.25-4.03)

Val/Ala + Ala/Ala 64 (30.2) 46 (43.4) 0.02c 1.79 (1.09-2.93)c

CDK7 rs2972388 206 (100) 101 (100)

T/T C: 0.48 C: 0.42 63 (30.6) 37 (36.6) 1 (Reference)

T/C 88 (42.7) 43 (42.6) 0.42 0.86 (0.50-1.49)

C/C 55 (26.7) 21 (20.8) 0.62 (0.32-1.19)

T/C + C/C 143 (69.4) 64 (63.4) 0.29 0.77 (0.46-1.27)

RAD23B rs1805329 212 (100) 106 (100)

94

Ala/Ala T: 0.16 T: 0.17 150 (70.8) 75 (70.8) 1 (Reference)

Ala/Val 55 (25.9) 27 (25.5) 0.98 0.94 (0.54-1.62)

Val/Val 7 (3.3) 4 (3.8) 1.19 (0.33-4.30)

Ala/Val + Val/Val 62 (29.2) 31 (29.2) 1.00 0.96 (0.57-1.62)

ERCC1 rs3212986 211 (100) 106 (100)

C/C A: 0.24 A: 0.21 118 (55.9) 64 (60.4) 1 (Reference)

C/A 83 (39.3) 39 (36.8) 0.61 0.84 (0.51-1.37)

A/A 10 (4.7) 3 (2.8) 0.52 (0.14-1.99)

C/A + A/A 93 (44.1) 42 (39.6) 0.45 0.80 (0.50-1.30)

ERCC4 rs1800067 210 (100) 102 (100)

Arg/Arg A: 0.11 A: 0.13 168 (80.0) 77 (75.5) 1 (Reference)

Arg/Gln 38 (18.1) 23 (22.5) 0.65 1.34 (0.74-2.43)

Gln/Gln 4 (1.9) 2 (2.0) 1.05 (0.19-5.98)

Arg/Gln + Gln/Gln 42 (20.0) 25 (24.5) 0.36 1.31 (0.74-2.33)

ERCC5 rs17655 212 (100) 105 (100)

Asp/Asp C: 0.30 C: 0.28 106 (50.0) 51 (48.6) 1 (Reference)

Asp/His 85 (40.1) 50 (47.6) 0.12 1.22 (0.75-1.98)

His/His 21 (9.9) 4 (3.8) 0.42 (0.13-1.29)

Asp/His + His/His 106 (50.0) 54 (51.4) 0.81 1.07 (0.67-1.72)

ERCC5 rs2227869 212 (100) 106 (100)

Cys/Cys C: 0.07 C: 0.04 184 (86.8) 99 (93.4) 1 (Reference)

Cys/Ser 27 (12.7) 6 (5.7) 0.14 0.39 (0.16-1.00)

Ser/Ser 1 (0.5) 1 (0.9) 1.77 (0.11-29.10)

Cys/Ser + Ser/Ser 28 (13.2) 7 (6.6) 0.08 0.44 (0.19-1.06)

ERCC6 rs4253211 211 (100) 102 (100)

Arg/Arg C: 0.11 C: 0.13 170 (80.6) 79 (77.5) 1 (Reference)

Arg/Pro 37 (17.5) 20 (19.6) 0.75 1.26 (0.68-2.33)

Pro/Pro 4 (1.9) 3 (2.9) 1.86 (0.39-8.91)

Arg/Pro + Pro/Pro 41 (19.4) 23 (22.5) 0.52 1.31 (0.72-2.37)

ERCC6 rs2228529 211 (100) 104 (100)

Gln/Gln G: 0.24 G: 0.20 118 (55.9) 66 (63.5) 1 (Reference)

Gln/Arg 86 (40.8) 35 (33.7) 0.44 0.67 (0.40-1.12)

Arg/Arg 7 (3.3) 3 (2.9) 0.72 (0.18-2.89)

Gln/Arg + Arg/Arg 93 (44.1) 38 (36.5) 0.20 0.67 (0.41-1.11)

XPC rs2228000 212 (100) 106 (100)

95

Ala/Ala T: 0.32 T: 0.30 95 (44.8) 47 (44.3) 1 (Reference)

Ala/Val 98 (46.2) 55 (51.9) 0.21 1.16 (0.71-1.88)

Val/Val 19 (9.0) 4 (3.8) 0.43 (0.14-1.37)

Ala/Val + Val/Val 117 (55.2) 59 (55.7) 0.94 1.04 (0.65-1.67)

XPC rs2228001 212 (100) 106 (100)

Lys/Lys C: 0.36 C: 0.41 82 (38.7) 39 (36.8) 1 (Reference)

Lys/Gln 108 (50.9) 47 (44.3) 0.10 0.96 (0.57-1.61)

Gln/Gln 22 (10.4) 20 (18.9) 1.93 (0.93-4.00)

Lys/Gln + Gln/Gln 130 (61.3) 67 (63.2) 0.74 1.12 (0.69-1.83)

ap-value determined by χ2 test (cases vs. control group); bORs were adjusted for gender

(male and female), age (≤30, 31-49, 50-69, ≥70 years) and smoking status (non-smoker

and smoker). cp < 0.05. DTC, well-differentiated thyroid cancer; MAF, minor allele

frequencies.

Following stratification according to histological criteria (Table 4.4), the DTC risk

increase observed for rs2230641 (CCNH) remained in the follicular subset (adjusted

OR = 2.72, 95% CI: 1.19-6.22, p = 0.02, for heterozygous; adjusted OR = 2.44, 95%

CI: 1.07-5.55, p = 0.03, for variant allele carriers) and almost reached significance in

the papillary subset (adjusted OR = 1.74, 95% CI: 0.99-3.07, p = 0.05, for

heterozygous; adjusted OR = 1.69, 95% CI: 0.98-2.92, p = 0.06, for variant allele

carriers), supporting the idea that this polymorphism may influence DTC susceptibility,

irrespective of tumour type. The risk of papillary TC was significantly increased in

rs2228001 (XPC) homozygous variant individuals (adjusted OR = 2.33, 95% CI: 1.05-

5.16, p = 0.04) and significantly reduced in rs2227869 (ERCC5) variant allele carriers

(adjusted OR = 0.25, 95% CI: 0.07-0.86, p = 0.03) and heterozygous individuals

(adjusted OR = 0.26, 95% CI: 0.08-0.90, p = 0.03). No significant differences in

genotypic frequencies or adjusted ORs were observed for the remaining SNPs, either

when considering overall DTC cases or its histological subsets, suggesting that these

SNPs alone do not contribute to individual susceptibility to DTC.

Table 4.4. Genotype distribution in the case population (n = 106) and associated DTC

risk (adjusted ORs), after stratification according to histological type.

Papillary carcinoma Follicular carcinoma

Genotype n (%) Adjusted OR (95%

CI)a

n (%) Adjusted OR (95%

CI)a

96

CCNH rs2230641 78 (100) 28 (100)

Val/Val 45 (57.7) 1 (Reference) 15 (53.6) 1 (Reference)

Val/Ala 30 (38.5) 1.74 (0.99-3.07) 13 (46.4) 2.72 (1.19-6.22)b

Ala/Ala 3 (3.8) 1.27 (0.32-5.15) 0 (0.0) -

Val/Ala + Ala/Ala 33 (42.3) 1.69 (0.98-2.92) 13 (46.4) 2.44 (1.07-5.55)b

CDK7 rs2972388 75 (100) 26 (100)

T/T 27 (36.0) 1 (Reference) 10 (38.5) 1 (Reference)

T/C 31 (41.3) 0.87 (0.47-1.60) 12 (46.2) 0.93 (0.37-2.31)

C/C 17 (22.7) 0.70 (0.35-1.43) 4 (15.4) 0.40 (0.12-1.37)

T/C + C/C 48 (64.0) 0.80 (0.46-1.40) 16 (61.5) 0.70 (0.30-1.65)

RAD23B rs1805329 78 (100) 28 (100)

Ala/Ala 53 (67.9) 1 (Reference) 22 (78.6) 1 (Reference)

Ala/Val 22 (28.2) 1.06 (0.59-1.91) 5 (17.9) 0.56 (0.20-1.58)

Val/Val 3 (3.8) 1.27 (0.31-5.25) 1 (3.6) 1.26 (0.14-11.28)

Ala/Val + Val/Val 25 (32.1) 1.08 (0.61-1.90) 6 (21.4) 0.62 (0.24-1.63)

ERCC1 rs3212986 78 (100) 28 (100)

C/C 49 (62.8) 1 (Reference) 15 (53.6) 1 (Reference)

C/A 27 (34.6) 0.72 (0.41-1.25) 12 (42.9) 1.07 (0.47-2.44)

A/A 2 (2.6) 0.46 (0.10-2.21) 1 (3.6) 0.76 (0.09-6.64)

C/A + A/A 29 (37.2) 0.69 (0.40-1.19) 13 (46.4) 1.04 (0.47-2.33)

ERCC4 rs1800067 75 (100) 27 (100)

Arg/Arg 57 (76.0) 1 (Reference) 20 (74.1) 1 (Reference)

Arg/Gln 17 (22.7) 1.38 (0.71-2.66) 6 (22.2) 1.46 (0.54-3.99)

Gln/Gln 1 (1.3) 0.76 (0.08-7.20) 1 (3.7) 1.87 (0.18-19.10)

Arg/Gln + Gln/Gln 18 (24.0) 1.32 (0.69-2.50) 7 (25.9) 1.51 (0.59-3.88)

ERCC5 rs17655 77 (100) 28 (100)

Asp/Asp 39 (50.6) 1 (Reference) 12 (42.9) 1 (Reference)

Asp/His 36 (46.8) 1.15 (0.67-1.96) 14 (50.0) 1.48 (0.64-3.43)

His/His 2 (2.6) 0.28 (0.06-1.27) 2 (7.1) 0.82 (0.17-4.03)

Asp/His + His/His 38 (49.4) 0.99 (0.59-1.68) 16 (57.1) 1.35 (0.60-3.05)

ERCC5 rs2227869 78 (100) 28 (100)

Cys/Cys 75 (96.2) 1 (Reference) 24 (85.7) 1 (Reference)

Cys/Ser 3 (3.8) 0.26 (0.08-0.90)b 3 (10.7) 0.87 (0.24-3.15)

Ser/Ser 0 (0.0) - 1 (3.6) 5.49 (0.32-95.50)

Cys/Ser + Ser/Ser 3 (3.8) 0.25 (0.07-0.86)b 4 (14.3) 1.09 (0.34-3.46)

97

ERCC6 rs4253211 76 (100) 26 (100)

Arg/Arg 60 (78.9) 1 (Reference) 19 (73.1) 1 (Reference)

Arg/Pro 13 (17.1) 1.06 (0.52-2.15) 7 (26.9) 1.90 (0.71-5.07)

Pro/Pro 3 (3.9) 2.41 (0.50-11.72) 0 (0.0) -

Arg/Pro + Pro/Pro 16 (21.1) 1.17 (0.60-2.28) 7 (26.9) 1.79 (0.67-4.78)

ERCC6 rs2228529 76 (100) 28 (100)

Gln/Gln 47 (61.8) 1 (Reference) 19 (67.9) 1 (Reference)

Gln/Arg 26 (34.2) 0.71 (0.40-1.25) 9 (32.1) 0.64 (0.27-1.51)

Arg/Arg 3 (3.9) 0.95 (0.24-3.80) 0 (0.0) -

Gln/Arg + Arg/Arg 29 (38.2) 0.73 (0.42-1.26) 9 (32.1) 0.58 (0.24-1.36)

XPC rs2228000 78 (100) 28 (100)

Ala/Ala 34 (43.6) 1 (Reference) 13 (46.4) 1 (Reference)

Ala/Val 43 (55.1) 1.23 (0.72-2.10) 12 (42.9) 0.92 (0.39-2.13)

Val/Val 1 (1.3) 0.15 (0.02-1.18) 3 (10.7) 1.30 (0.32-5.24)

Ala/Val + Val/Val 44 (56.4) 1.06 (0.63-1.80) 15 (53.6) 0.97 (0.44-2.16)

XPC rs2228001 78 (100) 28 (100)

Lys/Lys 26 (33.3) 1 (Reference) 13 (46.4) 1 (Reference)

Lys/Gln 36 (46.2) 1.08 (0.60-1.95) 11 (39.3) 0.65 (0.27-1.54)

Gln/Gln 16 (20.5) 2.33 (1.05-5.16)b 4 (14.3) 1.17 (0.34-4.07)

Lys/Gln + Gln/Gln 52 (66.7) 1.28 (0.74-2.24) 15 (53.6) 0.73 (0.33-1.65)

aORs were adjusted for gender (male and female), age (≤30, 31-49, 50-69, and ≥70

years), and smoking status (non-smoker and smoker). bp-value < 0.05. DTC, well-

differentiated thyroid cancer.

To assess the effect of combined genotypes, further statistical analysis was applied to

those SNPs that are located in the same gene (rs17655 and rs2227869 on ERCC5;

rs4253211 and rs2228529 on ERCC6; rs2228000 and rs2228001 on XPC). Also, since

SNPs in different NER genes may influence the way their expression products interact

(hence, their repair activity), we also analysed SNP-SNP interactions between different

genes, as long as these interactions were biologically plausible. The genotype

distribution of the rs17655/rs2227869 (ERCC5) combination was significantly different

in cases and controls (p = 0.01); however, no specific ERCC5 genotype combination

was associated with altered DTC risk (data not shown), probably due to the low

number of patients included in each genetic subgroup. None of the remaining genotype

combinations showed association with disease (data not shown).

98

Discussion

We conducted a hospital-based case-control study in a Caucasian Portuguese

population to evaluate the potential modifying role of a comprehensive selection of 11

SNPs in 8 NER pathway genes in individual susceptibility to non‑familial DTC. Overall,

we observed that NER polymorphisms such as rs2230641 (CCNH) and, possibly,

rs2227869 (ERCC5) and rs2228001 (XPC) were associated with DTC susceptibility. A

consistent risk increase was observed for rs2230641 (CCNH) heterozygous and variant

allele carriers, compared to wild-type individuals, both when considering all DTC cases

and only the follicular subset. When considering only the papillary subset, the risk

association almost reached significance for rs2230641 (CCNH) but was significant for

the rs2228001 (XPC) variant genotype (increased risk). Also, a protective effect was

observed for rs2227869 (ERCC5) in heterozygous and variant allele carriers, in the

papillary subset. The association between the rs2227869 (ERCC5) heterozygous

genotype and reduced DTC risk almost reached significance when all DTC cases were

considered. No other significant correlation was observed for the remaining SNPs.

To our knowledge, this is the first study to assess the effect of these SNPs on DTC

susceptibility. Our previous study reporting an association between an ERCC2

haplotype (rs13181/rs1799793) and increased TC (mainly papillary) risk (17) is the only

other association study that we are aware of, focusing on the role of NER pathway

SNPs in TC susceptibility. However, studies correlating the polymorphisms considered

in this study with cancer risk have been published for other types of cancer.

Concerning rs2230641 (CCNH), studies on oesophageal (22) bladder (23) and renal

cell carcinoma (24) have yielded mostly negative results. Two significant associations

have been reported, with opposite findings; according to Enjuanes et al (25), the minor

allele is associated with decreased risk for chronic lymphocytic leukaemia; on the

contrary, in line with our results, Chen et al (26), observed, in ever smokers, a

significant association for the rs2230641 variant allele with bladder cancer risk and an

almost 30-fold increased risk in carriers of the rs2230641 (CCNH), rs2228526 (ERCC6)

and rs1805329 (RAD23B) variant alleles.

Previous evidence on the role of XPC polymorphisms on cancer risk is also conflicting;

both rs2228001 and rs2228000 have been extensively investigated in case-control

cancer association studies but, when considered separately, results are mostly

negative, possibly due to insufficient sample size. Increasing the power through

performance of meta-analysis has revealed small but significant increases in overall

99

(27-29), bladder (27-31) and breast (29) cancer risk for rs2228000 and in overall (28,

29), lung (27-30), bladder (29) and colorectal (29) cancer risk for rs2228001. Meta-

analyses yielding negative results have also been published (32, 33). The effect of

XPC polymorphisms may be best represented by its haplotype since significantly

increased cancer risk has been observed more frequently when considering both

polymorphisms together, as a haplotype block (22, 34), or in combined analysis with

other NER variants (23, 35, 36).

With respect to rs2227869 (ERCC5), notably, results similar to our own have been

reported by Hussain et al (37) in the only cancer association study we retrieved from

our literature review; decreased stomach cancer risk was observed in heterozygous

individuals, according to this study.

As for the remaining SNPs, rs3212986 (ERCC1), rs1800067 (ERCC4), rs17655

(ERCC5) and rs1805329 (RAD23B) have been extensively analysed in prior cancer

association studies, mostly with negative results. For rs3212986 (ERCC1), rs1800067

(ERCC4) and rs17655 (ERCC5) these findings are further corroborated by several

meta-analyses that, in agreement with our report, demonstrated no clear association

with overall (38-41), lung (42) or breast (43) cancer risk. rs2972388 (CDK7), rs4253211

and rs2228529 (ERCC6) have received little attention in the context of cancer

susceptibility but the unique reports we found for each of these SNPs are substantially

different from ours, as rs2972388 (CDK7) and rs2228529 (ERCC6) were associated,

respectively, with increased breast cancer risk in a Korean population (44) and

increased non-melanoma skin cancer risk in an American population (45). For

rs4253211 (ERCC6), the variant allele seems to confer a protective effect towards

laryngeal (36) and oesophageal (22) cancer, but no association with bladder cancer

was observed (23).

CCNH codes for Cyclin H, a protein that, together with CDK7 and MAT1, forms the

cyclin-activated kinase (CAK) complex. CAK integrates TFIIH, a larger complex

implicated in DNA denaturation prior to damage excision. CAK can also phosphorylate

nuclear receptors such as the retinoic acid or the oestrogen receptors and a very

different range of substrates (16). It is also involved in cell cycle regulation (46).

Although data on the functional consequences of rs2230641 is lacking, the pleiotropic

effects of CCNH on NER, cell cycle regulation and oestrogen receptor phosphorylation,

among others, confer biological plausibility to our hypothesis that CCNH variants

(namely, rs2230641) may be involved in cancer susceptibility. Its role in oestrogen

receptor phosphorylation could be of particular significance for DTC, which, as

100

previously noted, is an endocrine tumour 3 times more prevalent in women than in

men. Discrepancies with prior studies could therefore be explained on the basis of the

specific hormonal involvement on DTC, insignificant for the types of cancer previously

evaluated.

XPC codes for a DNA binding protein that, together with RAD23B and centrin 2, forms

the distortion-sensing component of NER, thus playing a central role in the process of

early damage recognition (16, 47). XPC is also involved in DNA damage-induced cell

cycle checkpoint regulation and apoptosis, removal of oxidative DNA damage and

redox homeostasis (47, 48). XPC deficiency has been correlated with decreased DNA

repair capacity (48), and hypersensitivity to DNA-oxidizing agents such as X-rays (47),

a well-known DTC risk factor, providing the rational basis for a putative involvement of

XPC polymorphisms in DTC susceptibility. Notably, multinodular TC was recently

reported as the most frequently observed internal tumour in Xeroderma pigmentosum

type C patients (49), further substantiating the potential role of XPC in thyroid

carcinogenesis. rs2228001 originates an amino acid substitution in the interaction

domain with TFIIH. In silico analysis indicates that rs2228001 may possibly be

damaging and in vitro evidence demonstrates differential repair capacity [reviewed in

reference (27)]. rs2228000 is located in the interaction domain of XPC with RAD23B

and, although its functional significance remains unclear, it is predicted to be benign

through in silico analysis (27). It is possible that both these variants, particularly their

haplotypes, may alter NER capacity, thereby modulating cancer susceptibility. Despite

the numerous case-control studies and meta-analyses that exist, clinical evidence is

conflicting and, thus, further studies are warranted.

ERCC5 codes for an endonuclease that exerts its activity at the 3' side of the damaged

strand (16). ERCC5 also plays a structural role, stabilizing the TFIIH complex; in its

absence, the CAK complex and the ERCC2 subunit dissociate from the TFIIH core

(50). Point mutations in ERCC5 may give rise to Xeroderma pigmentosum and

Cockayne syndrome, highlighting its importance for effective DNA repair.

It is possible that NER polymorphisms, through impairing oxidative DNA damage

repair, may contribute to DTC development. In addition, it is possible that the

pleiotropic actions of some NER proteins (such as CCNH or XPC, demonstrated to be

involved in cell cycle regulation, apoptosis or hormone signalling), may convey these

specific proteins a relevant role in carcinogenesis, particularly DTC.

Discrepancies from prior studies may have originated from the inherent characteristics

of each cancer and respective organ. Divergent genetic background and environmental

101

exposure of study populations may have also contributed. The low statistical power

inherent to small sample use may explain some of our negative results. The histology-

dependent differences observed for some SNPs could derive from different

carcinogenesis pathways (hence, different genetic risk factors) among DTC histological

types, as occurs between well‑differentiated and anaplastic TC, or, more likely, from

small sample size on stratified analysis.

Indeed, the main limitation of our study was sample size; small samples may be

underpowered to detect modest effects of low penetrance genes and, on the other

hand, may increase the probability that findings are attributable to chance, particularly

after stratification (small numbers in the subgroups). The success of more

sophisticated statistical analysis, such as haplotype analysis and evaluation of gene-

gene and gene-environment interactions, is also limited. Moreover, we cannot exclude

the possibility that other variants in linkage disequilibrium with the ones considered

here could be responsible for the observed associations.

In conclusion, our study provides, for the first time, insight into the potential role of

CCNH, ERCC5, XPC and other NER polymorphisms in DTC susceptibility. Additional

studies with larger sample sizes are necessary to validate our findings and to provide

conclusive evidence for associations between these and other NER variants and DTC

risk. Such studies should be powered to allow for haplotype analysis and evaluation of

gene-gene and gene-environment interactions. Functional studies are also warranted,

as well as a broader analysis of the involvement of NER variants in DTC progression

and therapy response.

Acknowledgements

This study was supported by the Projects PTDC/SAu-OSM/105572/2008 and

PTDC/SAu-ESA/102367/2008, Projecto Estratégico Nº Pest-E/SAU/UI0009/2011 from

Fundação para a Ciência e Tecnologia (FCT).

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XPF Arg415Gln polymorphism and breast cancer risk: a meta-analysis of case-control

studies. Breast cancer research and treatment. 2011;129(1):203-9.

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Chapter V

Mismatch repair single nucleotide polymorphisms and thyroid cancer

susceptibility

[Research Paper]


Santos LS, Silva SN, Gil OM, Ferreira TC, Limbert E, Rueff J (2018). Mismatch

repair single nucleotide polymorphisms and thyroid cancer susceptibility. Oncol

Lett. 15(5): 6715-6726. (DOI: 10.3892/ol.2018.8103)




108

109

Chapter V - Mismatch repair single nucleotide polymorphisms and thyroid

cancer susceptibility

Abstract

Thyroid cancer (TC) is the most common endocrine malignancy and its incidence

continues to rise worldwide. Ionizing radiation exposure is the best established

etiological factor. Heritability is high; however, despite valuable contribution from recent

genome‑wide association studies, the current understanding of genetic susceptibility to

TC remains limited. Several studies suggest that altered function or expression of the

DNA mismatch repair (MMR) system may contribute to TC pathogenesis. Therefore,

the present study aimed to evaluate the potential role of a panel of MMR single

nucleotide polymorphisms (SNPs) on the individual susceptibility to well‑differentiated

TC (DTC). A case‑control study was performed involving 106 DTC patients and 212

age‑ and gender‑matched controls, who were all Caucasian Portuguese. Six SNPs

present in distinct MMR genes (MLH1 rs1799977, MSH3 rs26279, MSH4 rs5745325,

PMS1 rs5742933, MLH3 rs175080 and MSH6 rs1042821) were genotyped through

TaqMan® assays and genotype‑associated risk estimates were calculated. An

increased risk was observed in MSH6 rs1042821 variant homozygotes [adjusted odds

ratio (OR) = 3.42, 95% CI: 1.04‑11.24, p = 0.04, under the co‑dominant model;

adjusted OR = 3.84, 95% CI: 1.18‑12.44, p = 0.03, under the recessive model]. The

association was especially evident for the follicular histotype and female sex. The

association was also apparent when MSH6 was analysed in combination with other

MMR SNPs such as MSH3 rs26279. Interestingly, two other SNP combinations, both

containing the MSH6 heterozygous genotype, were associated with a risk reduction,

suggesting a protective effect for these genotype combinations. These data support the

idea that MMR SNPs such as MSH6 rs1042821, alone or in combination, may

contribute to DTC susceptibility. This is coherent with the limited evidence available.

Nevertheless, further studies are needed to validate these findings and to establish the

usefulness of these SNPs as genetic susceptibility biomarkers for DTC so that, in the

near future, cancer prevention policies may be optimized under a personalized

medicine perspective.

Key words: MSH6, DNA repair, mismatch repair, single nucleotide polymorphism,

genetic susceptibility, thyroid cancer

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Introduction

Despite accounting for only ~2% of all human cancers, thyroid cancer (TC) is the most

common endocrine malignancy. Its incidence continues to rise worldwide, being one of

the cancers with the highest incidence among adolescent and young adults (ages

15‑39 years) and three times more frequent in women than in men (1, 2). TC is usually

classified with respect to histological and clinical criteria: Papillary and follicular TC,

representing 70‑80% and 10‑20% of cases, respectively, are the two most common

varieties. Both tend to grow slowly and are often considered together as

well‑differentiated TC (DTC) (1, 3).

DTC is generally accepted as a multifactorial disease (3). Among the several risk

factors suggested to contribute to DTC, exposure to ionizing radiation (IR) remains the

best‑established one (1, 4). Heritability is high (familial risk is one of the highest among

cancers not showing typical Mendelian inheritance), suggesting that genetic factors

(most likely, multiple common low‑penetrance or rare moderate‑penetrance alleles)

strongly contribute to DTC predisposition (5). Much effort has been made to identify

such susceptibility variants. The most robust evidence is for markers at 9q22.33

(FOXE1), 14q13.3 (NKX2‑1), 2q35 (DIRC3) and 8p12 (NRG1), as variants in these

regions have been repeatedly associated with DTC through several genome‑wide

association studies (GWASs), confirmed in follow‑up studies and independently

replicated across different populations (6-12). Additional markers have recently been

suggested (8, 10-13) but still require confirmation and replication. Overall, the number

of confirmed GWAS‑proposed DTC risk alleles is still very limited (14) and, more

importantly, explains only a relatively small proportion of the estimated heritability of

DTC (11, 15, 16).

Multiple germ‑line single nucleotide polymorphisms (SNPs) within genes involved in

critical cellular processes – e.g., DNA repair, cell‑cycle control and apoptosis,

intracellular signalling, endobiotic or xenobiotic metabolism, thyroid physiology – have

also been associated with DTC susceptibility through candidate‑gene association

studies (CGASs) [reviewed in (5, 17)]. While most of these findings have not been

properly replicated, some could, as recently demonstrated (14), represent true

associations with DTC. The identification of additional variants potentially involved in

DTC susceptibility may explain part of the missing heritability of the disease and is

therefore highly desirable. Considering the important role that DNA‑damaging agents

such as IR play in DTC aetiology, DNA repair SNPs would be particularly interesting

candidates. Many, across the main DNA repair pathways – BER (18, 19), NER (20,

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21), NHEJ (22, 23) and HR (24-26) – have already been associated with DTC. To our

knowledge, DNA mismatch repair (MMR) SNPs have not yet been investigated.

The MMR pathway plays a crucial role in post‑replication repair: It recognizes

base‑base mispairs and insertion/deletion loops that, in spite of the proofreading

function of DNA polymerases, inescapably arise during replication. MMR thus prevents

base substitutions or repeat sequence instability, greatly increasing DNA replication

fidelity and safeguarding genomic integrity (27). MMR also participates, among other

cellular processes (e.g., mitotic and meiotic recombination, immunoglobulin class

switching), in the recognition of DNA damage induced by genotoxic chemicals, UV

light, IR or oxidative stress (e.g., oxidative lesions, double strand breaks, pyrimidine

dimers and inter‑strand crosslinks) and subsequent repair (in cooperation with other

repair pathways) or damage‑induced cytotoxicity (downstream signalling for cell cycle

arrest and apoptosis) (28-30). MMR's role is therefore critical to carcinogenesis: loss of

MMR (e.g., inactivating mutation) greatly increases the rate of spontaneous mutation,

leading to a mutator phenotype, and results in microsatellite instability (MSI), a

hallmark of MMR defects (27, 29, 31). Not surprisingly, heterozygous germline MMR

mutations (e.g., MLH1, MSH2, MSH6 or PMS2) give rise to Lynch syndrome (LS), an

autosomal dominant condition (hereditary nonpolyposis colorectal cancer, HNPCC)

which strongly predisposes to early‑onset colorectal cancer (CRC) and several

extracolonic tumours, all typically presenting MSI. MMR mutations and epigenetic

silencing (e.g., MLH1 promoter methylation) are also being increasingly implicated in a

growing range of tumours (27, 31, 32).

Interestingly, MMR mutations are increasingly being detected in TC cases (33, 34)

[mutation frequency correlating with progression from papillary to more aggressive TC

phenotypes (35)] and TC, despite not being part of the usual LS tumour spectrum, has

been incidentally observed among LS patients (36-40). The notion that MMR deficiency

may contribute to TC pathogenesis and/or progression is biologically plausible since

the MMR pathway is involved in the repair and damage response to IR‑induced lesions

such as 8‑oxoGuanine (29). Supplementary evidence (reviewed in (41) further supports

this hypothesis: 1) MLH1 promoter methylation occurs in TC and is associated with

lymph node metastasis and BRAF mutation; 2) High levels of MSI have been reported

in DTC; and 3) altered MLH1, PMS1 and MSH2 expression has been reported in TC.

As such, it is possible that MMR pathway SNPs, through interference with DNA

damage response and/or repair capacity in thyroid cells, could contribute to DTC

susceptibility. Since this hypothesis has not yet been explored, we undertook a

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hospital‑based case‑control study in a Caucasian Portuguese population, to evaluate

the potential modifying role of a panel of SNPs in MMR genes on the individual

susceptibility to non‑familial DTC. Identifying SNPs which may serve as DTC

susceptibility biomarkers may contribute to the identification of individuals who are at

increased risk for DTC and, eventually, the optimization of cancer prevention

procedures.


Ethical statement

This study was approved by the local ethics committees of the involved institutions and

carried out in compliance with the Helsinki Declaration. At recruitment, written informed

consent was obtained from each study subject and anonymity was guaranteed.

Study subjects

A total of 318 participants, all of which Caucasian Portuguese, were enrolled in this

study: 106 histologically confirmed DTC patients subject to Iodine‑131 treatment in the

Department of Nuclear Medicine of the Portuguese Oncology Institute, Lisbon, Portugal

and 212 age (±2 years) and gender‑matched controls (two for each case), selected

from unrelated subjects who were seeking healthcare for non‑neoplasic pathology at

São Francisco Xavier Hospital, Lisbon, Portugal. For controls, age at diagnosis was

defined as the matched case age of diagnosis. The recruitment of both patients and

controls was based on previously described (21) inclusion and exclusion criteria. At

recruitment, a standard questionnaire was administered through face‑to‑face interviews

by trained interviewers to obtain information on demographic characteristics (e.g.,

gender, age, occupation), family history of cancer, lifestyle habits (e.g., smoking,

alcohol drinking) and IR exposure. According to the information collected, none of the

study participants had been previously exposed to relevant (i.e. other than that from

natural and standard diagnostic sources) levels of ionizing radiation (from therapeutic

or occupational sources, e.g. none of the study participants worked or lived nearby a

nuclear power plant). Detailed clinical and pathological investigation was also

performed. For the purpose of smoking status, former smokers who gave up smoking

either 2 years before DTC diagnosis or 2 years before their inclusion as controls were

considered as non‑smokers. The participation rate was 95% and blood samples were

available for all subjects.

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SNP selection

Using the publicly available NCBI SNP database (http://www.ncbi.nlm.nih.gov/snp/,

accessed February 15, 2017), a comprehensive set of potentially functional SNPs

covering the MMR pathway were selected for genotyping. In order to be eligible, SNPs

had to i) alter the amino acid sequence (missense SNPs); ii) exhibit minor allele

frequency (MAF) greater than 0.10; and iii) have been previously referred to in

MEDLINE (https://www.ncbi.nlm.nih.gov/pubmed/, accessed February 15, 2017). A

total of five SNPs, specifically, rs1799977 (MLH1), rs26279 (MSH3), rs5745325

(MSH4), rs175080 (MLH3) and rs1042821 (MSH6), fulfilled these criteria and were

thus analysed. In addition, since no PMS1 SNP fulfilled all of these criteria, rs5742933

– a common (MAF > 0.10) 5'UTR SNP which is located within the PMS1 promoter

region (potentially regulatory role on transcription) and is the most frequently quoted

PMS1 SNP – was also included in the study. Table 5.1 summarizes the genomic

location, base and amino acid exchange and MAF of the selected SNPs.

Table 5.1 - Selected SNPs and detailed information on the corresponding base and

amino acid exchanges, MAF and TaqMan® assay used for genotyping.

Gene Location dbSNP ID

(rs no.)a

Base

change

Aminoacid

change

MAF

(%)a TaqMan® Assay

MLH1 3p22.2 rs1799977 A → G Ile219Val 13.0 C___1219076_20

MSH3 5q14.1 rs26279 A → G Thr1045Ala 28.0 C____800002_1_

MSH4 1p31.1 rs5745325 G → A Ala97Thr 21.3 C___3286081_10

PMS1 2q32.2 rs5742933 G → C --b 21.9 C__29329633_10

MLH3 14q24.3 rs175080 G → A Pro844Leu 36.4 C___1082805_10

MSH6 2p16.3 rs1042821 C → T Gly39Glu 20.1 C___8760558_10

aaccording to http://www.ncbi.nlm.nih.gov/projects/SNP/ (accessed February 15,

2017). bSNP located on 5’ UTR. MAF, minor allele frequency; SNP, single nucleotide

polymorphism.

DNA extraction and genotyping

After informed consent, peripheral venous blood samples from each study subject were

collected into 10 ml heparinised tubes and stored at ‑80˚C. Genomic DNA was

extracted from these samples by using the commercially available QIAamp® DNA mini

kit (Qiagen GmbH, Hilden, Germany) according to the manufacturer's protocols. DNA

extracts were kept at ‑20˚C until analysis.


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In order to assure uniformity in DNA content (2.5 ng/μl) prior to genotyping, DNA

quantity was assessed fluorimetrically in all samples using the Quant‑iT™ Picogreen®

dsDNA Assay kit (Invitrogen; Thermo Fisher Scientific, Inc., Waltham, MA, USA) and a

Zenyth 3100 plate reader (Anthos Labtec Instruments, Salzburg, Austria).

SNP genotyping was carried out using the Taqman® allelic discrimination assay on a

96‑well ABI 7300 Real Time PCR system (Applied Biosystems; Thermo Fisher

Scientific, Inc.), following the manufacturer's instructions. Commercial pre‑designed

assay primers and probes, purchased from Applied Biosystems; Thermo Fisher

Scientific, Inc., were used for every SNP and are listed in Table 5.1. The amplification

conditions consisted of an initial activation step (10 min, 95˚C), followed by ≥40

amplification cycles of denaturation (15 sec, 92˚C) and annealing/extension (60 sec,

60˚C). The fluorescence intensity emitted by VIC and FAM dyes in each well was

detected (60 sec) and analysed with Applied Biosystems sequence detection software

(System SDS version 1.3.1).

To assure accuracy of the genotyping and avoid variant misclassification, four negative

controls (wells containing no DNA) were included in each plate. Genotyping of

inconclusive samples was repeated. Also, for quality control, 10‑15% of the samples

were randomly selected and run in duplicates. 100% concordance between

experiments was observed.


Prior to analysis, an exact probability test available in SNPStats software (42) was

used to check whether genotype distributions for each studied SNP deviated

significantly from Hardy‑Weinberg equilibrium (HWE).

Since all variables considered were categorical or categorized (e.g., age), descriptive

statistics were presented as frequencies and percentages.

The distribution of demographic variables such as gender, age group and smoking

status and of genotype frequencies was compared between groups through Chi‑square

or two‑sided Fisher's exact test for 2x2 or 2x3 contingency tables, respectively.

For all elected SNPs, genotype‑associated risk of DTC was estimated by binary logistic

regression analysis and expressed as both crude and adjusted odds ratios (OR) and

95% confidence intervals (CI). Risk estimates were calculated under codominant,

dominant, recessive and log‑additive genetic models. Adjustment, when performed,

included terms for gender (male/female), age group (<30, 30‑49, 50‑69 and ≥70 years)

and smoking habits (smokers/non‑smokers). The most common homozygous

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genotype, female gender, lower age group and non‑smoking status were taken as

reference for the purpose of such calculations. The remaining information that was

collected on demographic characteristics (e.g. occupation), family history of cancer,

lifestyle habits (e.g. alcohol drinking) and prior IR exposure was not suitable for

rigorous quantitative transformation and, therefore, not included in the adjustment.

Stratified analysis according to histological type of tumour (papillary or follicular TC),

gender and age was also performed. Additionally, we conducted a genotype interaction

analysis (combination of alleles) in order to investigate the combined effect of different

pairs of SNPs on DTC risk. All possible combinations were analysed. For each pair of

SNPs, the combination of the most common homozygous genotypes of each individual

SNP was taken as the reference category. Paired genotypes with frequency <5% in the

control group were pooled together.

Finally, the chromosomic location of the variants included in this study was compared

to that of DTC markers previously reported in GWAS. Linkage disequilibrium (LD)

between co‑localized variants in European populations was verified in silico through the

use of LDLink (43), a publicly available web‑based application that uses Phase 3

haplotype data from the 1,000 Genomes Project to calculate pairwise LD between

user‑input variants in different population groups.

This was a ‘proof of concept’ study to ascertain whether MMR variants might be linked

to DTC. Bonferroni adjustment was not used because it is too conservative. Also, the

complement of the false negative rate β to compute the power of a test (1‑β) was not

taken into account at this stage since further studies with more patients and controls

should be undertaken to change over this preliminary study into a confirmatory positive

one.

The statistical analysis was done with SPSS 22.0 (IBM SPSS Statistics for Windows,

version 22.0; IBM Corp, Armonk, NY, USA) except for HWE deviation assessment,

MAF calculations, haplotype estimation and linkage disequilibrium (LD) analysis which

were performed using the SNPstats Software (42). Two‑tailed p < 0.05 was considered

to indicate a statistically significant difference.

Results

The demographic characteristics of the 106 DTC cases and their 212 age and

gender‑matched controls are depicted in Table 5.2. The mean age for each group was

52 years (range 19‑77 in the patient group and 18‑77 in the control group). Female

patients significantly outnumbered male patients, in accordance with the worldwide

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estimation for gender distribution in DTC (1, 2). A total of 11.3% of patients were

categorized as smokers. No statistically significant difference between groups was

observed concerning age distribution, gender and smoking habits. Regarding DTC

histological classification, 78 (73.6%) patients were diagnosed as of the papillary type,

while 28 (26.4%) were diagnosed as of the follicular type. All cancer patients were

incident cases and none of the controls had a family history of cancer.

Table 5.2 - General characteristics for the DTC case (n = 106) and control (n = 212)

populations.

Characteristics Controls n (%) Cases n (%) p-valuec

Gender

Male 31 (14.6) 16 (15.1)

1.00

Female 181 (85.4) 90 (84.9)

Agea,b

<30 10 (4.7) 4 (3.8)

0.98 30-49 75 (35.4) 38 (35.8)

50-69 98 (46.2) 49 (46.2)

70 29 (13.7) 15 (14.2)

Smoking habits

Non-smokers 174 (82.1) 94 (88.7)

0.19 Smokers 36 (17.0) 12 (11.3)

Missing 2 (0.9) 0 (0.0)

aAge of diagnosis, for cases. bAge at the time of diagnosis of the matched case, for

controls. cp-value for cases vs. control group determined by two-sided Fisher’s exact

test (gender, smoking habits) or χ2 test (age). DTC, well-differentiated thyroid cancer.

Table 5.3 summarizes the results for MAF, genotypic frequencies and crude/adjusted

ORs of the six MMR pathway SNPs selected in our study. The genotype distributions of

the studied SNPs were in HWE (p ≥ 0.05), in both case and control groups. No relevant

LD was observed between the studied SNPs (data not shown). When comparing, for

each of the studied SNPs, the genotype frequency distribution between cases and

controls, a significant difference was observed only for MSH6 rs1042821 (p = 0.04, on

the codominant and recessive models). Statistical significance was not attained when

assuming a dominant model of inheritance (p = 0.54). No additional significant

differences were found, irrespective of the model of inheritance assumed. When

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performing logistic regression analysis, a significant DTC risk increase was observed in

MSH6 rs1042821 variant allele homozygotes, after adjustment for age, gender and

smoking status (Glu/Glu vs. Gly/Gly: adjusted OR = 3.42, 95% CI: 1.04‑11.24, p = 0.04;

Glu/Glu vs. Gly/Gly+Gly/Glu: adjusted OR = 3.84, 95% CI: 1.18‑12.44, p = 0.03). This

association was also apparent without covariate adjustment when assuming a

recessive model of inheritance (Glu/Glu vs. Gly/Gly+Gly/Glu: OR = 3.35, 95% CI:

1.07‑10.50, p = 0.04). No significant associations with DTC risk were observed for the

remaining SNPs analysed in this study, irrespective of the model assumed.

118

Table 5.3 - Genotype distribution in case (n = 106) and control (n = 212) populations and associated DTC risk (crude and adjusted ORs).

Genotype MAF Genotype frequency p-valuea OR (95% CI) Adjusted OR (95% CI)b

Controls Cases Controls n (%) Cases n (%)

MLH1 rs1799977 212 (100) 105 (100)

Ile/Ile G: 0.34 G: 0.30 93 (43.9) 48 (45.7)

0.42

1 (Reference)d 1 (Reference)d

Ile/Val 95 (44.8) 50 (47.6) 1.02 (0.63-1.66) 1.02 (0.62-1.68)

Val/Val 24 (11.3) 7 (6.7) 0.57 (0.23-1.41) 0.56 (0.22-1.40)

Dominant model 119 (56.1) 57 (54.3) 0.81 0.93 (0.58-1.49) 0.93 (0.58-1.50)

Recessive model 24 (11.3) 7 (6.7) 0.23 0.56 (0.23-1.34) 0.55 (0.23-1.34)

Log-additive model -- -- -- 0.86 (0.59-1.23) 0.85 (0.59-1.24)

MSH3 rs26279 211 (100) 105 (100)

Thr/Thr G: 0.35 G: 0.33 93 (44.1) 48 (45.7)

0.89


Thr/Ala 90 (42.7) 45 (42.9) 0.97 (0.59-1.60) 0.94 (0.57-1.56)

Ala/Ala 28 (13.3) 12 (11.4) 0.83 (0.39-1.78) 0.80 (0.37-1.72)

Dominant model 118 (55.9) 57 (54.3) 0.81 0.94 (0.59-1.50) 0.91 (0.56-1.46)

Recessive model 28 (13.3) 12 (11.4) 0.72 0.84 (0.41-1.73) 0.82 (0.40-1.70)


MSH4 rs5745325 212 (100) 106 (100)

Ala/Ala A: 0.33 A: 0.27 97 (45.8) 57 (53.8)

0.38


Ala/Thr 91 (42.9) 40 (37.7) 0.75 (0.46-1.23) 0.75 (0.45-1.23)

Thr/Thr 24 (11.3) 9 (8.5) 0.64 (0.28-1.47) 0.64 (0.28-1.48)

119

Dominant model 115 (54.2) 49 (46.2) 0.19 0.73 (0.45-1.16) 0.72 (0.45-1.16)

Recessive model 24 (11.3) 9 (8.5) 0.56 0.73 (0.33-1.63) 0.72 (0.32-1.63)


PMS1 rs5742933 212 (100) 104 (100)

G/G C: 0.18 C: 0.17 144 (67.9) 73 (70.2)

0.90


G/C 58 (27.4) 27 (26.0) 0.92 (0.54-1.57) 0.88 (0.51-1.51)

C/C 10 (4.7) 4 (3.8) 0.79 (0.24-2.60) 0.76 (0.23-2.60)

Dominant model 68 (32.1) 31 (29.8) 0.70 0.90 (0.54-1.50) 0.86 (0.51-1.45)

Recessive model 10 (4.7) 4 (3.8) 1.00 0.81 (0.25-2.64) 0.80 (0.24-2.67)


MLH3 rs175080 212 (100) 106 (100)

Pro/Pro A: 0.46 A: 0.51 60 (28.3) 22 (20.8)

0.34


Pro/Leu 109 (51.4) 59 (55.7) 1.48 (0.83-2.64) 1.50 (0.83-2.71)

Leu/Leu 43 (20.3) 25 (23.6) 1.59 (0.79-3.17) 1.60 (0.79-3.22)

Dominant model 152 (71.7) 84 (79.2) 0.17 1.51 (0.86-2.63) 1.53 (0.87-2.69)

Recessive model 43 (20.3) 25 (23.6) 0.56 1.21 (0.69-2.12) 1.21 (0.69-2.12)


MSH6 rs1042821 210 (100) 106 (100)

Gly/Gly T: 0.21 T: 0.22 127 (60.5) 68 (64.2)

0.04c


Gly/Glu 78 (37.1) 30 (28.3) 0.72 (0.43-1.20) 0.73 (0.43-1.23)

Glu/Glu 5 (2.4) 8 (7.5) 2.99 (0.94-9.49) 3.42 (1.04-11.24)c

120

Dominant model 83 (39.5) 38 (35.8) 0.54 0.86 (0.53-1.39) 0.87 (0.54-1.43)

Recessive model 5 (2.4) 8 (7.5) 0.04c 3.35 (1.07-10.50)c 3.84 (1.18-12.44)c


ap-value for cases vs. control group determined by two-sided Fisher’s exact test (whenever 2x2 contingency tables are possible) or χ2 test

(remaining cases). bORs were adjusted for gender (male and female), age (<30, 30-49, 50-69, ≥70 years) and smoking status (non-

smoker and smoker). cSignificant results (p<0.05) highlighted in bold. dThe reference comparator for OR calculations. DTC, well-

differentiated thyroid cancer; MAF, minor allele frequency; OR, odds ratio; CI, confidence interval.

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Since DTC comprises two distinct histological types (papillary and follicular), affects

women more than men and is the most incident malignancy in the 15‑39 years age

group (1, 2), patients and controls were stratified on the basis of these criteria, i.e.,

histological tumour type, gender and age, in order to identify any subgroup‑specific risk

association. As shown in Table 5.4, stratification of subjects according to histological

criteria showed that the association between the homozygous variant genotype of

MSH6 rs1042821 and DTC risk, observed in the complete set of patients, was also

present in the follicular subset (adjusted OR = 20.98, 95% CI: 1.08‑406.53, p = 0.04,

under the co‑dominant model; adjusted OR = 23.70, 95% CI: 1.25‑449.32, p = 0.04,

under the recessive model) but absent from the papillary subset, suggesting a

histological type‑specific SNP effect. Also in the follicular subset, a significant

difference in the genotype frequency distribution of MLH3 rs175080 was observed (p =

0.04, in the dominant model, data not shown). On binary logistic regression analysis,

significantly increased follicular TC risk was observed in MLH3 rs175080 variant allele

carriers (OR = 3.95, 95% CI: 1.05‑14.81, p = 0.04). After gender stratification (Table

5.4), the frequency distribution of MSH6 rs1042821 genotypes differed significantly

between female DTC patients and their age and gender‑matched controls (p = 0.02, in

the codominant model, data not shown). Also, as depicted in Table 5.4, the

homozygous variant genotype of this SNP was found to confer increased DTC risk in

females only, under both the co‑dominant (OR = 4.42, 95% CI: 1.10‑17.75, p = 0.04

and adjusted OR = 4.78, 95% CI: 1.17‑19.56, p = 0.03) and the recessive model (OR =

5.00, 95% CI: 1.26‑19.84, p = 0.02 and adjusted OR = 5.42, 95% CI: 1.34‑21.92, p =

0.02), supporting the idea that this polymorphism might influence DTC susceptibility,

particularly in women. The study population was also stratified according to the age of

diagnosis (Table 5.4). In order to avoid excessively low numbers in each strata, only

two groups were formed: <50 and ≥50 years. In the elderly group (≥50 years), a highly

significant difference in the frequency distribution of MSH6 rs1042821 genotypes was

observed between DTC patients and the corresponding controls (p = 0.001 in the

codominant model, data not shown). Unfortunately, no MSH6 rs1042821 homozygous

variant individuals ≥50 years were observed in the control group, limiting OR

calculations and subsequent analysis for this SNP. Further analysis of our study

subjects after histological type, gender and age stratification revealed no other

significant correlations between the analysed SNPs and DTC risk.

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Table 5.4 - Genotype distribution in the case population (n = 106) and associated DTC risk (crude and adjusted ORs), after stratification

according to histological type, gender and age.a

A, Histological type

Genotype

Papillary Carcinoma Follicular Carcinoma

n (%) OR (95% CI) Adjusted OR (95% CI)b n (%) OR (95% CI) Adjusted OR (95% CI)b

MSH6 rs1042821 78 (100) 28 (100)

Gly/Gly 49 (62.8) 1 (reference)e 1 (reference)e 19 (67.9) 1 (reference)e 1 (reference)e

Gly/Glu 24 (30.8) 0.74 (0.41-1.32) 0.74 (0.41-1.35) 6 (21.4) 0.65 (0.22-1.91) 0.76 (0.24-2.35)

Glu/Glu 5 (6.4) 2.30 (0.59-8.95) 2.47 (0.61-9.89) 3 (10.7) 5.84 (0.57-60.03) 20.98 (1.08-406.53)c

Dominant model 29 (37.2) 0.83 (0.48-1.46) 0.85 (0.48-1.49) 9 (32.1) 0.92 (0.35-2.43) 1.10 (0.39-3.07)

Recessive model 5 (6.4) 2.57 (0.67-9.85) 2.74 (0.69-10.84) 3 (10.7) 6.60 (0.65-66.63) 23.70 (1.25-449.32)c

Log-additive model -- 0.98 (0.61-1.59) 1.00 (0.62-1.62) -- 1.24 (0.57-2.68) 1.58 (0.66-3.75)

MLH3 rs175080 78 (100) 28 (100)

Pro/Pro 19 (24.4) 1 (reference)e 1 (reference)e 3 (10.7) 1 (reference)e 1 (reference)e

Pro/Leu 42 (53.8) 1.13 (0.59-2.19) 1.17 (0.60-2.27) 17 (60.7) 3.78 (0.97-14.79) 3.61 (0.88-14.85)

Leu/Leu 17 (21.8) 1.17 (0.53-2.61) 1.20 (0.54-2.68) 8 (28.6) 4.36 (0.95-20.04) 4.29 (0.89-20.78)

Dominant model 59 (75.6) 1.14 (0.61-2.14) 1.18 (0.62-2.22) 25 (89.3) 3.95 (1.05-14.81)c 3.81 (0.97-14.95)

Recessive model 17 (21.8) 1.08 (0.56-2.10) 1.08 (0.56-2.10) 8 (28.6) 1.64 (0.57-4.69) 1.67 (0.55-5.02)


B, Gender

Genotype Male Female

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MSH6 rs1042821 16 (100) 90 (100)


Gly/Glu 4 (25.0) 0.86 (0.21-3.54) 0.96 (0.20-4.52) 26 (28.9) 0.70 (0.41-1.22) 0.70 (0.40-1.22)

Glu/Glu 1 (6.3) 0.86 (0.07-10.66) 1.08 (0.07-16.53) 7 (7.8) 4.42 (1.10-17.75)c 4.78 (1.17-19.56)c

Dominant model 5 (31.3) 0.86 (0.23-3.19) 0.98 (0.23-4.24) 33 (36.7) 0.86 (0.51-1.44) 0.86 (0.51-1.45)

Recessive model 1 (6.3) 0.90 (0.08-10.77) 1.09 (0.08-15.61) 7 (7.8) 5.00 (1.26-19.84)c 5.42 (1.34-21.92)c


C, Age

Genotype

<50 years ≥50 years


MSH6 rs1042821 42 (100) 64 (100)


Gly/Glu 12 (28.6) 0.56 (0.25-1.27) 0.56 (0.25-1.26) 18 (28.1) 0.84 (0.43-1.64) 0.86 (0.44-1.70)

Glu/Glu 1 (2.4) 0.31 (0.03-2.79) 0.32 (0.04-2.93) 7 (10.9) --d --d

Dominant model 13 (31.0) 0.53 (0.24-1.16) 0.53 (0.24-1.17) 25 (39.1) 1.17 (0.63-2.17) 1.21 (0.64-2.27)

Recessive model 1 (2.4) 0.38 (0.04-3.37) 0.40 (0.04-3.58) 7 (10.9) --d --d


aOnly SNPs presenting significant findings are shown. bORs were adjusted for gender (male and female), age (<30, 30-49, 50-69, and ≥70

years), and smoking status (non-smoker and smoker). cSignificant results (p < 0.05) highlighted in bold. dGenotype not found in the

corresponding controls. eThe reference comparator for OR calculations. DTC, well-differentiated thyroid cancer; SNP, single nucleotide

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polymorphism; OR, odds ratio; CI, confidence interval.

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Proteins that participate in a common DNA repair pathway functionally interact with

each other, establishing ground for additive or even multiplicative effects of different

SNPs of the same pathway on DNA repair activity and, hence, cancer risk. This has

been previously demonstrated for other DNA repair pathways (16, 44, 45) and, most

likely, also applies to MMR, justifying the usefulness of assessing the effect of

combined genotypes on DTC risk. As detailed in Table 5.5, the combined genotype

distribution of the MSH6 rs1042821‑MLH3 rs175080 SNP pair was significantly

different in cases and controls (p = 0.032). On logistic regression analysis, when MSH6

rs1042821 and MSH3 rs26279 were considered together, a significantly increased risk

was observed in the pooled group of MSH6 rs1042821 variant allele homozygotes,

despite only after adjusting for gender, age and smoking status (adjusted OR = 3.81,

95% CI: 1.11‑13.13, p = 0.03). Interestingly, two other MSH6 rs1042821 genotype

combinations, all involving the rs1042821 heterozygous genotype, yielded significant

results in the opposite direction: a significantly decreased risk was detected in

combined MSH6 rs1042821‑MSH4 rs5745325 heterozygotes (OR = 0.34, 95% CI:

0.14‑0.87, p = 0.02 and adjusted OR = 0.35, 95% CI: 0.14‑0.88, p = 0.03), as well as in

individuals simultaneously heterozygous for MSH6 rs1042821 and homozygous for the

common allele of MLH3 rs175080 (OR = 0.13, 95% CI: 0.03‑0.61, p = 0.01 and

adjusted OR = 0.11, 95% CI: 0.02‑0.53, p = 0.01). None of the remaining genotype

combinations showed association with disease (data not shown).

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Table 5.5 – Two-way SNP interactions: distribution of combined genotypes in the case (n = 106) and control (n = 212) populations and

associated DTC risk (crude and adjusted ORs).a

Genotype Genotype frequency DTC risk

Controls n

(%)

Cases n

(%)

p-

valueb

OR (95% CI) p-

valueb

Adjusted OR (95% CI)c p-

valueb

MSH6 rs1042821 – MSH3 rs26279 209 (100) 105 (100) 0.167

Gly/Gly – Thr/Thr 59 (28.2) 29 (27.6) 1 (reference)e 1 (reference)e

Gly/Gly – Thr/Ala 56 (26.8) 32 (30.5) 1.16 (0.62-2.16) 0.64 1.18 (0.63-2.20) 0.62

Gly/Glu – Thr/Thr 31 (14.8) 16 (15.2) 1.05 (0.50-2.22) 0.90 1.14 (0.53-2.43) 0.74

Gly/Glu – Thr/Ala 33 (15.8) 10 (9.5) 0.62 (0.27-1.42) 0.26 0.60 (0.26-1.39) 0.23

Gly/Gly – Ala/Ala 11 (5.3) 7 (6.7) 1.30 (0.46-3.69) 0.63 1.26 (0.44-3.62) 0.67

Glu/Glu – Thr/Thr

Glu/Glu – Thr/Ala

Glu/Glu – Ala/Ala

5 (2.4) 8 (7.6) 3.26 (0.98-10.84) 0.05 3.81 (1.11-13.13)d 0.03d

Gly/Glu – Ala/Ala 14 (6.7) 3 (2.9) 0.44 (0.12-1.64) 0.22 0.42 (0.11-1.59) 0.20

MLH3 rs175080 – MSH6 rs1042821 210 (100) 106 (100) 0.032d

Pro/Pro – Gly/Gly 32 (15.2) 19 (17.9) 1 (reference)e 1 (reference)e

Pro/Pro – Gly/Glu 26 (12.4) 2 (1.9) 0.13 (0.03-0.61)d 0.01d 0.11 (0.02-0.53)d 0.01d

Pro/Leu – Gly/Gly 71 (33.8) 36 (34.0) 0.85 (0.43-1.71) 0.66 0.81 (0.40-1.65) 0.56

Pro/Leu – Gly/Glu 35 (16.7) 19 (17.9) 0.91 (0.41-2.03) 0.83 0.94 (0.41-2.13) 0.88

Pro/Pro – Glu/Glu 5 (2.4) 8 (7.5) 2.70 (0.77-9.44) 0.12 3.09 (0.85-11.27) 0.09

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Pro/Leu – Glu/Glu

Leu/Leu – Glu/Glu

Leu/Leu – Gly/Gly 24 (11.4) 13 (12.3) 0.91 (0.38-2.20) 0.84 0.83 (0.34-2.03) 0.68

Leu/Leu – Gly/Glu 17 (8.1) 9 (8.5) 0.89 (0.33-2.39) 0.82 0.89 (0.33-2.43) 0.82

MSH4 rs5745325 – MSH6 rs1042821 210 (100) 106 (100) 0.149

Ala/Ala – Gly/Gly 53 (25.2) 36 (34.0) 1 (reference)e 1 (reference)e

Ala/Ala – Gly/Glu 41 (19.5) 20 (18.9) 0.72 (0.36-1.42) 0.34 0.74 (0.37-1.47) 0.39

Ala/Thr – Gly/Gly 59 (28.1) 26 (24.5) 0.65 (0.35-1.21) 0.18 0.66 (0.35-1.23) 0.19

Ala/Thr – Gly/Glu 30 (14.3) 7 (6.6) 0.34 (0.14-0.87)d 0.02d 0.35 (0.14-0.88)d 0.03d

Ala/Ala – Glu/Glu

Ala/Thr – Glu/Glu

Thr/Thr – Gly/Glu

Thr/Thr – Glu/Glu

12 (5.7) 11 (10.4) 1.35 (0.54-3.39) 0.52 1.43 (0.56-3.66) 0.45

Thr/Thr – Gly/Gly 15 (7.1) 6 (5.7) 0.59 (0.21-1.66) 0.32 0.60 (0.21-1.70) 0.33

aOnly combined genotypes presenting significant findings are shown. bp-value for cases vs. control group determined by two-sided Fisher’s

exact test (whenever 2x2 contingency tables are possible) or χ2 test (remaining cases). cORs were adjusted for gender (male and female), age

(<30, 30-49, 50-69, ≥70 years) and smoking status (non-smoker and smoker). dSignificant results (p < 0.05) highlighted in bold. eThe reference

comparator for OR calculations. DTC, well-differentiated thyroid cancer; SNP, single nucleotide polymorphism; OR, odds ratio; CI, confidence

interval.

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Finally, since MSH3 and MLH3 (whose studied variants yielded significant associations

on SNP pair analysis) are located in the same chromosomic region that DTC markers

reported in prior GWAS (rs13184587 at 5q14.1 and rs10136427 at 14q24.3,

respectively) (13), we used LDLink (43) to verify in silico any potential linkage

disequilibrium relation between these MMR variants and the GWAS‑suggested

markers co‑localized in the same chromosomic region. No linkage disequilibrium was

observed between either MSH3 rs26279 and rs13184587 or MLH3 rs175080 and

rs10136427 in European populations (data not shown).

Discussion

To our knowledge, this was the first study evaluating the potential role of MMR SNPs

on DTC susceptibility in Caucasian populations.

We observed a significantly increased DTC risk in MSH6 rs1042821 variant allele

homozygotes (Glu/Glu). MSH6 rs1042821 is probably one of the most studied SNPs of

the MMR pathway and its potential association with cancer (other than TC) has

previously been addressed, with inconsistent results: rs1042821 has been associated

with increased CRC risk (46, 47), as well as with triple negative breast cancer (TNBC)

(48) and highly malignant bladder cancer (49). Contrasting results have been reported

for hepatocellular (50), colorectal (51) and pancreatic cancer (52). Most studies,

however, present inconclusive findings (53-57), including a recent meta‑analysis (58)

aggregating data from many of the above‑quoted studies. It is possible that organ and

population‑specific characteristics (e.g., genetic background and environmental

exposure) may have contributed to such diverse observations. More recently,

rs1042821 has also been detected through sequencing techniques in several cancer

cases (59-61) but, considering the high population frequency of this SNP, this could be

merely coincidental.

The involvement of MSH6 SNPs in cancer susceptibility (DTC, in particular) is

expected for three fundamental reasons. Firstly, because it is biologically plausible:

MSH6 integrates the MutSα complex, a sensor of genetic damage that, besides its role

in the repair of replication errors, cooperates with other DNA repair and

damage‑response signalling pathways to allow for cell cycle arrest, DNA repair and/or

apoptosis of genetically damaged cells. Of importance for DTC susceptibility, MutSα

ensures accurate homologous recombination repair of double strand breaks and

cooperates with MUTYH in the repair of 8‑oxoGuanine [reviewed in (27-29)], lesions

that commonly arise from IR exposure, the most well‑known DTC risk factor. Secondly,

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because of the functional impact of MSH6 mutations: Experimental studies in

MSH6‑deficient yeast, mice or human cells demonstrate that MSH6 mutations results

in partial MMR deficiency (mild mutator phenotype, characterized by weak

microsatellite instability, MSI‑L) and increased cancer susceptibility in animal models

(27). And finally because, in the clinical context, MSH6 mutations are associated with

cancer syndromes (and TC, possibly): Inherited MSH6 germline mutations are

responsible for 7‑10% of LS cases, patients presenting an atypical phenotype (lower

CRC incidence – with later onset – high incidence of endometrial cancer and lower

degree or absence of MSI), compared to the more frequent MSH2 and MLH1‑mutant

LS cases (27, 31, 39, 62). TC – despite not part of the usual LS spectrum – has been

sporadically observed in LS patients harbouring MSH2 and MLH1 mutations (36, 38-

40) and, more recently, also in a MSH6‑mutant LS case (37). MSH6 mutations were

also recently observed in both anaplastic (33) and papillary TC (34). In the latter study,

MSH6 was even the most frequently mutated gene and two of these mutations

(Gly355Ser and Ala36Val) were coincidental in family‑related patients, suggesting a

causative association. For all of the above, it is likely that MSH6 genetic variation

contributes to TC development.

The rs1042821 SNP is a common missense variant that involves the substitution

116G>A in exon 1 of the MSH6 gene. It results in the substitution of glutamic acid for

glycine at position 39 (Gly39Glu) of the MSH6 N‑terminal region (NTR), a highly

disordered domain upstream of the mismatch binding domain. The importance of the

MSH6 NTR is being increasingly recognized as missense mutations in this region have

been associated with cancer [an exhaustive list of LS‑associated mutations is available

in the InSiGHT database (32)]. Interestingly, the MSH6 NTR is absent from prokaryotic

MutS which, coincidentally, does not share some of the functions of eukaryotic MutSα

(e.g., activation of apoptosis) (63), suggesting a critical role for this region in such

processes. As extensively reviewed in Edelbrock et al (28), several sequence motifs in

the NTR may be of relevance to the multitude of actions performed by MSH6,

including: 1) a short, conserved PCNA interacting protein (PIP) motif, located near the

N‑terminal extreme, that allows PCNA binding; 2) a PWWP sequence motif, distal to

the PIP box, that mediates interactions with chromatin and chromatin‑associating

proteins; 3) a conserved motif near the NTR C‑terminus, rich in positively charged

amino acids that (through electrostatic attraction) contributes to nonspecific DNA

binding and stabilizes the MutSα‑DNA interaction (possibly modulating the residence

time of MutSα at the lesion site); 4) nuclear localization sequences (NLSs, e.g., a

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conserved Ser‑Pro‑Ser sequence – amino acids 41‑43 – containing phosphorylated

serines), that may contribute to the nuclear import of MutSα; and 5) multiple

phosphorylation sites (19 out of the 23 identified in MSH6, according to the updated list

at http://www.uniprot.org/uniprot/P52701), that may be involved in the post‑translational

regulation of MutSα stability, nuclear import and differential downstream signalling for

MMR and DNA damage response. The NTR may also be responsible for other protein

interactions.

Functional assays are needed to confirm if the MSH6 rs1042821 variant affects the

function of MutSα. However, given its location – in the MSH6 NTR, near a NLS

containing two phosphorylation sites (Ser41 and Ser43) – it is possible that rs1042821

interferes with phosphorylation of these residues (both MAPK recognition motifs) and

hence with the post‑translational regulation of MutSα stability, nuclear import or activity

(28). The rs1042821 SNP may also interfere with non‑specific DNA binding since

glutamate, contrasting with glycine, is negatively charged at physiological pH. This may

hamper electrostatic attraction to the phosphate backbone of DNA, interfere with the

stability of the MutSα‑DNA interaction and hence decrease the residence time of

MutSα at the lesion site [previously suggested to play a role in the differential

regulation of the DNA repair and apoptosis signalling roles of MSH6 (63)]. In fact,

increasing number of negatively charged glutamate residues within the amino acid

231‑289 NTR segment of the yeast Msh6 increases mutation rates in these cells (64)

and substitutions of glutamic acid for glycine, in general, can determine the formation of

sterically different helical structures, polypeptide folding, and intrinsic aggregation (51).

Whether this applies to MSH6 rs1042821 remains to be established.

In our study, upon stratification, the association between the MSH6 rs1042821

homozygous variant genotype and increased DTC risk was especially evident for the

follicular histotype, female sex and, possibly, older age (≥50 years). Concerning the

histological type of tumour, this contrasts with prior evidence: rs1042821 has been

associated with the development of BRAF mutated (Val600Glu) colon tumours (54) –

only in microsatellite stable (MSS), not MSI tumours – and the Val600Glu BRAF

mutation is a hallmark of papillary, not follicular TC (3). However, as in our study, this

observation resulted from stratification analysis with only a limited number of subjects

in each strata [n = 3 for follicular TC cases with Glu/Glu genotype in our study; n = 4 for

BRAF mutated, MSS tumours with Glu/Glu genotype in (54)]. Either observation could

therefore be due to chance (type I statistical error), hampering solid conclusions.

Further studies with a larger sample size are needed to clarify the relationship, if any,

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between rs1042821 and DTC histological type. The genotype‑disease association was

stronger among women, an expected finding since DTC affects women more than men

(1, 2), differential incidence starting with the onset of puberty and declining after

menopause (65). Also, TC rates in women with breast cancer history (and vice‑versa)

are higher than expected (66), suggesting some common ground between these

conditions. Oestrogen could be the ‘missing link’: Besides its well‑established role in

the pathogenesis of several endocrine‑related cancers (e.g., breast, endometrial,

ovarian) (67), oestrogen may promote the growth of TC cells and thus contribute to

development and progression of DTC, through increased transcription of

ERE‑containing genes, activation of the MAPK and PI3K signalling pathways,

modulation of the TC microenvironment or specific effects on thyroid stem and

progenitor cells (65). Oestrogen has also been suggested to give rise to

cancer‑initiating mutations through the formation of DNA adducts and other oxidative

lesions, high levels of which have been observed in women with breast, thyroid or

ovarian cancer (68). On the other hand, MSH6 is increasingly being implicated in such

oestrogen‑associated cancers as 1) in vitro oestrogen exposure after

catechol‑O‑methyltransferase inhibition increases the levels of 8‑oxo‑dG (69), an

oxidative DNA lesion whose repair involves the MutSα complex; 2) MSH6 mutations

and reduced MSH6 mRNA expression have been reported in breast cancer patients

and breast tumour derived cell lines, respectively (70); 3) in LS patients, endometrial

cancer is commonly associated with MSH6 mutations (27, 31, 39, 62); 4) MSH2 – the

binding partner of MSH6 in MutSα – is able to transactivate the oestrogen receptor α,

through its MSH6 interaction domain (71); 5) several DNA repair SNPs have been

associated with increased oestrogen sensitivity in the development of breast cancer

(72-74). Also, we previously reported a non‑significant breast cancer risk increase in

rs1042821 variant allele homozygotes (53), in line with the results reported here.

Overall, if oestrogen indeed contributes to DTC and MSH6 is indeed involved in

oestrogen‑associated cancers, it is only logical that a putative association between

rs1042821 and DTC susceptibility is particularly visible in women. Finally, in the current

study, considering only individuals of age ≥50 years, the rs1042821 homozygous

variant genotype was detected only in DTC patients, not in controls. This may suggest

that rs1042821 is associated with DTC susceptibility particularly among older

individuals. This is compatible with the observation of later onset cancer in LS patients

harbouring MSH6 mutations (27, 31, 39). Also, in line with our results, rs1042821 has

been associated with increased breast cancer risk in women of age >60 years and

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decreased risk in women of age ≤60 years (57). Finally, MSH6 has been demonstrated

to be markedly downregulated in senescent cells (75), suggesting that MutSα activity

decreases during the aging process. Since our results were based on stratified

analysis, further studies are required to confirm this finding.

On paired SNP analysis, several associations were observed in our study. Most of

these involve MSH6 rs1042821, possibly reflecting an individual SNP effect. However –

since MMR proteins functionally interact within the same pathway – an additive (or

even multiplicative) effect with other MMR SNPs is possible. Supporting this

hypothesis, several studies have shown that, although individual susceptibility alleles

may have only a modest effect, DTC risk may be substantially increased when multiple

risk variants are considered together (15, 16). Considering the strong genetic

component of DTC susceptibility, such a role for gene‑gene interactions is likely (16).

One SNP combination comprising the MSH6 rs1042821 homozygous variant genotype

was associated with increased DTC risk, as expected from single SNP analysis.

Interestingly, two other SNP pairs containing the MSH6 heterozygous genotype were

associated with a risk reduction. A similar non‑significant trend was already evident on

single SNP analysis, suggesting a protective effect for the MSH6 rs1042821

heterozygous genotype. Prior evidence supports this hypothesis: We previously

reported a breast cancer risk reduction in combined MSH6 rs1042821

heterozygotes/MSH3 rs26279 common allele homozygotes (53).

Other studies (50-53, 57), including a recent meta‑analysis by Li et al (58), detected a

cancer risk reduction in MSH6 rs1042821 heterozygotes or variant allele carriers. It

should be noted that these observations in variant allele carriers do not contradict our

prior suggestion of risk increase in variant homozygotes: considering, as stated above,

i) the dual role of MSH6 on DNA repair and apoptosis; ii) the likely involvement of the

MSH6 NTR in the differential regulation of such functions; and iii) the location and

potential impact of rs1042821, it is possible that this SNP has distinct effects on each

of MSH6 functions (DNA repair or apoptosis signalling) critically impairing one but

somehow favouring the other. If so, variant allele homozygotes – lacking the common

form of MSH6 – could have higher cancer risk, while the presence of both forms in

heterozygotes could be of some benefit. Further studies are required to confirm this

hypothesis. Furthermore, it is interesting to note that two out of the three SNP pairs

significantly associated with DTC susceptibility in our study involve variants that are

located in the exact same chromosomic region of previously GWAS‑suggested DTC

markers. According to our in silico analysis, no linkage disequilibrium was identified

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between these co‑localized variants in European populations. However, since it was

not possible to verify this hypothesis with experimental data from our study, we cannot

exclude the possibility that some of the variants analysed are indeed in linkage

disequilibrium with previously suggested DTC markers, in the Portuguese population.

In conclusion, the rapidly increasing incidence of DTC (1) has prompted research on

the genetic predisposing factors of this disease. Recently performed GWAS (6-12)

have provided valuable contribution but, even so, explain only part of the estimated

heritability of DTC (11, 15, 16). Several reasons may contribute: it is possible that the

highly stringent criteria applied to GWAS to prevent false‑positive findings result in the

exclusion of SNPs truly associated with DTC risk (14). Furthermore, evidence from the

latest GWAS (10-13) suggests the existence of population‑specific DTC risk alleles,

raising the possibility that novel cancer susceptibility markers, specific for

geographically distinct populations, may remain to be identified. Finally, gene‑gene and

gene‑environment interactions, despite seldom addressed, may also play an important

role and explain part of the unresolved heritability of DTC susceptibility (15, 16). The

identification of additional common variants, gene‑environment and gene‑gene

interactions predisposing to DTC may thus unveil at least part of the unexplained

genetic component of DTC susceptibility. Hypothesis‑driven case control association

studies remain a valid approach and, as recently demonstrated (14), could provide

valuable insight into the genetic risk factors for DTC.

This work suggests an involvement of MMR SNPs such as MSH6 rs1042821, alone or

in combination, on DTC susceptibility. However, despite the care put to avoid selection

bias and variant misclassification, our results should be regarded solely as a proof of

concept on the role of MMR genes on DTC susceptibility. Also, since the information

that was collected from study participants on prior IR exposure was not suitable for

rigorous statistical analysis, it was not possible to include it as a covariate in the

adjustment statistical model. Since IR exposure remains the best-established risk

factor for TC, future studies should be designed in order to account for this. Finally,

since no SNP functional assessment was performed, we cannot exclude the possibility

that the associations observed are due to other variants, in LD with the ones

considered here. Therefore, in order to obtain conclusive evidence, these preliminary

findings must be replicated in larger, multicentric studies with independent datasets of

patients. Such studies should be powered to allow for more sophisticated analysis

(e.g., haplotype analysis, evaluation of gene‑gene and gene‑environment interactions),

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for the study of other (e.g., less frequent but potentially relevant) variants and their

potential association with mutational events that occur early in DTC carcinogenesis.

Acknowledgements

The authors acknowledge the invaluable contributions of their late colleague Professor

Jorge Gaspar (1963-2015). The authors wish to thank Ana Paula Azevedo and Isabel

Manita for technical support. This study was supported by funding through project

UID/BIM/00009/2016 [Centre for Toxicogenomics and Human Health (ToxOmics)],

from Fundação para a Ciência e a Tecnologia (FCT), Portugal.

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Chapter VI

Thyroid Cancer: The Quest for Genetic Susceptibility Involving DNA Repair

Genes

[Research Paper]


Santos LS, Gomes BC, Bastos HN, Gil OM, Azevedo AP, Ferreira TC, Limbert E,

Silva SN, Rueff J (2019). Thyroid Cancer: The Quest for Genetic Susceptibility

Involving DNA Repair Genes. Genes (Basel). 10(8): E586. (DOI:

10.3390/genes10080586)




144

145

Chapter VI - Thyroid Cancer: The Quest for Genetic Susceptibility Involving DNA

Repair Genes

Abstract

The incidence of thyroid cancer (TC), particularly well-differentiated forms (DTC), has

been rising and remains the highest among endocrine malignancies. Although ionizing

radiation (IR) is well established on DTC aetiology, other environmental and genetic

factors may also be involved. DNA repair single nucleotide polymorphisms (SNPs)

could be among the former, helping in explaining the high incidence. To further clarify

the role of DNA repair SNPs in DTC susceptibility, we analysed 36 SNPs in 27 DNA

repair genes in a population of 106 DTCs and corresponding controls with the aim of

interpreting joint data from previously studied isolated SNPs in DNA repair genes.

Significant associations with DTC susceptibility were observed for XRCC3 rs861539,

XPC rs2228001, CCNH rs2230641, MSH6 rs1042821 and ERCC5 rs2227869 and for

a haplotype block on chromosome 5q. From 595 SNP-SNP combinations tested and

114 showing relevance, 15 significant SNP combinations (p < 0.01) were detected on

paired SNP analysis, most of which involving CCNH rs2230641 and mismatch repair

variants. Overall, a gene-dosage effect between the number of risk genotypes and

DTC predisposition was observed. In spite of the volume of data presented, new

studies are sought to provide an interpretability of the role of SNPs in DNA repair

genes and their combinations in DTC susceptibility.

Keywords: Thyroid cancer; DNA repair; genetic susceptibility; genetic markers; SNPs

Introduction

Thyroid cancer (TC) is the most common endocrine malignancy and its increasing

incidence raises concern. It is two to four times more frequent in women than in men

and one of the most common malignancies in adolescent and young adults, ages 15-

39 years, the median age at diagnosis being lower than that for most other types of

cancer (1, 2). Papillary (PTC) and follicular (FTC) thyroid cancer, representing 85-90%

and 5-10% of cases, respectively, are the most common histological varieties and are

often collectively referred to as well-differentiated thyroid carcinoma (DTC). In contrast

to anaplastic thyroid cancer (ATC), DTC prognosis is generally good, with high long-

term survival and low disease-specific mortality (3, 4).

146

DTC aetiology is multifactorial, resulting from the interplay between genetic and

environmental factors: exposure to ionizing radiation (IR), particularly during childhood,

remains the best-established modifiable risk factor, despite others – such as dietary

habits (e.g., iodine intake), obesity and xenobiotic exposure – have also been proposed

(2, 4, 5). The importance of hereditary factors on DTC susceptibility is evidenced from

familial studies demonstrating high disease risk among first-degree relatives and

placing DTC as one of the cancers with higher heritability (6). So far, the most robust

evidence – provided by several genome wide association studies (GWASs), with

independent replication across different populations – establishes markers at 9q22.33

(FOXE1), 14q13.3 (NKX2-1), 2q35 (DIRC3), 8p12 (NRG1) and 1q42.2 (PCNXL2) as

the strongest genetic susceptibility markers for DTC [reviewed in (6, 7)]. Further

candidate markers such as single nucleotide polymorphisms (SNPs) within genes

involved in cell cycle control and apoptosis, DNA repair, intracellular signalling and

transcriptional regulation have been proposed [reviewed in (8-10)] but many of these

findings have not been properly replicated. Overall, currently proposed DTC risk

markers are still largely insufficient to explain the high heritability of DTC (6). It is

possible that other, yet unidentified, genetic variants have a relevant impact on DTC

susceptibility and thus explain part of the missing heritability of the disease. Their

identification is therefore highly desirable.

DNA repair safeguards genomic integrity upon exposure to genotoxic agents, its

absence or impairment leading to cancer-driving mutations in oncogenes or tumour

suppressor genes [reviewed in (11, 12)]. A great number of DNA repair SNPs has been

associated with cancer susceptibility [reviewed in (12, 13)], strongly suggesting that

such variants may, if functionally significant, modulate the individual sensitivity to

genotoxic agents and, hence, contribute to cancer predisposition.

Considering the important role that IR and, possibly, other DNA damaging agents play

in DTC aetiology, DNA repair SNPs could, through interference with DNA repair

capacity, contribute to DTC susceptibility. Indeed, prior studies by our team do suggest

that SNPs across different DNA repair pathways – e.g., RAD51 and XRCC3 (HR

pathway), CCNH (NER pathway) and MSH6 (MMR pathway) – may be implicated in

TC (or, more specifically, DTC) predisposition (14-18). Such studies add on to prior and

subsequent work by other teams (8, 12, 19-25) that propose additional markers and

reinforce the notion that DNA repair SNPs may contribute to DTC risk. However,

besides being scarce, these studies provide only limited information on the impact of

the studied SNP in specific subpopulations, e.g., male versus female patients or early-

147

onset versus late-onset DTC. Considering the specificities of DTC regarding gender

distribution and median age at diagnosis (1, 2) such detailed analysis could prove

useful. Although gene-gene interactions could be of utmost importance in the real

context, possibly decisive, they have only seldom been evaluated and, when

considered (19, 20, 22, 24, 26, 27), analyses were usually limited to the combined

effect of SNPs in the same gene or in genes of the same pathway. DNA repair proteins

functionally interact with each other, both within the same DNA repair pathway and

across different pathways, establishing ground for additive or even multiplicative effects

of different SNPs (irrespective of their pathway) on DNA repair activity and, hence,

cancer risk. This has been previously demonstrated for other types of cancer such as

breast cancer (28-30) and, most likely, also applies to DTC. Such hypothesis has not,

to the best of our knowledge, been investigated, justifying the usefulness of assessing

the effect of combined genotypes on DTC risk.

In the present work we grouped and analysed all studies performed by our group on a

Caucasian Portuguese population (14-18). Since the actual biological situation reflects

the concerted action of various alleles in the repair of DNA lesions that may be

carcinogenic, all the data was re-analysed in order to identify intra and inter-pathway

genotype combinations and thus further characterize the potential contribution of those

DNA repair SNPs to DTC susceptibility. Such screening efforts may allow the

identification of candidate SNPs for future use as susceptibility biomarkers, hence, the

development of tailored DTC prevention policies and perhaps implementation of

guidelines.


Study subjects

Overall, 335 Caucasian Portuguese subjects were enrolled in this hospital-based case-

control study: 106 histologically confirmed DTC patients were recruited in the Service

of Nuclear Medicine of the Portuguese Oncology Institute, Lisbon, Portugal where they

were treated according to the hospital current practice and 229 unrelated age (2 years)

and gender-matched controls (two for each DTC case, in each of the previously

published studies) were recruited at the Department of Clinical Pathology of the São

Francisco Xavier Hospital, West Lisbon Hospital Centre, Portugal where they were

seeking healthcare for non-neoplastic pathology. None of the study participants had

personal history of prior malignancy nor familial history of thyroid disease.

148

In order to verify eligibility criteria and to account for potential confounding factors,

information on demographic characteristics (e.g., gender, age, occupation), family

history of cancer, lifestyle habits (e.g., smoking, alcohol drinking) and IR exposure was

collected from each study participant, on recruitment, through a pre-designed

questionnaire performed by trained interviewers. Prior exposure to relevant levels of

ionizing radiation (i.e., other than that from natural and standard diagnostic sources)

was denied by all subjects included in the study. Former smokers were considered as

non-smokers if they gave up smoking 2 years before DTC diagnosis or 2 years before

their inclusion as controls. The response rate was >95% for both cases and controls.

All studies were previously approved by the local ethics boards of the involved

institutions and conducted in compliance with the Helsinki Declaration. On recruitment,

prior to blood withdrawal, all eligible subjects were informed about the objectives of the

study. Those agreeing to participate gave their written informed consent and were

enrolled in the study. The anonymity of all participants was guaranteed.

SNP selection

The selection of SNPs for genotyping was performed according to criteria that were

predefined individually for each original study (14-18). Briefly, eligible SNPs were

required to exhibit a minor allele frequency (MAF) greater than 0.05 in Caucasian

populations, the remaining criteria (e.g., being located in a coding or splice region,

altering the amino acid sequence, being a tagging SNP, having been previously

referred to in MEDLINE) varying according to the individual study, as indicated in the

original studies of individual alleles.

Overall, a total of 36 DNA repair SNPs across all DNA repair pathways were selected

for genotyping and analysed. Details on the genomic location, base and amino acid

exchange and MAF of selected SNPs are presented on Table 6.1.

149

Table 6.1. - Selected SNPs and detailed information on the corresponding base and

amino acid exchanges, minor allele frequency (MAF) and AB assay used for

genotyping.

Gene Location

dbSNP

cluster ID

(rs no.)

Base

change

Amino acid

change

MAF

(%)a AB Assay ID


XRCC1 19q13.31 rs1799782 C → T Arg194Trp 13.1 --e

19q13.31 rs25487 G → A Arg399Gln 26.6 --e

OGG1 3p25.3 rs1052133 C → G Ser326Cys 29.9 --e

APEX1 14q11.2 rs1130409 T → G Asp148Glu 44.0 C___8921503_10

MUTYH 1p34.1 rs3219489 G → C Gln335His 31.9 C__27504565_10

PARP1 1q42.12 rs1136410 T → C Val762Ala 24.4 C___1515368_1_

Nucleotide Excision Repair (NER)

CCNH 5q14.3 rs2230641 T → C Val270Ala 13.8 C__11685807_10

CDK7 5q13.2 rs2972388 A → G Asn33Asn 40.5 C___1191757_10

ERCC5 13q33.1 rs2227869 G → C Cys529Ser 4.9 C__15956775_10

13q33.1 rs17655 C → G Asp1104His 37.7 C___1891743_10

ERCC1 19q13.32 rs3212986 G → T -- b 29.4 C___2532948_10

RAD23B 9q31.2 rs1805329 C → T Ala249Val 16.7 C__11493966_10

ERCC6 10q11.23 rs2228529 A → G Gln1413Arg 15.6 C__16171343_10

10q11.23 rs4253211 G → C Arg1230Pro 6.4 C__25762749_10

ERCC4 16p13.12 rs1800067 G → A Arg415Gln 3.1 C___3285104_10

XPC 3p25.1 rs2228000 C → T Ala499Val 24.8 --e

3p25.1 rs2228001 A → C Lys939Gln 34.4 --e

Mismatch Repair (MMR)



5q14.1 rs184967 G → A Arg949Gln 9.8 C____907914_10

MSH4 1p31.1 rs5745549 G → A Ser914Asn 6.4 C___1184803_10

1p31.1 rs5745325 G → A Ala97Thr 21.3 C___3286081_10

PMS1 2q32.2 rs5742933 G → C -- c 21.9 C__29329633_10

MLH3 14q24.3 rs175080 G → A Pro844Leu 36.4 C___1082805_10



150

RAD51 15q15.1 rs1801321 G → T -- c 25.7 C___7482700_10

NBN 8q21.3 rs1805794 C → G Glu185Gln 35.7 C__26470398_30

XRCC2 7q36.1 rs3218536 G → A Arg188His 5.3 --e

XRCC3 14q32.33 rs861539 C → T Thr241Met 21.7 --e

Non-homologous End Joining (NHEJ)

XRCC4 5q14.2 rs1805377 G → A -- d 37.5 C__11685997_10

LIG4 13q33.3 rs1805388 C → T Thr9Ile 14.6 C__11427969_20

XRCC4 5q14.2 rs28360135 T → C Ile134Thr 1.4 C__25618660_10

XRCC5

2q35 rs1051685 A → G -- b 17.2 C___8838368_1_

2q35 rs1051677 T → C -- b 15.6 C___8838367_1_

2q35 rs6941 C → A -- b 15.7 C___8838374_10

2q35 rs2440 C → T -- b 42.0 C___3231046_10

aMinor Allele Frequency, according to http://www.ncbi.nlm.nih.gov/projects/SNP/.

bSNP located on 3’ UTR. cSNP located on 5’ UTR. dSNP located on intron. enot

applicable (genotyping performed by PCR-RFLP). SNPs, single nucleotide

polymorphisms.

Practical Methodologies — Brief Description

All DNA samples were obtained after collection of peripheral venous blood samples

from each participant. The DNA extraction was performed as described previously (14-

18) using a commercially available kit (QIAamp® DNA mini kit; Qiagen GmbH, Hilden,

Germany), according to the manufacturer’s recommendations. All samples were stored

at -20 ºC until further analysis.

Genotyping was carried out through either real-time polymerase chain reaction (PCR)

or conventional PCR-restriction fragment length polymorphism (RFLP) techniques, as

described in previous studies (14-18). For real-time PCR – the option for the vast

majority of SNPs considered in this study – genotyping was performed on an ABI 7300

Real-Time PCR system thermal cycler (Applied Biosystems; Thermo Fisher Scientific,

Inc., Waltham, MA, USA), using the commercially available TaqMan® SNP Genotyping

Assays (Applied Biosystems) identified in Table 6.1. Conventional techniques of

polymerase chain reaction (PCR) and restriction fragment length polymorphism (RFLP)

were employed to genotype XRCC1 rs1799782, XRCC1 rs25487 and OGG1

rs1052133 (BER pathway); XPC rs2228000 and XPC rs2228001 (NER pathway); and

XRCC3 rs861539 and XRCC2 rs3218536 (HR pathway). Primer design methods and

sequences, PCR conditions, PCR product sizes, restriction analysis conditions and


151

expected digestion pattern for each genotype have been described in full detail

elsewhere (14, 16, 17) and will therefore not be reproduced here. Irrespective of the

genotyping method, all inconclusive samples were reanalysed. Also, for quality control,

at least 10-15% of genotype determinations were run in duplicates through

independent experiments, with 100% concordance between experiments.


Prior to analysis, genotype distributions for each studied SNP were checked for

deviation from Hardy-Weinberg equilibrium (HWE) using SNPstats platform (31), in

both case and control populations. Variable transformation was applied to categorize

the only continuous variable (age of diagnosis) and the Chi-square test was then used

to evaluate differences in genotype frequency, smoking status, age class and gender

distributions between DTC patients and controls. Whenever the construction of 2x2

contingency tables was possible, the two-sided Fisher’s exact test was employed

instead of the Chi-square test.

Logistic regression was used to estimate the risk of DTC associated with each

genotype: risk estimates were calculated under the codominant, dominant and

recessive models and expressed as crude and adjusted odds ratios (OR) and

corresponding 95% confidence intervals (CI). Whenever adjustment was performed,

terms for gender (male/female), age class (<30, 30-49, 50-69 and ≥70 years) and

smoking habits (smokers/non-smokers) were included in the model, the most common

homozygous genotype, female gender, lower age group and non-smoking status being

considered the reference classes for such calculations. As data on prior IR exposure

was not suitable for rigorous quantitative transformation, it was not possible to include

such term in the adjustment model. Risk estimates were calculated in the whole

population and after stratification according to histological type of tumour (papillary or

follicular TC), gender (male and female) and age (<50 and ≥50 years).

Finally, the joint effect of multiple SNPs on DTC risk was estimated from application of

logistic regression analysis (1) to relevant haplotypes, (2) to individual genetic risk

scores calculated from genotype variables significant on single SNP analysis and (3) to

all possible 2x2 combinations of the DNA repair SNPs included in this study. For the

purpose of risk score calculations, genotypes presenting significant results on single

SNP analysis were attributed a +1 score, the risk score for each participant

corresponding to the sum of such scores. Samples with one or more missing

genotypes were excluded from these calculations to avoid bias due to missing data.

152

For paired SNP analysis, the combination of the most common homozygous genotypes

of each individual SNP in the control group was taken as the reference category in OR

calculations. Also, paired genotypes with frequency <5% in the study population were

pooled together.

This is not a conclusive final study but an exploratory one that should be regarded as

‘proof of concept’. As such, the Bonferroni adjustment was deemed as not necessary

as it is too conservative. Also, the complement of the false negative rate β to compute

the power of a test (1-β) was not taken into account at this stage since further studies

with more patients and controls should be undertaken to change over this preliminary

study into a confirmatory positive one. All statistical analyses were performed with

SPSS 22.0 (IBM SPSS Statistics for Windows, version 22.0, IBM Corp, Armonk, NY,

USA) except for assessment of HWE deviation, MAF calculations, haplotype estimation

and linkage disequilibrium (LD) analysis which were carried out using SNPstats (31).

Results were considered significant when the corresponding two-tailed p-values were

<0.05 except for paired SNP analysis where, because of the high number of SNP-SNP

combinations being tested, a more stringent significance level (p < 0.01) was

employed. The study was approved by the Ethical Committee of Nova Medical School,

Faculty of Medical Sciences with the number 05/2008 dated of January 9th, 2008. The

approval was also obtained by the ethical committee of Portuguese Oncology Institute

(IPO), the hospital responsible for blood samples collection, with the reference GIC/357

dated of July 14th 2004.

Results

General Analysis

The general characteristics of the 106 DTC patients and their 229 age- and gender-

matched controls included in this study are depicted in Table 6.2. The overall mean

age of the study population was 51 years (52.1 in the patient group and 51.0 in the

control group). As expected from the worldwide gender distribution for DTC (1, 2),

female patients greatly outnumbered male patients in the case group. Twelve (11.3%)

DTC patients were categorized as smokers. Age distribution, gender and smoking

habits were not significantly different between case and control populations.

Concerning histological classification of tumours, 78 (73.6%) patients were diagnosed

as papillary TC while 28 (26.4%) presented follicular tumours, in line with DTC

histotype distributions commonly reported in the literature (4). Three additional cases of

poorly differentiated TC were also present in some of our original studies but, since this

153

study concerns only with DTC, such cases (and the corresponding controls) were

excluded from this analysis. Prior IR exposure (except for diagnostic X-rays) was

denied by all cases.

Table 6.2. - General characteristics for the DTC case (n = 106) and control (n = 229)

populations.

Characteristics Controls n (%) Cases n (%) p-valuec

Gender Male 43 (18.8) 16 (15.1)

0.445 Female 186 (81.2) 90 (84.9)

Agea,b

<30 14 (6.1) 4 (3.8)

0.817 30-49 85 (37.1) 38 (35.8)

50-69 100 (43.7) 49 (46.2)

70 30 (13.1) 15 (14.2)

Smoking habits

Non-smokers 184 (80.3) 94 (88.7)

0.084 Smokers 43 (18.8) 12 (11.3)

Missing 2 (0.9) 0 (0.0)

aAge of diagnosis, for cases. bAge at the time of diagnosis of the matched case, for

controls. cp-value for cases vs. control group determined by two-sided Fisher’s exact

test (gender, smoking habits) or χ2 test (age). DTC, well-differentiated thyroid cancer.

All DTC Cases

Allelic and genotypic frequencies as well as crude/adjusted ORs were calculated for all

36 DNA repair SNPs analysed in our study. Significant findings are reported in Table

6.3. The allelic and genotypic frequencies observed in the control group were in

agreement with those expected for Caucasian populations. Also, for the majority of

SNPs, genotype distributions were in Hardy-Weinberg equilibrium (HWE, p ≥ 0.05), in

both case and control populations. Significant deviations from HWE were observed for

OGG1 rs1052133, MUTYH rs3219489 and CDK7 rs2972388 in the control group and

for XRCC1 rs1799782, XPC rs2228000 and MSH3 rs184967 in the DTC group.

Further, strong linkage disequilibrium was observed between XRCC5 rs1051677 and

rs6941, but not between any other pair of SNPs. XRCC5 rs6941 was thus excluded

from further analysis, the conclusions taken for XRCC5 rs1051677 being valid for

XRCC5 rs6941, since they behave as tag SNPs.

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Table 6.3. - Genotype distribution in case and control populations and associated DTC risk (crude and adjusted ORs). Only SNPs presenting

significant findings are shown.

Genotype MAF Genotype frequency

p-valuea OR (95% CI) Adjusted OR (95% CI)b Controls Cases Controls n (%) Cases n (%)

CCNH rs2230641 212 (100) 106 (100)

Val/Val

C: 0.17 C: 0.23

148 (69.8) 60 (56.6)

0.037c

1 (Reference) 1 (Reference)

Val/Ala 56 (26.4) 43 (40.6) 1.89 (1.15-3.12)c 1.89 (1.14-3.14)c

Ala/Ala 8 (3.8) 3 (2.8) 0.93 (0.24-3.61) 1.01 (0.25-4.04)

Dominant model 64 (30.2) 46 (43.4) 0.024c 1.77 (1.09-2.87)c 1.79 (1.09-2.93)c

Recessive model 8 (3.8) 3 (2.8) 0.757 0.74 (0.19-2.86) 0.80 (0.20-3.17)

ERCC5 rs2227869 212 (100) 106 (100)

Cys/Cys

C: 0.07 C: 0.04

184 (86.8) 99 (93.4)

0.135


Cys/Ser 27 (12.7) 6 (5.7) 0.41 (0.17-1.03) 0.39 (0.16-1.00)c

Ser/Ser 1 (0.5) 1 (0.9) 1.86 (0.12-30.04) 1.78 (0.11-29.13)

Dominant model 28 (13.2) 7 (6.6) 0.088 0.47 (0.20-1.10) 0.44 (0.19-1.06)

Recessive model 1 (0.5) 1 (0.9) 1.000 2.01 (0.12-32.45) 1.92 (0.12-31.48)

XPC rs2228001 212 (100) 106 (100)

Lys/Lys

C: 0.36 C: 0.41

82 (38.7) 39 (36.8)

0.103


Lys/Gln 108 (50.9) 47 (44.3) 0.92 (0.55-1.53) 0.95 (0.57-1.60)

Gln/Gln 22 (10.4) 20 (18.9) 1.91 (0.94-3.91) 1.92 (0.93-3.97)

Dominant model 130 (61.3) 67 (63.2) 0.807 1.08 (0.67-1.76) 1.12 (0.69-1.82)

155

Recessive model 22 (10.4) 20 (18.9) 0.052 2.01 (1.04-3.87)c 1.97 (1.01-3.84)c

MSH6 rs1042821 210 (100) 106 (100)

Gly/Gly

T: 0.21 T: 0.22

127 (60.5) 68 (64.2)

0.042c


Gly/Glu 78 (37.1) 30 (28.3) 0.72 (0.43-1.20) 0.73 (0.43-1.23)

Glu/Glu 5 (2.4) 8 (7.5) 2.99 (0.94-9.49) 3.42 (1.04-11.24)c

Dominant model 83 (39.5) 38 (35.8) 0.543 0.86 (0.53-1.39) 0.87 (0.54-1.43)


XRCC3 rs861539 209 (100) 106 (100)

Thr/Thr

T: 0.40 T: 0.45

70 (33.5) 36 (34.0)

0.021c


Thr/Met 112 (53.6) 44 (41.5) 0.76 (0.45-1.30) 0.77 (0.45-1.31)

Met/Met 27 (12.9) 26 (24.5) 1.87 (0.96-3.67) 1.89 (0.96-3.72)

Dominant model 139 (66.5) 70 (66.0) 1.000 0.98 (0.60-1.61) 0.99 (0.60-1.62)


ap-value for cases vs. control group determined by two-sided Fisher’s exact test (whenever 2x2 contingency tables are possible) or χ2 test

(remaining cases). bORs were adjusted for gender (male and female), age (<30, 30-49, 50-69, ≥70 years) and smoking status (non-smoker

and smoker). cp < 0.05. DTC, well-differentiated thyroid cancer; MAF, minor allele frequency; OR, odds ratio; CI, confidence interval.

156

As expected, both the comparison of genotype frequency distributions between case

and control populations and the logistic regression analysis (Table 6.3) yielded results

similar to those previously reported (14-18): significant differences on the distribution of

genotypic frequencies between cases and controls were observed for CCNH

rs2230641 (p = 0.037 on the codominant model and p = 0.024 on the dominant model),

for MSH6 rs1042821 (p = 0.042, on the codominant model and p = 0.037 on the

recessive model) and for XRCC3 rs861539 (p = 0.021 on the codominant model and p

= 0.011 on the recessive model). On logistic regression analysis, after adjustment for

age, gender and smoking status, DTC risk was significantly increased in CCNH

rs2230641 heterozygotes (adjusted OR = 1.89, 95% CI: 1.14-3.14, p = 0.014) and also

in variant allele carriers, according the dominant model (adjusted OR = 1.79, 95% CI:

1.09-2.93, p = 0.021), in MSH6 rs1042821 variant allele homozygotes (adjusted OR =

3.42, 95% CI: 1.04-11.24, p = 0.042 on the codominant model; adjusted OR = 3.84,

95% CI: 1.18-12.44, p = 0.025 on the recessive model), in XRCC3 rs861539 variant

allele homozygotes (adjusted OR = 2.20, 95% CI: 1.20-4.03, p = 0.011 on the

recessive model) and in XPC rs2228001 variant allele homozygotes (adjusted OR =

1.97, 95% CI: 1.01-3.84, p = 0.046 on the recessive model). A borderline significant

DTC risk reduction was observed in ERCC5 rs2227869 heterozygotes (adjusted OR =

0.39, 95% CI: 0.16-1.00, p = 0.049). The association between XPC rs2228001 and

DTC risk is a new finding emerging from this reanalysis, since the recessive model of

inheritance had not been applied in the original study (17). No additional significant

differences in genotype frequency distributions nor associations with DTC risk were

found, irrespective of the model assumed.

Stratified Analysis

Stratified analysis according to histological tumour type, gender and age may be

important to identify any subgroup-specific risk association but was only partially

performed in prior studies in this population. On stratification according to histological

criteria (Table 6.4), this study confirmed prior observations (14, 17, 18) of increased

papillary TC risk in XPC rs2228001 and XRCC3 rs861539 variant allele homozygotes

(XPC rs2228001: adjusted OR = 2.31, 95% CI: 1.07-4.98, p = 0.033; XRCC3 rs861539:

adjusted OR = 2.10, 95% CI: 1.07-4.11, p = 0.031, both on the recessive model),

decreased papillary TC risk in ERCC5 rs2227869 heterozygotes (adjusted OR = 0.23,

95% CI: 0.07-0.81, p = 0.022, on the codominant model) or variant allele carriers

(adjusted OR = 0.22, 95% CI: 0.06-0.77, p = 0.018, on the dominant model) and

157

increased follicular TC risk in MLH3 rs175080 variant allele carriers (crude OR = 3.95,

95% CI: 1.05-14.81, p = 0.042) and MSH6 rs1042821 variant allele homozygotes

(adjusted OR = 20.98, 95% CI: 1.08-406.53, p = 0.044, on the codominant model;

adjusted OR = 23.70, 95% CI: 1.25-449.32, p = 0.035, on the recessive model).

Interestingly, three other significant associations were observed in this reanalysis that

were not present or had not been detected in the original studies, while two previously

observed associations were lost in this reanalysis: a previously undetected decreased

papillary TC risk was observed in MUTYH rs3219489 heterozygotes (crude OR = 0.56,

95% CI: 0.32-1.00, p = 0.048) and variant allele carriers (crude OR = 0.57, 95% CI:

0.33-0.99, p = 0.048) as well as in NBN rs1805794 variant allele homozygotes

(adjusted OR = 0.28, 95% CI: 0.08-0.97, p = 0.045, on the recessive model) while the

presence of the variant allele of XRCC2 rs3218536 exhibited a protective effect for

follicular TC (crude OR = 0.21, 95% CI: 0.04-1.00, p = 0.049, either for heterozygotes

in the codominant model and for variant allele carriers in the dominant model). In

contrast, the associations of XRCC5 rs2440 and CCNH rs2230641 genotypes with

papillary and follicular TC risk, respectively, reported in our original studies (15, 17),

were no longer observed.

On gender stratification (Table 6.4), when considering female patients only, a

significantly increased DTC risk was evident for CCNH rs2230641 heterozygotes

(adjusted OR = 1.97, 95% CI: 1.13-3.43, p = 0.017) and variant allele carriers (adjusted

OR = 1.90, 95% CI: 1.11-3.24, p = 0.020), for XPC rs2228001 variant allele

homozygotes (adjusted OR = 2.00, 95% CI: 1.01-3.96, p = 0.048, on the recessive

model), for MSH6 rs1042821 variant allele homozygotes (adjusted OR = 4.78, 95% CI:

1.17-19.56, p = 0.030, on the codominant model; adjusted OR = 5.42, 95% CI: 1.34-

21.92, p = 0.018, on the recessive model) and for XRCC3 rs861539 variant allele

homozygotes (adjusted OR = 2.36, 95% CI: 1.12-4.97, p = 0.024, on the codominant

model; adjusted OR = 2.68, 95% CI: 1.39-5.18, p = 0.003, on the recessive model).

Opposing, ERCC5 rs2227869 heterozygotes (adjusted OR = 0.25, 95% CI: 0.07-0.88,

p = 0.030) and variant allele carriers (adjusted OR = 0.32, 95% CI: 0.11-0.97, p =

0.044) as well as ERCC5 rs17655 variant allele homozygotes (adjusted OR = 0.27,

95% CI: 0.08-0.95, p = 0.041, on the recessive model) presented a significant risk

reduction among female patients. Among these gender-specific genetic effects, only

the association with MSH6 rs1042821 had been reported in the original studies (18).

No significant association was observed in the male subset of patients, possibly

because of the low number of cases in this gender group. An association between

158

XRCC5 rs1051677 and TC risk had previously been identified in this subset of patients

(15) but significance was lost upon restricting analysis to well-differentiated forms of TC

(this study).

Stratified analysis according to the age of diagnosis had only been performed in some

of our initial studies, namely those involving SNPs of the BER and MMR pathways (16,

18), with negative results. We therefore extended this analysis to the remaining DNA

repair SNPs, considering two age groups: <50 and ≥50 years. In patients under 50

years of age, both homozygosity for the XPC rs2228001 variant allele (adjusted OR =

2.86, 95% CI: 1.01-8.08, p = 0.048, on the recessive model) and the presence of at

least one XRCC5 rs2440 variant allele (adjusted OR = 2.53, 95% CI: 1.02-6.26, p =

0.045) were associated with increased DTC risk. When restricting the analysis to

patients with 50 or more years of age, DTC risk was increased in CCNH rs2230641

heterozygotes (adjusted OR = 2.91, 95% CI: 1.51-5.60, p = 0.001) and variant allele

carriers (adjusted OR = 3.04, 95% CI: 1.59-5.81, p = 0.001), in RAD51 rs1801321

variant allele homozygotes (adjusted OR = 2.99, 95% CI: 1.25-7.14, p = 0.014, on the

codominant model; unadjusted OR = 2.03, 95% CI: 1.00-4.12, p = 0.049, on the

recessive model) and variant allele carriers (adjusted OR = 2.14, 95% CI: 1.06-4.32, p

= 0.034) and in XRCC3 rs861539 variant allele homozygotes (adjusted OR = 2.63,

95% CI: 1.16-5.97, p = 0.021, on the recessive model). On the contrary, the presence

of at least one variant ERCC6 rs2228529 allele (adjusted OR = 0.47, 95% CI: 0.24-

0.92, p = 0.028) and its presence in heterozygosity (adjusted OR = 0.48, 95% CI: 0.24-

0.97, p = 0.042) were associated with a DTC risk reduction in this older age group.

No further correlations between individual DNA repair SNPs and DTC risk were

observed on histology-, gender- and age-based stratification analysis.

159

Table 6.4. - Genotype distribution in the case population (n = 106) and associated DTC risk (crude and adjusted ORs), after stratification

according to histological type, gender and age. Only SNPs presenting significant findings are shown.

Genotype

Papillary Carcinoma Follicular Carcinoma

n (%) Crude OR

(95% CI)

Adjusted OR

(95% CI)a n (%)

Crude OR

(95% CI)

Adjusted OR

(95% CI)a

MUTYH rs3219489 78 (100) 28 (100)

Gln/Gln 48 (61.5) 1 (reference) 1 (reference) 15 (53.6) 1 (reference) 1 (reference)

Gln/His 27 (34.6) 0.56 (0.32-1.00)b 0.57 (0.32-1.02) 11 (39.3) 0.95 (0.37-2.43) 1.09 (0.40-2.92)

His/His 3 (3.8) 0.66 (0.16-2.68) 0.69 (0.17-2.86) 2 (7.1) 4.13 (0.35-49.28) 6.97 (0.47-104.26)

Dominant model 30 (38.5) 0.57 (0.33-0.99)b 0.58 (0.33-1.02) 13 (46.4) 1.08 (0.43-2.67) 1.27 (0.49-3.29)

Recessive model 3 (3.8) 0.85 (0.21-3.36) 0.87 (0.22-3.54) 2 (7.1) 4.23 (0.37-48.8) 6.75 (0.46-98.39)

ERCC5 rs2227869 78 (100) 28 (100)

Cys/Cys 75 (96.2) 1 (reference) 1 (reference) 24 (85.7) 1 (reference) 1 (reference)

Cys/Ser 3 (3.8) 0.24 (0.07-0.84)b 0.23 (0.07-0.81)b 3 (10.7) 1.28 (0.28-5.78) 1.20 (0.26-5.61)

Ser/Ser 0 (0.0) -- -- 1 (3.6) -- --

Dominant model 3 (3.8) 0.23 (0.07-0.80)b 0.22 (0.06-0.77)b 4 (14.3) 1.70 (0.42-6.90) 1.61 (0.38-6.74)

Recessive model 0 (0.0) -- -- 1 (3.6) -- --

XPC rs2228001 78 (100) 28 (100)

Lys/Lys 26 (33.3) 1 (reference) 1 (reference) 13 (46.4) 1 (reference) 1 (reference)

Lys/Gln 36 (46.2) 1.01 (0.55-1.85) 1.03 (0.56-1.90) 11 (39.3) 0.72 (0.27-1.91) 0.91 (0.33-2.54)

Gln/Gln 16 (20.5) 2.27 (0.99-5.22) 2.35 (1.00-5.51) 4 (14.3) 1.18 (0.28-4.96) 1.05 (0.24-4.65)

160

Dominant model 52 (66.7) 1.22 (0.69-2.15) 1.23 (0.69-2.20) 15 (53.6) 0.80 (0.32-2.01) 0.94 (0.36-2.44)

Recessive model 16 (20.5) 2.26 (1.06-4.80)b 2.31 (1.07-4.98)b 4 (14.3) 1.39 (0.36-5.39) 1.10 (0.27-4.51)

MLH3 rs175080

Pro/Pro 19 (24.4) 1 (reference) 1 (reference) 3 (10.7) 1 (reference) 1 (reference)

Pro/Leu 42 (53.8) 1.13 (0.59-2.19) 1.17 (0.60-2.27) 17 (60.7) 3.78 (0.97-14.79) 3.61 (0.88-14.85)

Leu/Leu 17 (21.8) 1.17 (0.53-2.61) 1.20 (0.54-2.68) 8 (28.6) 4.36 (0.95-20.04) 4.29 (0.89-20.78)

Dominant model 59 (75.6) 1.14 (0.61-2.14) 1.18 (0.62-2.22) 25 (89.3) 3.95 (1.05-14.81)b 3.81 (0.97-14.95)

Recessive model 17 (21.8) 1.08 (0.56-2.10) 1.08 (0.56-2.10) 8 (28.6) 1.64 (0.57-4.69) 1.67 (0.55-5.02)

MSH6 rs1042821 78 (100) 28 (100)

Gly/Gly 49 (62.8) 1 (reference) 1 (reference) 19 (67.9) 1 (reference) 1 (reference)

Gly/Glu 24 (30.8) 0.74 (0.41-1.32) 0.74 (0.41-1.35) 6 (21.4) 0.65 (0.22-1.91) 0.76 (0.24-2.35)

Glu/Glu 5 (6.4) 2.30 (0.59-8.95) 2.47 (0.61-9.89) 3 (10.7) 5.84 (0.57-60.03) 20.98 (1.08-406.53)b

Dominant model 29 (37.2) 0.83 (0.48-1.46) 0.85 (0.48-1.49) 9 (32.1) 0.92 (0.35-2.43) 1.10 (0.39-3.07)

Recessive model 5 (6.4) 2.57 (0.67-9.85) 2.74 (0.69-10.84) 3 (10.7) 6.60 (0.65-66.63) 23.70 (1.25-449.32)b

NBN rs1805794 78 (100) 28 (100)

Glu/Glu 42 (53.8) 1 (reference) 1 (reference) 13 (46.4) 1 (reference) 1 (reference)

Glu/Gln 33 (42.3) 1.17 (0.66-2.07) 1.15 (0.64-2.04) 10 (35.7) 0.90 (0.33-2.41) 0.72 (0.25-2.05)

Gln/Gln 3 (3.8) 0.31 (0.09-1.10) 0.29 (0.08-1.06) 5 (17.9) 2.69 (0.62-11.71) 2.23 (0.44-11.18)

Dominant model 36 (46.2) 0.95 (0.55-1.64) 0.94 (0.54-1.63) 15 (53.6) 1.15 (0.47-2.86) 0.90 (0.34-2.39)

Recessive model 3 (3.8) 0.29 (0.08-1.01) 0.28 (0.08-0.97)b 5 (17.9) 2.83 (0.70-11.50) 2.66 (0.58-12.06)

XRCC2 rs3218536 78 (100) 28 (100)

161

Arg/Arg 66 (84.6) 1 (reference) 1 (reference) 26 (92.9) 1 (reference) 1 (reference)

Arg/His 12 (15.4) 1.17 (0.54-2.52) 1.19 (0.55-2.57) 2 (7.1) 0.21 (0.04-1.00)b 0.20 (0.04-1.05)

His/His 0 (0.0) -- -- 0 (0.0) -- --

Dominant model 12 (15.4) 1.17 (0.54-2.52) 1.19 (0.55-2.57) 2 (7.1) 0.21 (0.04-1.00)b 0.20 (0.04-1.05)

Recessive model 0 (0.0) -- -- 0 (0.0) -- --

XRCC3 rs861539 78 (100) 28 (100)

Thr/Thr 26 (33.3) 1 (reference) 1 (reference) 10 (35.7) 1 (reference) 1 (reference)

Thr/Met 31 (39.7) 0.75 (0.40-1.40) 0.74 (0.39-1.39) 13 (46.4) 0.81 (0.30-2.20) 0.78 (0.27-2.24)

Met/Met 21 (26.9) 1.76 (0.82-3.75) 1.76 (0.82-3.77) 5 (17.9) 2.50 (0.55-11.41) 2.72 (0.54-13.60)

Dominant model 52 (66.7) 0.97 (0.54-1.73) 0.97 (0.54-1.73) 18 (64.3) 1.00 (0.39-2.58) 1.00 (0.37-2.69)


Genotype

Male Female

n (%) OR (95% CI) Adjusted OR (95% CI)a n (%) OR (95% CI) Adjusted OR (95%

CI)a

CCNH rs2230641 16 (100) 90 (100)

Val/Val 7 (43.8) 1 (reference) 1 (reference) 53 (58.9) 1 (reference) 1 (reference)

Val/Ala 9 (56.3) 1.38 (0.40-4.70) 1.67 (0.44-6.34) 34 (37.8) 2.03 (1.17-3.53)b 1.97 (1.13-3.43)b

Ala/Ala 0 (0.0) -- -- 3 (3.3) 1.26 (0.30-5.20) 1.36 (0.32-5.78)

Dominant model 9 (56.3) 1.21 (0.36-4.06) 1.40 (0.38-5.17) 37 (41.1) 1.93 (1.13-3.30)b 1.90 (1.11-3.24)b

Recessive model 0 (0.0) -- -- 3 (3.3) 1.01 (0.25-4.12) 1.11 (0.26-4.68)

162

ERCC5 rs2227869 16 (100) 90 (100)

Cys/Cys 13 (81.3) 1 (reference) 1 (reference) 86 (95.6) 1 (reference) 1 (reference)

Cys/Ser 3 (18.8) 0.96 (0.21-4.48) 0.94 (0.19-4.62) 3 (3.3) 0.26 (0.08-0.91)b 0.25 (0.07-0.88)b

Ser/Ser 0 (0.0) -- -- 1 (1.1) 1.85 (0.11-29.93) 1.70 (0.10-27.92)

Dominant model 3 (18.8) 0.96 (0.21-4.48) 0.94 (0.19-4.62) 4 (4.4) 0.34 (0.11-1.01) 0.32 (0.11-0.97)b

Recessive model 0 (0.0) -- -- 1 (1.1) 2.02 (0.13-32.71) 1.92 (0.12-31.53)

ERCC5 rs17655 16 (100) 89 (100)

Asp/Asp 10 (62.5) 1 (reference) 1 (reference) 41 (46.1) 1 (reference) 1 (reference)

Asp/His 5 (31.3) 0.61 (0.17-2.20) 0.63 (0.17-2.34) 45 (50.6) 1.38 (0.81-2.33) 1.36 (0.80-2.30)

His/His 1 (6.3) -- -- 3 (3.4) 0.31 (0.09-1.10) 0.32 (0.09-1.14)

Dominant model 6 (37.5) 0.73 (0.21-2.51) 0.76 (0.22-2.67) 48 (53.9) 1.13 (0.68-1.88) 1.13 (0.68-1.89)

Recessive model 1 (6.3) -- -- 3 (3.4) 0.27 (0.08-0.92)b 0.27 (0.08-0.95)b

XPC rs2228001 16 (100) 90 (100)


Lys/Gln 6 (37.5) 0.58 (0.17-2.05) 0.59 (0.16-2.20) 41 (45.6) 1.01 (0.57-1.78) 1.05 (0.59-1.86)

Gln/Gln 1 (6.3) 1.56 (0.09-28.15) 1.22 (0.06-23.58) 19 (21.1) 2.05 (0.96-4.36) 2.05 (0.96-4.38)

Dominant model 7 (43.8) 0.64 (0.19-2.16) 0.63 (0.18-2.27) 60 (66.7) 1.20 (0.71-2.05) 1.24 (0.72-2.12)

Recessive model 1 (6.3) 2.00 (0.12-34.24) 1.55 (0.09-28.35) 19 (21.1) 2.04 (1.03-4.03)b 2.00 (1.01-3.96)b

MSH6 rs1042821 16 (100) 90 (100)

Gly/Gly 11 (68.8) 1 (reference) 1 (reference) 57 (63.3) 1 (reference) 1 (reference)

Gly/Glu 4 (25.0) 0.86 (0.21-3.54) 0.96 (0.20-4.52) 26 (28.9) 0.70 (0.41-1.22) 0.70 (0.40-1.22)

163

Glu/Glu 1 (6.3) 0.86 (0.07-10.66) 1.08 (0.07-16.53) 7 (7.8) 4.42 (1.10-17.75)b 4.78 (1.17-19.56)b

Dominant model 5 (31.2) 0.86 (0.23-3.19) 0.98 (0.23-4.24) 33 (36.7) 0.86 (0.51-1.44) 0.86 (0.51-1.45)


XRCC3 rs861539 16 (100) 90 (100)


Thr/Met 6 (37.5) 0.69 (0.19-2.59) 0.62 (0.16-2.43) 38 (42.2) 0.80 (0.44-1.43) 0.81 (0.45-1.46)

Met/Met 2 (12.5) 0.60 (0.09-3.89) 0.47 (0.07-3.28) 24 (26.7) 2.26 (1.09-4.71)b 2.36 (1.12-4.97)b

Dominant model 8 (50.0) 0.67 (0.20-2.26) 0.58 (0.16-2.08) 62 (68.9) 1.06 (0.62-1.83) 1.08 (0.63-1.88)


Genotype

<50 years ≥50 years

n (%) OR (95% CI) Adjusted OR (95% CI)a n (%) OR (95% CI) Adjusted OR (95%

CI)a

CCNH rs2230641 42 (100) 64 (100)

Val/Val 27 (64.3) 1 (reference) 1 (reference) 33 (51.6) 1 (reference) 1 (reference)

Val/Ala 14 (33.3) 0.96 (0.43-2.13) 0.93 (0.41-2.12) 29 (45.3) 2.97 (1.55-5.68)b 2.91 (1.51-5.60)b

Ala/Ala 1 (2.4) 0.27 (0.03-2.26) 0.27 (0.03-2.31) 2 (3.1) 5.94 (0.52-67.64) 8.01 (0.62-102.77)


Recessive model 1 (2.4) 0.27 (0.03-2.26) 0.27 (0.03-2.33) 2 (3.1) 4.10 (0.36-46.05) 5.67 (0.45-72.01)

ERCC6 rs2228529 42 (100) 62 (100)

Gln/Gln 20 (47.6) 1 (reference) 1 (reference) 46 (74.2) 1 (reference) 1 (reference)

164

Gln/Arg 20 (47.6) 1.19 (0.56-2.54) 1.09 (0.50-2.36) 15 (24.2) 0.49 (0.25-0.98)b 0.48 (0.24-0.97)b

Arg/Arg 2 (4.8) 2.20 (0.29-16.75) 2.12 (0.27-16.60) 1 (1.6) 0.32 (0.04-2.84) 0.30 (0.03-2.63)


Recessive model 2 (4.8) 2.03 (0.28-14.91) 2.04 (0.27-15.33) 1 (1.6) 0.40 (0.05-3.53) 0.37 (0.04-3.28)

XPC rs2228001 42 (100) 64 (100)


Lys/Gln 15 (35.7) 0.58 (0.25-1.32) 0.58 (0.25-1.37) 32 (50.0) 1.22 (0.63-2.35) 1.27 (0.66-2.48)

Gln/Gln 10 (23.8) 2.21 (0.73-6.65) 2.11 (0.68-6.58) 10 (15.6) 1.69 (0.65-4.38) 1.74 (0.66-4.57)

Dominant model 25 (59.5) 0.82 (0.38-1.75) 0.81 (0.37-1.78) 42 (65.6) 1.31 (0.70-2.44) 1.36 (0.72-2.56)


RAD51 rs1801321 42 (100) 64 (100)

G/G 14 (33.3) 1 (reference) 1 (reference) 14 (21.9) 1 (reference) 1 (reference)

G/T 19 (45.2) 0.95 (0.41-2.24) 1.00 (0.42-2.38) 31 (48.4) 1.76 (0.84-3.69) 1.83 (0.87-3.86)

T/T 9 (21.4) 0.80 (0.29-2.20) 0.75 (0.27-2.10) 19 (29.7) 2.90 (1.23-6.83)b 2.99 (1.25-7.14)b


Recessive model 9 (21.4) 0.82 (0.34-1.99) 0.75 ( (0.30-1.84) 19 (29.7) 2.03 (1.00-4.12)b 2.05 (1.00-4.21)

XRCC3 rs861539 42 (100) 64 (100)


Thr/Met 16 (38.1) 0.65 (0.27-1.52) 0.63 (0.27-1.52) 28 (43.8) 0.85 (0.43-1.68) 0.87 (0.44-1.73)

Met/Met 11 (26.2) 1.47 (0.53-4.08) 1.48 (0.52-4.19) 15 (23.4) 2.25 (0.92-5.49) 2.42 (0.97-6.03)

Dominant model 27 (64.3) 0.84 (0.38-1.83) 0.83 (0.37-1.84) 43 (67.2) 1.09 (0.57-2.05) 1.12 (0.59-2.14)

165


XRCC5 rs2440 42 (100) 62 (100)

C/C 8 (19.0) 1 (reference) 1 (reference) 22 (35.5) 1 (reference) 1 (reference)

C/T 23 (54.8) 2.25 (0.88-5.77) 2.53 (0.96-6.62) 31 (50.0) 1.00 (0.52-1.95) 0.97 (0.50-1.90)

T/T 11 (26.2) 2.35 (0.79-6.98) 2.53 (0.84-7.63) 9 (14.5) 1.28 (0.49-3.38) 1.29 (0.48-3.45)

Dominant model 34 (81.0) 2.28 (0.94-5.57) 2.53 (1.02-6.26)b 40 (64.5) 1.06 (0.56-1.99) 1.03 (0.54-1.95)

Recessive model 11 (26.2) 1.38 (0.58-3.29) 1.41 (0.58-3.43) 9 (14.5) 1.28 (0.53-3.11) 1.31 (0.53-3.23)

aORs were adjusted for gender (male and female), age (<30, 30-49, 50-69, and ≥70 years), and smoking status (non-smoker and smoker).

bSignificant results (p < 0.05) highlighted in bold. DTC, well-differentiated thyroid cancer; SNP, single nucleotide polymorphism; OR, odds ratio;

CI, confidence interval.

166

Combined Genotypes

In order to investigate the joint effect of multiple SNPs on DTC risk, genetic risk scores

(RS) were calculated for each study participant, considering only significant findings on

single SNP analysis. As depicted in Table 6.5, after adjusting for covariates, DTC risk

was more than two and five times higher in individuals bearing, respectively, 2

(adjusted OR = 2.68, 95% CI: 1.56-4.59, p < 0.001) and 3 or more (adjusted OR =

5.02, 95% CI: 2.24–11.24, p = 0.001) risk genotypes (CCNH rs2230641 Val/Ala or

Ala/Ala; ERCC5 rs2227869 Cys/Cys or Ser/Ser; XPC rs2228001 Gln/Gln; MSH6

rs1042821 Glu/Glu; XRCC3 rs861539 Met/Met), when compared to individuals bearing

none or only one of such risk genotypes. Similar associations between RS and TC risk

were also observed on stratification according to histological, gender or age criteria,

after adapting RS calculations to the SNPs significant for each strata (Table 6.5). A

high significance level was observed in most cases (p < 0.001 in approximately 50% of

RS categories) and was even greater if higher RS categories were merged together

(results not shown).

167

Table 6.5. – Risk score (RS) in case and control populations and associated DTC risk (crude and adjusted ORs). Risk scores calculated from

significant results on single SNP analysisa.

Risk score (RS)a. Frequency

p-valueb OR (95% CI) p-value Adjusted OR (95% CI)c p-valueb Controls n (%) Cases n (%)

DTC (all cases) 191 (100) 106 (100)

0-1 114 (59.7) 34 (32.1)

<0.001d


2 64 (33.5) 52 (49.1) 2.72 (1.60-4.63)d <0.001d 2.68 (1.56-4.59)d <0.001d

3/+ 13 (6.8) 20 (18.9) 5.16 (2.33-11.44)d <0.001d 5.02 (2.24-11.24)d <0.001d

Histological type

Papillary TC 152 (100) 78 (100)

0-2 85 (55.9) 17 (21.8)

<0.001d


3 48 (31.6) 44 (56.4) 4.58 (2.36-8.89)d <0.001d 4.55 (2.34-8.84)d <0.001d

4/+ 19 (12.5) 17 (21.8) 4.47 (1.94-10.32)d <0.001d 4.46 (1.92-10.36)d <0.001d

Follicular TC 56 (100) 28 (100)

0-1 24 (42.9) 5 (17.9) 0.029d


2/+ 32 (57.1) 23 (82.1) 3.45 (1.15-10.39)d 0.028d 3.52 (1.12-11.07)d 0.032d

Gender

Female 174 (100) 89 (100)

0-2 114 (65.5) 28 (31.5)

<0.001d


3 51 (29.3) 43 (48.3) 3.43 (1.92-6.13)d <0.001d 3.42 (1.90-6.14)d <0.001d

4/+ 9 (5.2) 18 (20.2) 8.14 (3.31-20.04)d <0.001d 8.01 (3.22-19.92)d <0.001d

168

Age

<50 years 83 (100) 42 (100)

0 26 (31.3) 6 (14.3)

0.020d


1 52 (62.7) 28 (66.7) 2.33 (0.86-6.34) 0.097 2.52 (0.92-6.94) 0.073

2 5 (6.0) 8 (19.0) 6.93 (1.66-28.89)d 0.008d 7.34 (1.72-31.24)d 0.007d

≥50 years 127 (100) 62 (100)

0-1 60 (47.2) 12 (19.4)

<0.001d


2 51 (40.2) 26 (41.9) 2.55 (1.17-5.56)d 0.019d 2.66 (1.21-5.85)d 0.015d

3/+ 16 (12.6) 24 (38.7) 7.50 (3.09-18.18)d <0.001d 7.90 (3.21-19.45)d <0.001d

aFor the purpose of risk score calculations, genotypes presenting significant results on single SNP analysis were attributed a +1 score, risk

score for each participant corresponding to the sum of such scores (+1 in all cases: CCNH rs2230641 Val/Ala or Ala/Ala + ERCC5

rs2227869 Cys/Cys or Ser/Ser + XPC rs2228001 Gln/Gln + MSH6 rs1042821 Glu/Glu + XRCC3 rs861539 Met/Met; +1 in papillary TC:

MUTYH rs3219489 Gln/Gln + ERCC5 rs2227869 Cys/Cys + XPC rs2228001 Gln/Gln + NBN rs1805794 Glu/Glu or Glu/Gln + XRCC3

rs861539 Met/Met; +1 in follicular TC: MLH3 rs175080 Pro/Leu or Leu/Leu + MSH6 rs1042821 Glu/Glu + XRCC2 rs3218536 Arg/Arg; +1 in

female participants: CCNH rs2230641 Val/Ala or Ala/Ala + ERCC5 rs2227869 Cys/Cys + ERCC5 rs17655 Asp/Asp or Asp/His + XPC

rs2228001 Gln/Gln + MSH6 rs1042821 Glu/Glu + XRCC3 rs861539 Met/Met; +1 in participants with age <50 years: XPC rs2228001 Gln/Gln

+ XRCC5 rs2440 C/T or T/T; +1 in participants with age ≥50 years: CCNH rs2230641 Val/Ala or Ala/Ala + ERCC6 rs2228529 Gln/Gln +

RAD51 rs1801321 G/T or T/T + XRCC3 rs861539 Met/Met). bp-value for cases vs. control group determined by two-sided Fisher’s exact test

(whenever 2x2 contingency tables are possible) or χ2 test (remaining cases). cORs were adjusted for gender (male and female), age (<30,

30-49, 50-69, ≥70 years) and smoking status (non-smoker and smoker). dp < 0.05. DTC, well-differentiated thyroid cancer; MAF, minor allele

frequency; OR, odds ratio; CI, confidence interval.

169

Also, in order to investigate the combined effect of different pairs of SNPs on DTC risk,

we performed a paired SNP analysis considering all possible 2x2 combinations of the

DNA repair SNPs included in this study. Overall, 595 SNP-SNP combinations were

tested, 114 (approximately 20%) of which yielded significant results at a 0.05

significance level (results not shown). Considering that such a high number of

hypothesis being tested may result in a considerable number of false positive findings,

a more stringent significance level (p < 0.01) was employed in this analysis, limiting the

number of SNP pairs with significant findings to 15 (approximately 2.5% of all possible

combinations). Such significant findings are depicted in Table 6.6 and also in Figure

6.1. CCNH rs2230641 emerges from Figure 6.1 as the DNA repair SNP most

frequently represented in significant SNP-SNP combinations, both at 0.01 and 0.05

significance levels, followed by RAD51 rs1801321, MLH3 rs175080 and MSH4

rs5745549 (0.01 significance level) or RAD51 rs1801321and XRCC3 rs861539 (0.05

significance level). MMR variants were the most frequently involved as they were

present in 9 of the 15 SNP-SNP combinations that were significant. Also, among

significant findings, 3 intra-pathway SNP combinations were detected: RAD51

rs1801321-XRCC3 rs861539 (HR pathway), MLH3 rs175080-MSH6 rs1042821 and

MSH4 rs5745549-MSH6 rs1042821 (MMR pathway).

Figure 6.1. SNP frequency (%) in SNP-SNP pairs showing significant results at p <

0.01 and p < 0.05 levels. Only SNPs presenting significant results (p < 0.05) on

combined genotype analysis are shown.

170

Table 6.6. – Two-way SNP interactions among DNA repair genes: distribution of

combined genotypes in enrolled populations and associated DTC risk (adjusted ORs).

Only SNPs presenting significant findings (p < 0.01) are shown.

Combined genotype

Frequency DTC risk

Controls n

(%)

Cases n

(%)

p-

valuea

Adjusted OR

(95% CI)b

p-

valuea

CCNH rs2230641 –

RAD51 rs1801321 212 (100) 106 (100)

Val/Val – G/G 58 (27.4) 13 (12.3) 0.037c 1 (Reference)

Val/Val – G/T 64 (30.2) 29 (27.4) 2.10 (0.99-4.45) 0.052

Val/Ala – G/G 15 (7.1) 13 (12.3) 3.77 (1.44-9.87) 0.007d

Val/Ala – G/T 27 (12.7) 20 (18.9) 3.43 (1.46-8.06) 0.005d

Val/Val – T/T 26 (12.3) 18 (17.0) 3.05 (1.29-7.19) 0.011c

Val/Ala – T/T 14 (6.6) 10 (9.4) 3.22 (1.17-8.89) 0.024c

Ala/Ala – G/G

Ala/Ala – G/T

Ala/Ala – T/T

8 (3.8) 3 (2.8) 1.86 (0.42-8.18) 0.414

MUTYH rs3219489 –

CCNH rs2230641 211 (100) 106 (100)

Gln/Gln – Val/Val 77 (36.5) 35 (33.0) 0.018c 1 (Reference)

Gln/Gln – Val/Ala 22 (10.4) 26 (24.5) 2.68 (1.32-5.42) 0.006d

Gln/His – Val/Val 66 (31.3) 23 (21.7) 0.81 (0.43-1.51) 0.500

Gln/His – Val/Ala 30 (14.2) 14 (13.2) 1.05 (0.49-2.23) 0.904

Gln/Gln – Ala/Ala

His/His – Val/Val

Gln/His – Ala/Ala

His/His – Val/Ala

16 (7.6) 8 (7.5) 1.24 (0.48-3.23) 0.660

CCNH rs2230641 –

MLH3 rs175080 195 (100) 106 (100)

Val/Val – Pro/Pro 40 (20.5) 11 (10.4) 0.097 1 (Reference)

Val/Val – Pro/Leu 77 (39.5) 36 (34.0) 1.76 (0.80-3.87) 0.162

Val/Ala – Pro/Pro 14 (7.2) 11 (10.4) 2.60 (0.91-7.41) 0.074

Val/Ala – Pro/Leu 23 (11.8) 21 (19.8) 3.34 (1.35-8.26) 0.009d

Val/Val – Leu/Leu 25 (12.8) 13 (12.3) 1.95 (0.75-5.09) 0.173

Val/Ala – Leu/Leu 11 (5.6) 11 (10.4) 3.69 (1.25-10.90) 0.018c

171

Ala/Ala – Pro/Pro

Ala/Ala – Pro/Leu

Ala/Ala – Leu/Leu

5 (2.6) 3 (2.8) 2.44 (0.48-12.45) 0.284

CCNH rs2230641 –

MSH4 rs5745549 195 (100) 106 (100)

Val/Val – Ser/Ser 132 (67.7) 51 (48.1) 0.009d 1 (Reference)

Val/Val – Ser/Asn 10 (5.1) 9 (8.5) 2.45 (0.93-6.43) 0.070

Val/Ala – Ser/Ser 41 (21.0) 38 (35.8) 2.27 (1.30-3.96) 0.004d

Val/Ala – Ser/Asn

Ala/Ala – Ser/Ser 12 (6.2) 8 (7.5) 1.87 (0.71-4.92) 0.207

MLH3 rs175080 –

RAD51 rs1801321 195 (100) 106 (100)

Pro/Pro – G/G 23 (11.8) 4 (3.8) 0.288 1 (Reference)

Pro/Pro – G/T 24 (12.3) 10 (9.4) 2.88 (0.77-10.78) 0.117

Pro/Leu – G/G 32 (16.4) 18 (17.0) 3.98 (1.14-13.89) 0.031c

Pro/Leu – G/T 46 (23.6) 25 (23.6) 3.59 (1.09-11.81) 0.035c

Pro/Pro – T/T 9 (4.6) 8 (7.5) 5.43 (1.23-23.88) 0.025c

Leu/Leu – G/G 14 (7.2) 6 (5.7) 2.92 (0.68-12.57) 0.151

Pro/Leu – T/T 23 (11.8) 16 (15.1) 4.66 (1.32-16.45) 0.017c

Leu/Leu – G/T 16 (8.2) 15 (14.2) 6.22 (1.70-22.78) 0.006d

Leu/Leu – T/T 8 (4.1) 4 (3.8) 3.55 (0.69-18.15) 0.128

ERCC6 rs4253211 –

RAD51 rs1801321 211 (100) 102 (100)

Arg/Arg – G/G 65 (30.8) 16 (15.7) 0.026c 1 (Reference)

Arg/Arg – G/T 72 (34.1) 42 (41.2) 2.51 (1.28-4.94) 0.007d

Arg/Pro – G/T 21 (10.0) 7 (6.9) 1.53 (0.54-4.29) 0.423

Arg/Arg – T/T 33 (15.6) 21 (20.6) 2.67 (1.22-5.85) 0.014c

Arg/Pro – G/G

Pro/Pro – G/G

Arg/Pro – T/T

Pro/Pro – G/T

20 (9.5) 16 (15.7) 3.65 (1.52-8.78) 0.004d

MLH3 rs175080 –

MSH6 rs1042821 210 (100) 106 (100)

Pro/Pro – Gly/Gly 32 (15.2) 19 (17.9) 0.032c 1 (Reference)

Pro/Pro – Gly/Glu 26 (12.4) 2 (1.9) 0.11 (0.02-0.53) 0.006d

172

Pro/Leu – Gly/Gly 71 (33.8) 36 (34.0) 0.81 (0.40-1.65) 0.561

Pro/Leu – Gly/Glu 35 (16.7) 19 (17.9) 0.94 (0.41-2.13) 0.878

Leu/Leu – Gly/Gly 24 (11.4) 13 (12.3) 0.83 (0.34-2.03) 0.680

Leu/Leu – Gly/Glu 17 (8.1) 9 (8.5) 0.89 (0.33-2.43) 0.819

Pro/Pro – Glu/Glu

Pro/Leu – Glu/Glu

Leu/Leu – Glu/Glu

5 (2.4) 8 (7.5) 3.09 (0.85-11.27) 0.088

MSH4 rs5745549 –

MSH6 rs1042821 210 (100) 106 (100)

Ser/Ser – Gly/Gly 124 (59.0) 60 (56.6) 0.004d 1 (Reference)

Ser/Ser – Gly/Glu 63 (30.0) 24 (22.6) 0.81 (0.46-1.43) 0.467

Ser/Asn – Gly/Glu 15 (7.1) 6 (5.7) 0.83 (0.30-2.28) 0.720

Ser/Asn – Gly/Gly

Ser/Ser – Glu/Glu 8 (3.8) 16 (15.1) 4.63 (1.83-11.69) 0.001d

ERCC6 rs4253211 –

MLH3 rs175080 195 (100) 102 (100)

Arg/Arg – Pro/Pro 51 (26.2) 13 (12.7) 0.067 1 (Reference)

Arg/Arg – Pro/Leu 78 (40.0) 45 (44.1) 2.43 (1.18-5.04) 0.017c

Arg/Pro – Pro/Leu 21 (10.8) 10 (9.8) 2.25 (0.83-6.14) 0.113

Arg/Arg – Leu/Leu 30 (15.4) 21 (20.6) 2.96 (1.28-6.88) 0.012c

Arg/Pro – Pro/Pro

Pro/Pro – Pro/Pro

Arg/Pro – Leu/Leu

Pro/Pro – Pro/Leu

Pro/Pro – Leu/Leu

15 (7.7) 13 (12.7) 4.23 (1.55-11.53) 0.005d

RAD51 rs1801321 –

XRCC3 rs861539 209 (100) 106 (100)

G/G – Thr/Thr 26 (12.4) 7 (6.6) 0.006d 1 (Reference)

G/G – Thr/Met 35 (16.7) 15 (14.2) 1.59 (0.56-4.49) 0.381

G/T – Thr/Thr 29 (13.9) 24 (22.6) 3.10 (1.14-8.44) 0.027c

G/T – Thr/Met 55 (26.3) 14 (13.2) 0.98 (0.35-2.73) 0.967

G/G – Met/Met 11 (5.3) 6 (5.7) 1.99 (0.54-7.41) 0.304

T/T – Thr/Thr 15 (7.2) 5 (4.7) 1.23 (0.33-4.61) 0.759

G/T – Met/Met 12 (5.7) 12 (11.3) 3.77 (1.17-12.13) 0.026c

T/T – Thr/Met 22 (10.5) 15 (14.2) 2.41 (0.83-7.05) 0.108

173

T/T – Met/Met 4 (1.9) 8 (7.5) 7.90 (1.80-34.74) 0.006d

ERCC6 rs2228529 –

MSH4 rs5745549 195 (100) 104 (100)

Gln/Gln – Ser/Ser 102 (52.3) 53 (51.0) 0.009d 1 (Reference)

Gln/Gln – Ser/Asn 6 (3.1) 13 (12.5) 4.77 (1.67-13.61) 0.003d

Gln/Arg – Ser/Ser 71 (36.4) 34 (32.7) 0.82 (0.48-1.43) 0.489

Gln/Arg – Ser/Asn

Arg/Arg – Ser/Ser

Arg/Arg – Ser/Asn

16 (8.2) 4 (3.8) 0.46 (0.14-1.47) 0.190

MSH4 rs5745549 –

XRCC5 rs2440 195 (100) 104 (100)

Ser/Ser – C/C 67 (34.4) 24 (23.1) 0.049c 1 (Reference)

Ser/Ser – C/T 84 (43.1) 50 (48.1) 1.76 (0.97-3.19) 0.063

Ser/Asn – C/T 12 (6.2) 4 (3.8) 1.02 (0.29-3.56) 0.972

Ser/Ser – T/T 27 (13.8) 17 (16.3) 1.86 (0.84-4.12) 0.124

Ser/Asn – C/C

Ser/Asn – T/T 5 (2.6) 9 (8.7) 6.18 (1.83-20.86) 0.003d

MUTYH rs3219489 –

XPC rs2228001 211 (100) 106 (100)

Gln/Gln – Lys/Lys 38 (18.0) 28 (26.4) 0.037c 1 (Reference)

Gln/Gln – Lys/Gln 54 (25.6) 27 (25.5) 0.68 (0.35-1.35) 0.274

Gln/His – Lys/Lys 41 (19.4) 9 (8.5) 0.31 (0.13-0.73) 0.008d

Gln/His – Lys/Gln 48 (22.7) 18 (17.0) 0.55 (0.26-1.16) 0.117

Gln/Gln – Gln/Gln 13 (6.2) 8 (7.5) 0.81 (0.29-2.25) 0.689

Gln/His – Gln/Gln 9 (4.3) 11 (10.4) 1.70 (0.61-4.77) 0.311

His/His – Lys/Lys

His/His – Lys/Gln

His/His – Gln/Gln

8 (3.8) 5 (4.7) 0.91 (0.26-3.16) 0.884

MSH3 rs184967 –

XRCC5 rs1051685 195 (100) 106 (100)

Arg/Arg – A/A 99 (50.8) 70 (66.0) 0.001d 1 (Reference)

Arg/Arg – A/G 32 (16.4) 8 (7.5) 0.34 (0.15-0.80) 0.013c

Arg/Gln – A/A 52 (26.7) 14 (13.2) 0.36 (0.18-0.71) 0.003d

Arg/Gln – A/G

Arg/Arg – G/G 12 (6.2) 14 (13.2) 1.46 (0.62-3.40) 0.387

174

Gln/Gln – A/A

CCNH rs2230641 –

LIG4 rs1805388 212 (100) 106 (100)

Val/Val – Thr/Thr 112 (52.8) 42 (39.6) 0.015c 1 (Reference)

Val/Val – Thr/Ile 32 (15.1) 16 (15.1) 1.36 (0.67-2.75) 0.396

Val/Ala – Thr/Thr 37 (17.5) 36 (34.0) 2.62 (1.45-4.71) 0.001d

Val/Ala – Thr/Ile 18 (8.5) 5 (4.7) 0.73 (0.25-2.11) 0.555

Val/Val – Ile/Ile

Ala/Ala – Thr/Thr

Val/Ala – Ile/Ile

Ala/Ala – Thr/Ile

13 (6.1) 7 (6.6) 1.47 (0.53-4.08) 0.456

ap value for cases vs. control group determined by two-sided Fisher’s exact test

(whenever 2x2 contingency tables are possible) or χ2 test (remaining cases). bORs

were adjusted for gender (male and female), age (<30, 30-49, 50-69, ≥70 years) and

smoking status (non-smoker and smoker). cp < 0.05. dp < 0.01.

Finally, haplotype analysis was applied to SNPs located in the same chromosome arm,

since these are likely to segregate together. According to such criteria, it was possible

to establish 8 blocks of DNA repair SNPs, of which only one, located on chromosome

5q and comprising 6 SNPs (CCNH rs2230641, CDK7 rs2972388, MSH3 rs26279,

MSH3 rs184967, XRCC4 rs1805377 and XRCC4 rs28360135), revealed significant

associations with DTC (Table 6.7): two different allele combinations were associated

with a significantly decreased DTC risk, when compared to the most frequent

combination of chromosome 5q SNPs (adjusted OR1 = 0.26, 95% CI: 0.08-0.87, p =

0.030; adjusted OR2 = 0.15, 95% CI: 0.03-0.72, p = 0.019). Haplogroup analysis

comprising all SNPs under study could also prove useful to understand the joint effect

of the variants since it would better reflect the real context situation (where different

DNA repair proteins interact with each other) but could not be performed because,

considering the high number of SNPs under study, the frequency of each specific allele

combination would be too low for meaningful results to be obtained.

175

Table 6.7. – Haplotypes comprising SNPs located in the same chromosome arm and corresponding DTC risk (adjusted ORs). Only haplotypes

presenting significant results are shown.

Haplotype Adjusted OR

(95% CI) p-valuea

Chromosome 5q

CCNH

rs2230641

CDK7

rs2972388

MSH3

rs26279

MSH3

rs184967

XRCC4

rs1805377

XRCC4

rs28360135 0.015

Val A Thr Arg G Ile 1.00 (Reference)

Val A Ala Arg G Ile 0.26 (0.08-0.87) 0.03

Val G Ala Gln G Ile 0.15 (0.03-0.72) 0.019

ap < 0.05. DTC, well-differentiated thyroid cancer; OR, odds ratio; CI, confidence interval.

176

Discussion

In order to further characterize the potential contribution of DNA repair SNPs to DTC

susceptibility, we aggregated and reanalysed the data from our previously published

case-control studies (14-18) performed on a Caucasian Portuguese population.

A significant risk increase was observed, after adjustment for age, gender and smoking

status, in CCNH rs2230641 heterozygotes and variant allele carriers, in MSH6

rs1042821 variant allele homozygotes (codominant and recessive model), in XRCC3

rs861539 variant allele homozygotes (recessive model) and in XPC rs2228001 variant

allele homozygotes (recessive model), while the heterozygous ERCC5 rs2227869

genotype was associated with a borderline risk reduction. Except for XPC rs2228001,

which is a new finding emerging from this reanalysis because the recessive model of

inheritance had not been applied in the original study, such results are fundamentally

similar to those reported on the original studies despite, on reanalysis, data was

restricted to DTC cases and corresponding controls. A role for these variants

specifically on well-differentiated forms of TC is thus apparent from this reanalysis. As

these findings have been discussed in detail in the original studies, they will be

discussed here only briefly, with emphasis on new data published since then.

XRCC3 participates in HR to maintain chromosome stability and repair DNA damage

and is therefore a highly suspected candidate gene for cancer susceptibility. The

XRCC3 rs861539 has been the most studied genetic variant of XRCC3 gene,

especially because it is located in a functional relevant domain of the protein, in an

interaction region with other proteins such as RAD51 (22, 32). The presence of this

variant may affect the structure of this DNA repair protein and lead to a deficiency in

the HR pathway. As a result, the HR pathway may be compromised, shifting the repair

mechanism to NHEJ, promoting chromosome instability and disturbing the cellular

repair capacity (33). The potential contribution of XRCC3 rs861539 to cancer

susceptibility has been widely addressed: while conflicting evidence exists, several

large meta-analyses strongly support a positive association with cancer susceptibility,

namely breast (34-36) and bladder cancer (36-38), among others. In the particular

context of thyroid cancer, interestingly, multiple studies (22, 39-43), including a meta-

analysis (44), have suggested the XRCC3 rs861539 variant T allele and/or, in

particular, the TT homozygous genotype to be associated with increased risk of TC or,

more specifically, PTC. In another meta-analysis (45) such association was also

detected but only in Caucasian populations. Therefore, despite studies reporting no

177

significant association also exist (46, 47), the vast majority of available evidence

supports our results and suggests a role for XRCC3 rs861539 in DTC susceptibility.

To the best of our knowledge, none of the remaining SNPs presenting significant

results on overall analysis has been evaluated in the context of DTC (or TC)

susceptibility.

XPC codes for a DNA binding protein that acts forming the distortion-sensing

component of NER by binding tightly with another important NER protein, HR23B, to

form a stable XPC-HR23B complex, thus playing a central role in the process of early

damage recognition (48, 49). XPC-HR23B complex can recognize a variety of DNA

adducts formed by exogenous carcinogens and binds to the DNA damage sites.

Therefore, it may play a role in decreasing the toxic effects of such carcinogens and its

deficiency may interact with carcinogen exposure (50). XPC is also involved in DNA

damage-induced cell cycle checkpoint regulation and apoptosis, removal of oxidative

DNA damage and redox homeostasis (49, 51). XPC rs2228001 (an A-to-C transition in

exon 15) leads to a substitution of glutamine for lysine in codon 939 (Lys939Gln) and is

located in the domain interacting with the transcription factor IIH (TFIIH) complex (50,

52-55), initiating the global genome NER pathway. XPC rs2228001 is one of the most

extensively studied NER pathway SNPs, as numerous case-control association studies

and meta-analyses have been performed to investigate its potential role on cancer

predisposition. In line with our data for DTC, a modest but consistent association of the

Gln/Gln homozygous genotype with overall cancer risk is apparent from two of the

three meta-analyses that pool data from different cancer types (56-58). Evidence from

these and other cancer site-specific meta-analyses is stronger for lung (53, 56-60),

bladder (54, 56, 61, 62) and colorectal cancer (CRC) (56, 58, 63, 64), but also exists

for other cancer types such as upper digestive system cancer (65) and hepatocellular

carcinoma (50, 66). XPC rs2228001 genotype has also been found to correlate with

survival of hepatocellular patients (66), with XPC mRNA expression levels (60, 66, 67),

with drug-induced toxicity in cancer patients treated with platinum-based

chemotherapeutic agents (e.g., cisplatin) (68, 69), with sensitivity of lung squamous cell

carcinoma patients to chemotherapy (67) and to interfere with the capacity to repair

DNA lesions induced by, e.g., benzo(a)pyrene (70-72), gamma-radiation (70), X-rays

(73), UV radiation (74), aflatoxin B1 (50) and meat-derived carcinogens (75). Overall,

evidence strongly suggests that XPC rs2228001 genotype is associated with altered

DNA repair capacity, establishing ground for a putative role of this SNP in cancer

susceptibility.

178

The MSH6 gene (mutS homolog 6) is a member of a set of genes known as the

mismatch repair (MMR) genes. MSH6 integrates the MutS complex, a sensor of

genetic damage that, besides its role in the repair of replication errors, cooperates with

other DNA repair and damage-response signalling pathways to allow for cell cycle

arrest, DNA repair and/or apoptosis of genetically damaged cells. Several MSH6

mutations have been identified and suggested as causative in Lynch syndrome (LS)

patients (76-80). Despite TC is not part of the usual LS spectrum, the effect of MSH6 in

TC susceptibility has previously been explored (81, 82). MSH6 rs1042821 has also

been frequently investigated in the context of cancer susceptibility, mostly with

inconclusive findings (83-90). Consistent with our results, MSH6 rs1042821 has

previously been associated with increased CRC risk (91-93), highly malignant bladder

cancer (94), pancreatic cancer (95) and triple negative breast cancer (TNBC) (96). On

the contrary, the T allele (97) and the CT heterozygous genotype (98) have been

associated with decreased colorectal and hepatocellular carcinoma, respectively. The

only meta-analysis concerning the role of MSH6 rs1042821 on cancer predisposition

that we are aware of is also inconclusive (99). Despite plausible, a potential role for

MSH6 rs1042821 on cancer predisposition (DTC, in particular) remains elusive. Further

well-powered studies are needed to clarify this issue.

The role of CCNH rs2230641 on cancer predisposition has only seldom been

evaluated: in agreement with our results, a significantly increased bladder cancer risk

in ever smokers has been reported for C allele carriers (100) but, on the contrary, such

genotype has also been associated with a significantly decreased risk of chronic

leukaemia (101). Most other studies, namely in oesophageal (102), bladder (103),

biliary tract (104) and renal cell carcinoma (105), as well as in oral premalignant lesions

(106) have been inconclusive. Interestingly, the pharmacogenomic implications of

CCNH rs2230641 on the outcome of platinum-based chemotherapy have also been

evaluated, results supporting a role for CCNH rs2230641 on the response to DNA

damaging agents: the presence of the CCNH rs2230641 variant C allele has been

associated with longer survival in non-small cell lung cancer (NSCLC) patients

receiving platinum-based chemotherapy (107) and with increased incidence and

severity of oxaliplatin-induced acute peripheral neuropathy in digestive tract cancer

patients undergoing oxaliplatin-based chemotherapy (108). Similarly, increased risk of

severe oxaliplatin-induced acute peripheral neuropathy was observed by Custodio et al

(109) in high-risk stage II and stage III colon cancer patients homozygous for the C

allele, submitted to oxaliplatin-based adjuvant chemotherapy. CCNH codes for a highly

179

conserved cyclin protein that participates in several cellular processes such as the

NER pathway, cell cycle regulation and receptor phosphorylation, among others (48,

110). Although data on the functional relevance of rs2230641 is lacking, the pleiotropic

effects of CCNH confer biological plausibility to our hypothesis that CCNH variants may

be involved in cancer susceptibility.

Finally, ERCC5, also known as XPG, is located on chromosome 13q22-q33 (111) and

comprises 15 exons (112, 113). It encodes a structure-specific endonuclease that has

multiple functions during NER (114), reason why defects in this gene can impair DNA

repair resulting in genomic instability and carcinogenesis (115). In fact, only a few

studies have considered the putative contribution of ERCC5 rs2227869 to cancer

susceptibility, most being inconclusive. Interestingly, the only significant findings

reported thus far are in line with those reported here, suggesting a protective role for

the heterozygous genotype: Hussain et al (116) reported a significant reduction in

stomach cancer risk in heterozygous genotype individuals and a similar, despite

nonsignificant, trend has also been independently observed for melanoma (117) and

for squamous cell carcinoma of the head and neck (SCCHN) (118). More importantly,

in the only meta-analysis performed to date (119), a decrease in cancer risk in ERCC5

rs2227869 heterozygotes (and for the C allele) has also been reported.

Many of these (and other) SNPs also presented significant findings on stratifying data

according to histotype, gender and age: on histological stratification, significant

associations were observed between XRCC3 rs861539, XPC rs2228001, ERCC5

rs2227869, MUTYH rs3219489 and NBN rs1805794 and papillary TC, while MSH6

rs1042821, MLH3 rs175080 and XRCC2 rs3218536 were associated with follicular TC.

XRCC3 rs861539, XPC rs2228001, MSH6 rs1042821, CCNH rs2230641, ERCC5

rs2227869 and ERCC5 rs17655 were associated with DTC in the female subset while

no association was observed in males. Finally, XPC rs2228001 and XRCC5 rs2440

were associated with DTC in participants younger than 50 years, while, in participants

aged 50 or more years, the DTC-associated SNPs included XRCC3 rs861539, CCNH

rs2230641, ERCC6 rs2228529 and RAD51 rs1801321.

It is unclear whether these findings (and which among these) truly represent group-

specific effects or whether they simply reflect the overall effect on the largest groups

(i.e., when group sizes are unbalanced, e.g., papillary TC vs follicular TC, female vs

male) and the corresponding lack of power to detect an effect on the smallest groups.

Also, due to the low sample size on each strata, some of these results may simply

represent incident findings (type I errors). XRCC3 rs861539, for example, has been

180

previously associated with papillary TC (22, 39, 40) – in line with our results – but not

with follicular TC. An effect of XRCC3 rs861539 genotype in follicular TC cannot,

however, be excluded since follicular TC is much less frequent than papillary TC and

these studies may have been underpowered to detect such effect. Also, Su et al (120)

have demonstrated the homozygous genotype of this SNP to be associated with breast

cancer, the association being stronger in women younger than 55 years, with earlier

first menarche or with latter menopause. This suggests an oestrogen-potentiated

genetic effect, compatible with our own observation of increased DTC risk in XRCC3

rs861539 TT homozygotes among females but not among males. Further, the

involvement of CCNH, through a cyclin-activated kinase complex, in oestrogen

receptor phosphorylation (48) provides a possible rationale for our own observation of

an association of the CCNH rs2230641genotype with DTC among females but not

among males. Finally, the association of MSH6 rs1042821with DTC, observed in this

study for female but not male individuals, is compatible with the growing evidence

placing DTC as an oestrogen-associated cancer (121-124) and implicating MSH6 in

such cancers (78, 125-129). These selected examples highlight the plausibility of the

existence of group-specific genetic effects. Overall, such histotype, gender and age

specificities in DTC susceptibility are likely since 1) papillary and follicular TC represent

distinct entities, with histotype-specific molecular profiles (e.g., BRAF mutations and

RET/PTC rearrangements in PTC, RAS mutations and PAX8/PPAR translocations in

FTC) (130); 2) important gender differences exist in the incidence of DTC (i.e., DTC is,

as previously stated two to four times more frequent in women than in men) (1, 2); and

3) DTC presents some age specificities, uncommon in other types of cancer (DTC is

one of the most common malignancies in adolescent and young adults, the median age

at diagnosis being lower than that for most other types of cancer) (1, 2). Further well-

powered studies are urgently needed to clarify these results and thus establish which

of these SNPs, if any, represents true group-specific susceptibility biomarkers.

Considering the multifactorial nature of DTC aetiology and the probable involvement of

multiple genetic factors, alone or in combination, in DTC susceptibility, we undertook a

combined genotype analyses to investigate the joint effect of multiple SNPs on DTC

risk. When combining all risk genotypes significant at single SNP analysis into a unique

unbalanced risk score, a clear-cut gene-dosage effect between the number of risk

genotypes (unbalanced risk score) and DTC risk was observed, both on global analysis

(considering all DTC cases and corresponding controls) and after stratification

according to histological, gender and age criteria. This is biologically plausible since the

181

different DNA repair proteins physically and functionally interact with each other, within

the same or different DNA repair pathways, establishing ground for additive or even

multiplicative effects of different SNPs on DNA repair activity and, hence, cancer risk.

Such polygenic approach to assess the cumulative effects of multiple genetic variants

on cancer risk has previously been employed (27, 107, 131, 132), supporting its

usefulness and clinical potential.

To investigate the effect of specific DNA repair SNP combinations on DTC risk, all

possible 2x2 combinations were tested on paired SNP analysis, yielding fifteen SNP

pairs with p < 0.01. Multiple interactions between SNPs from different DNA repair

pathways and, even, other DNA damage response proteins have previously been

reported (39, 42, 66, 87), providing a rationale for such approach. Of notice, CCNH

rs2230641 was the most frequently represented DNA repair SNP in such significant

combinations, both at 0.01 and 0.05 significance levels, a finding that is compatible

with the pleiotropic role of CCNH in DNA damage repair, cell cycle regulation and

receptor phosphorylation (48, 110). More importantly, the contribution of MMR variants

to the joint effect of DNA repair SNPs on DTC risk is evident from our results, as they

were present in 9 of the 15 SNP pairs presenting significant findings. Besides its critical

role in post-replication repair (through recognition and repair of base-base mispairs and

insertion/deletion loops that arise during replication), the MMR pathway cooperates

with other repair pathways in the recognition and subsequent repair of DNA damage

induced by IR, UV light, oxidative stress or genotoxic chemicals (e.g., oxidative lesions,

double strand breaks, pyrimidine dimers and inter-strand crosslinks) and contributes to

damage-induced cytotoxicity through downstream signalling for cell cycle arrest and

apoptosis (133-135). Therefore, considering the large spectre of action of the MMR

pathway, an elevated number of interactions between MMR and other DNA repair

SNPs is expected. Such hypothesis, in line with our findings, has been recently

strengthened by a report (136) associating SNPs from different DNA repair pathways

with CRC in Lynch syndrome patients, a cancer predisposition condition originated by

germline MMR mutations. Finally, among SNP pairs presenting significant findings in

this study, three are intra-pathway combinations involving either HR or MMR pathway

SNPs. The joint effects of MLH3 rs175080-MSH6 rs1042821 and MSH4 rs5745549-

MSH6 rs1042821 (MMR pathway) SNP combinations were reported and discussed in

our original study (18). The joint effect of RAD51 rs1801321 and XRCC3 rs861539 (HR

pathway) on cancer risk has been previously reported for breast cancer (137), in line

182

with our results, and may be of particular relevance for DTC since the formation of

radiation damage-induced RAD51 foci requires functional XRCC3 (138).

Finally, on applying haplotype analysis to SNPs that are located in the same

chromosome arm (thus likely to segregate together), one block of DNA repair SNPs

located on chromosome 5q (comprising CCNH rs2230641, CDK7 rs2972388, MSH3

rs26279, MSH3 rs184967, XRCC4 rs1805377 and XRCC4 rs28360135) was

associated with DTC risk in our study. Such results further suggest an independent or

interactive effect of these SNPs on DTC predisposition.

Overall, our results suggest that DNA repair SNPs across different pathways may

contribute to DTC predisposition, possibly exerting cumulative effects. This is of

relevance since the estimated high heritability of DTC is only partially explained, even

when considering the contribution of several GWAS recently performed. Gene-gene

and gene-environment interactions have been hypothesised to play an important role

so their identification and in-depth study is highly desirable to explain the “missing”

heritability of DTC. However, the results presented here should be regarded only as

proof of concept and must therefore be validated through replication in larger

independent populations. Future studies should also be designed with the intention of

accounting for environmental factors such as IR exposure and iodine deficiency (and

their potential interaction with genetic factors). In addition, they should be sufficiently

powered to allow other, less frequent but potentially relevant SNPs, to be studied and

to allow more sophisticated and conclusive gene-gene interaction analysis to be

performed. Finally, in order to strengthen our preliminary findings, the functional

significance of these SNPs should be further investigated as well as their potential

association with mutational events involved in DTC carcinogenesis (e.g., BRAF

mutations and RET/PTC rearrangements).

Funding

This work was supported by FCT – Fundação para a Ciência e a Tecnologia

(Portuguese Foundation for Science and Technology) through Project

UID/BIM/00009/2019-Centre for Toxicogenomics and Human Health.

Acknowledgments

The authors warmly acknowledge the generous collaboration of patients and controls in

this study.

183

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Chapter VII

Micronuclei Formation upon Radioiodine Therapy for Well-Differentiated Thyroid

Cancer: The Influence of DNA Repair Genes Variants

[Research Paper]


Santos LS, Gil OM, Silva SN, Gomes BC, Ferreira TC, Limbert E, Rueff J (2020).

Micronuclei Formation upon Radioiodine Therapy for Well-Differentiated Thyroid

Cancer: The Influence of DNA Repair Genes Variants. Genes. 11(9): 1083. (DOI:

10.3390/genes11091083)




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199

Chapter VII - Micronuclei Formation upon Radioiodine Therapy for Well-

Differentiated Thyroid Cancer: The Influence of DNA Repair Genes Variants

Abstract

Radioiodine therapy with 131I remains the mainstay of standard treatment for well-

differentiated thyroid cancer (DTC). Prognosis is good but concern exists that 131I-

emitted ionizing radiation may induce double-strand breaks in extra-thyroidal tissues,

increasing the risk of secondary malignancies. We, therefore, sought to evaluate the

induction and 2-year persistence of micronuclei (MN) in lymphocytes from 26 131I-

treated DTC patients and the potential impact of nine homologous recombination (HR),

non-homologous end-joining (NHEJ), and mismatch repair (MMR) polymorphisms on

MN levels. MN frequency was determined by the cytokinesis-blocked micronucleus

assay while genotyping was performed through pre-designed TaqMan® Assays or

conventional PCR-restriction fragment length polymorphism (RFLP). MN levels

increased significantly one month after therapy and remained persistently higher than

baseline for 2 years. A marked reduction in lymphocyte proliferation capacity was also

apparent 2 years after therapy. MLH1 rs1799977 was associated with MN frequency

(absolute or net variation) one month after therapy, in two independent groups.

Significant associations were also observed for MSH3 rs26279, MSH4 rs5745325,

NBN rs1805794, and tumour histotype. Overall, our results suggest that 131I therapy

may pose a long-term challenge to cells other than thyrocytes and that the individual

genetic profile may influence 131I sensitivity, hence its risk-benefit ratio. Further studies

are warranted to confirm the potential utility of these single nucleotide polymorphisms

(SNPs) as radiogenomic biomarkers in the personalization of radioiodine therapy.

Key words: thyroid cancer; Iodine-131; chromosome-defective micronuclei; DNA repair;

micronucleus assay; single nucleotide polymorphism; pharmacogenomic variants;

pharmacogenetics; precision medicine

Introduction

Thyroid cancer (TC) is the most common endocrine malignancy, accounting for

approximately 2.1% of cancers diagnosed all over the world. TC incidence is about two

to four times higher in women than in men and is one of the most common

malignancies in adolescent and young adults (ages 15–39 years), with the median age

at diagnosis being lower than that for most other types of cancer (1-3). TC incidence

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has been steadily increasing, over the last three decades (1), most likely because of

“surveillance bias” and overdiagnosis resulting from increased detection of small

stationary lesions of limited clinical relevance. A true rise in the number of TC cases

(e.g., due to increasing exposure to ionizing radiation (IR) from medical sources) is,

however, also possible (2-4).

Papillary (PTC) and follicular (FTC) thyroid carcinoma represent 85–90% and 5–10% of

TC cases, respectively. These tumour histotypes retain their morphologic features,

being often referred to as differentiated thyroid carcinoma (DTC) (3, 4). The best-

established modifiable risk factor for DTC is IR exposure during childhood and

adolescence (radioiodines including 131I, X-radiation, -radiation) (2-5) and the standard

treatment consists of surgical resection (total or near-total thyroidectomy) accompanied

by post-thyroidectomy radioiodine (RAI) therapy and TSH suppression (3, 4). The

majority of DTC cases is indolent in nature, iodine-avid, and responds favourably to

standard therapy. Overall prognosis is thus generally good, translating into high long-

term survival and low disease-specific mortality (4).

The widespread use of RAI therapy in the management of DTC relies on the ability of

131I to be preferentially taken up and concentrated in normal or neoplastic thyroid

follicular cells, taking advantage of these cells’ specialized mechanism for iodide

uptake and accumulation (3, 6, 7). Thyrocyte-accumulated 131I undergoes [β and ]

decay and releases high-energy electrons that inflict devastating DNA damage locally.

Thyroid cell death through radiation cytotoxicity ensues, allowing for the ablation of

remnant normal thyroid tissue and the eradication of any residual tumour foci (3, 6).

Unfortunately, since other tissues may also concentrate 131I, its DNA damaging effects

may not be limited to the thyroid gland, increasing the risk of RAI-associated secondary

malignancies such as soft tissue tumours, colorectal cancer, salivary tumours, and

leukaemia (3, 7). Since the rising incidence of TC is mostly driven by increased

detection of stationary subclinical lesions, concern exists that DTC overdiagnosis may

result in potentially harmful overtreatment (2). Indeed, if we consider the indolent

behaviour of the disease, its long-term survival rate, and its mean age of diagnosis,

such therapy-related morbidity may not be justified, as most patients will have many

years to experience its negative effects (2). The revised American Thyroid Association

(ATA) clinical practice guidelines for the management of DTC (8) reflect such concern

for the first time, recommending a more cautious diagnosis and treatment approach in

order to reduce RAI use (hence, radiation exposure) particularly in younger ages. This

includes, for example, more stringent criteria for diagnosis upon nodule detection,

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molecular-based risk stratification for improved treatment decisions, personalized

disease management and long-term surveillance strategies and, most importantly, use

of lower RAI doses (30–50 mCi) in patients with low-risk DTC (2, 8, 9).

The most relevant types of DNA damage inflicted upon IR exposure are double-strand

breaks (DSBs). Such lesions are predominantly processed by DNA repair enzymes of

the homologous recombination (HR) and non-homologous end-joining (NHEJ) repair

pathways, despite mismatch repair (MMR) pathway enzymes have also been

implicated (10, 11). The activity of such DNA repair enzymes determines the capacity

of cells to repair DSBs which, in turn, influences their sensitivity to IR. Lower DNA

repair capacity, therefore, increases the extent of IR-induced DNA damage, increasing

both the likelihood of cell death through IR-induced cytotoxicity and the likelihood of

malignant transformation upon IR exposure (12, 13).

Single nucleotide polymorphisms (SNPs) in DNA repair enzymes across these three

pathways have been identified and some have been demonstrated to affect the DNA

repair capacity (14, 15). Such DNA repair SNPs may therefore modulate sensitivity to

IR and many have indeed been associated with TC or, more specifically, DTC

susceptibility (for which IR exposure is the best-established risk factor) (16-21). It is

likely that such functional DNA repair SNPs, through interference with the extent of IR-

induced DSBs on thyrocytes, could influence the cytotoxic potential of RAI therapy,

hence its efficacy on DTC treatment. Likewise, through a similar effect on other cells

that take up and concentrate 131I, such SNPs could also modify the risk of secondary

malignancies, hence the safety of RAI therapy. Identifying these variants is, therefore,

an important challenge with clinical relevance. However, to our knowledge, the issue

has not been addressed in prior studies.

We have previously demonstrated that therapy with 70 mCi 131I in DTC patients is

consistently associated with increased DNA damage levels in peripheral lymphocytes

(22, 23). With this study, we aimed to confirm, through the use of the cytokinesis-

blocked micronucleus (CBMN) assay, our prior findings in a new group of DTC patients

submitted to RAI therapy with 100 mCi. Further, we sought to extend our analysis at 24

months after 131I administration so that the long-term persistence of 131I-induced DNA

damage could be better characterized. Finally, the potential influence of HR, NHEJ,

and MMR polymorphisms on the micronuclei (MN) frequency in RAI-treated DTC

patients was also investigated.

Understanding the role of repair SNPs on the extent and persistence of 131I-induced

DNA damage will contribute to the identification of genetic biomarkers that influence

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the individual response to 131I-based RAI therapy and thus modulate the risk-benefit

ratio of RAI therapy in DTC patients. Such efforts may provide the basis for improved,

personalized, therapeutic decisions in the context of DTC therapy, with impact on

disease prognosis and patient safety.


Study population

Twenty-six DTC patients proposed for radioiodine therapy at the Department of

Nuclear Medicine of the Portuguese Oncology Institute of Lisbon (Portugal) were

selected according to criteria published elsewhere (22). All participants were treated

according to current practice, consisting of total thyroidectomy followed by oral

administration of 131I, 70 mCi (15 patients) or 100 mCi (11 patients), to ablate thyroid

remnant cells. Patients were followed for two years unless they had to be submitted to

further treatment. In such cases, patients were no longer elective for cytogenetic

analysis and had to be excluded from further analysis. A mixed cross-sectional and

longitudinal study design was used, respectively, for comparisons among genotypes or

dose groups at each time point and across different time points. In the latter case, pre-

treatment values allowed each patient to serve as his own control.

To characterize the study population and account for potential confounding factors, all

participants were interviewed and completed a detailed questionnaire covering

standard demographic characteristics, personal and family medical history, lifestyle

habits, and prior IR exposure. For the purpose of smoking status, former smokers who

had quit smoking at least 2 years prior to diagnosis were considered as non-smokers.

Clinical and pathological examination was also performed.

Peripheral blood samples were collected from each patient into both 10 mL heparinized

tubes (for cytogenetic analysis) and citrated tubes (for genotype analysis). For

cytogenetic analysis, blood samples were drawn (1) prior to 131I administration as well

as 1, 6, and 24 months after therapy in patients submitted to a 70 mCi dose and (2)

prior to 131I administration as well as 1 and 3 months afterward in patients submitted to

a 100 mCi dose. For genotype analysis, blood samples were stored at -80ºC until

further use.

All subjects gave their informed consent for inclusion before they participated in the

study. The study was conducted in accordance with the Declaration of Helsinki, and the

protocol was approved by the Ethics Committee of Instituto Português de Oncologia

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Francisco Gentil (GIC/357) and by the Ethics Committee of Faculdade Ciências

Médicas (CE-5/2008).

Genotype analysis

Genomic DNA was isolated from blood samples using the commercially available

QIAamp® DNA mini kit (QIAamp® DNA mini kit; Qiagen GmbH, Hilden, Germany),

according to the manufacturer’s recommendations. The fluorimetric Quant-iT™

Picogreen® dsDNA Assay Kit (Invitrogen, Waltham, MA, USA) was used to quantify

and ensure uniformity in DNA concentration (2.5 ng/µL).DNA samples were kept at -

20ºC until further use.

SNPs were selected from those already analysed by our team in a cohort of 106 DTC

patients, according to selection criteria published elsewhere (18-21). Due to sample

size limitations, only SNPs presenting a minor allele frequency (MAF) > 0.15 in the

original pool of patients were considered. MLH3 rs175080 was excluded a posteriori for

insufficient genotype frequency (n ≤ 1) in at least one of the 131I dose groups (Table

S7.1). Overall, a total of 9 DNA repair SNPs across 3 DNA repair pathways (HR,

NHEJ, and MMR) were considered for further analysis (Table 7.1).

Genotyping was performed mostly by real-time polymerase chain reaction (RT-PCR):

amplification and allelic discrimination were carried out on a 96-well ABI 7300 Real-

Time PCR system thermal cycler (Applied Biosystems; Thermo Fisher Scientific, Inc.,

Waltham, MA, USA), following the manufacturer’s instructions, with the use of the

commercially available TaqMan® SNP Genotyping Assays (Applied Biosystems)

identified in Table 7.1. For XRCC3 rs861539 (HR pathway), genotyping was performed

by conventional PCR-restriction fragment length polymorphism (RFLP) techniques.

Primer sequences, PCR, and digestion conditions as well as expected electrophoretic

patterns have been described (19). To confirm genotyping and ensure accurate results,

inconclusive samples were reanalysed and genotyping was repeated in 10–15% of

randomly chosen samples, with 100% concordance.

Cytogenetic analysis

The cytokinesis-block micronucleus assay (CBMN) was used to analyse DNA damage

and conducted according to standard methods. The methodology was performed and

published as described previously (22-24). The frequency of binucleated cells carrying

micronuclei (BNMN), defined as the number of cells with MN per 1000 binucleated

lymphocytes, is expressed as a count per thousand (‰). The Cytokinesis-Block

204

Proliferation Index (CBPI) was determined according to the formula CBPI = [MI + 2MII

+ 3(MIII + MIV)]/N, where MI-MIV correspond to the number of human lymphocytes

with one to four nuclei, respectively, and N is the total number of cells analysed.


amino acid changes, minor allele frequency, and Applied Biosystems (AB) assay used

for genotyping.

Gene Location dbSNP

Cluster ID

(rs no.)

Base

Change

Amino acid

Change

MAF

(%)a

AB Assay ID



MSH4 1p31.1 rs5745325 G → A Ala97Thr 26.0 C___3286081_10

PMS1 2q32.2 rs5742933 G → C --b 23.4 C__29329633_10


RAD51 15q15.1 rs1801321 G → T --b 33.2 C___7482700_10

NBN 8q21.3 rs1805794 G → C Glu185Gln 34.7 C__26470398_30

XRCC3 14q32.33 rs861539 C → T Thr241Met 29.0 --d

XRCC5 2q35 rs2440 C → T --c 36.3 C___3231046_10

aMAF, minor allele frequency, according to the Genome Aggregation Database

(gnomAD), v2.1.1, available at https://gnomad.broadinstitute.org/. bSNP located on 5′

UTR. cSNP located on 3′ UTR. dnot applicable (genotyping performed by PCR-RFLP).

SNPs, single nucleotide polymorphisms.


All analyses were done with SPSS 22.0 (IBM SPSS Statistics for Windows, version

22.0, IBM Corp, Armonk, NY, USA) except for deviation of genotype distributions from

Hardy–Weinberg equilibrium (HWE) and linkage disequilibrium (LD) analysis between

SNPs on the same chromosome, which were performed with SNPstats (25).

Categorical variables, presented as frequencies and percentages, were compared

between dose groups and with the original cohort of DTC patients by the Pearson’s

Chi-square (χ2) test or the two-sided Fisher’s exact test whenever 2x2 contingency

tables were possible. For continuous variables (BNMN frequency, CBPI, and their net

variation from baseline), presented as mean ± standard deviation, the normality and

homogeneity of variances were evaluated by the Shapiro-Wilk and Levene tests,

https://gnomad.broadinstitute.org/

205

respectively. Longitudinal comparisons were performed by the paired sample t test

(whenever a normal distribution could not be excluded) or the Wilcoxon signed-rank

test (remaining cases) while the parametric Student t test (normal distributions) or the

nonparametric Mann-Whitney U test (non-normal distributions) for independent

samples were used for cross-sectional comparisons between the two 131I dose groups

and between different gender, age class, smoking status, histological type of tumour,

and genotype categories.

Variable transformation was considered, when practically useful: DTC patients were

dichotomized according to age, with the cut-off point being defined as the median age

of all patients included (54 years). Due to limited sample size (hence, low frequency of

homozygous variant genotypes), a dominant model of inheritance was assumed for all

SNPs. Moreover, the net variation in BNMN frequency (i.e., therapy-induced BNMN)

was calculated by subtracting the background (pre-treatment) BNMN frequency from

the corresponding post-treatment values.

This is an exploratory ‘proof of concept’ study, not a conclusive final one. As such, the

Bonferroni adjustment was deemed as not necessary as it is too conservative.

Furthermore, the complement of the false-negative rate β to compute the power of a

test (1-β) was not taken into account at this stage since larger studies are needed to

change this preliminary study into a confirmatory one. Statistical significance was set at

p < 0.05.

Results

Characteristics of the study population

A general description of the study population is presented in Table 7.2. The age of DTC

patients submitted to 131I therapy ranged from 32 to 73 years, with a mean of 52.54 ±

11.62 years. As expected, female patients (88.5%, n = 23) greatly outnumbered male

patients (11.5%, n = 3) and papillary carcinoma cases (PTC, 69.2%, n = 18) were also

more frequent than follicular ones (FTC, 30.8%, n = 8), in agreement with gender and

histotype distributions commonly reported for DTC (1, 2, 4). Overall, 15.4% (n = 4) of

patients were smokers. No significant differences in patient age, gender, histological

type of tumour, and smoking status were observed between groups submitted to

different 131I doses (Table 7.2) nor between any of these groups (separated or together)

and our original DTC population (18).

206

Table 7.2. General characteristics for differentiated thyroid carcinoma (DTC) patients

treated with 70 mCi (n = 15) and 100 mCi (n = 11) 131I.

Characteristics Study Population

n (%)

70 mCi

n (%)

100 mCi

n (%) p Valuec

Gender

Male 3 (11.5) 1 (6.7) 2 (18.2) 0.556

Female 23 (88.5) 14 (93.3) 9 (81.8)

Agea 52.54 ± 11.62b 52.07 ± 10.26b 53.18 ± 13.76b 0.815

≤54 14 (53.8) 8 (53.3) 6 (54.5) 1.000

>54 12 (46.2) 7 (46.7) 5 (45.5)

Smoking habits

Non-smokers 22 (84.6) 13 (86.7) 9 (81.8) 1.000

Smokers 4 (15.4) 2 (13.3) 2 (18.2)

Histology

Papillary 18 (69.2) 10 (66.7) 8 (72.7) 1.000

Follicular 8 (30.8) 5 (33.3) 3 (27.3)

aFor age categorization purposes, the median age of all patients included in the study

(54 years) was defined as the cut-off point. bmean ± S.D. cp value for 70 mCi versus

100 mCi groups determined by two-sided Fisher’s exact test (gender, smoking habits,

and age categories) or Student t test (age mean ± S.D.).

Cytogenetic data

The frequency of BNMN (mean ± S.D.) in the 26 DTC patients submitted to 131I therapy

and included in this study is illustrated in Figure 7.1 and summarized in Table S7.2.

Pre-treatment and post-treatment values are presented, stratified by dose group.

207

0 10 20 30

0

10

20

30

131I dose (70 and 100 mCi)

Time (months)

BN

MN

fre

qu

en

cy

(‰

) 70 mCi

100 mCi

Figure 7.1. Binucleated cells carrying micronuclei (BNMN) frequency (‰, mean ± S.D.)

in DTC patients before and after (1, 3/6 and 24 months) therapy with different doses of

131I (70 and 100 mCi).

The results from the 70 mCi dose group until 6 months after 131I administration have

been published before (22). As it was not possible to collect genotyping data on 4 of

the original 19 patients, these patients were excluded and the data were re-analysed.

Longitudinal results in this dose group are, nevertheless, similar to those originally

reported (22): as evident from Figure 7.1, BNMN frequency in these patients increases

significantly 1 month after 131I therapy (from 5.27 ± 3.63‰ to 8.80 ± 4.65‰, p = 0.039)

and stabilizes at 6 months after 131I therapy (8.93 ± 5.92‰, p = 0.944 vs. 1 month after

therapy), remaining persistently higher than before treatment (p = 0.041).

To investigate the long-term persistence of such therapy-induced damage, the study of

these patients at 2 years after therapy was extended (Table S7.2 and Figure 7.1).

Cytogenetic data at such time point was available for 11 patients only. The frequency

of BNMN remained stable (9.64 ± 2.80‰, similar to values at 1 and 6 months, p =

0.460 and p = 0.328, respectively) and persistently higher than baseline (p = 0.005).

To confirm these findings and check for a possible dose effect, the study was

replicated in an independent group of patients administered with 100 mCi. As

expected, BNMN frequency was significantly higher in the 100 mCi group than in the

70 mCi group, irrespective of the time point (Table S7.2 and Figure 7.1), suggesting a

dose-effect association (hence, a cause-effect relation) between iodine dose and

BNMN levels. Apart from this quantitative difference, the effect of either dose on BNMN

208

frequency was qualitatively similar, BNMN in the 100 mCi group increasing significantly

1 month after therapy (from 9.64 ± 4.78‰ to 17.27 ± 5.14‰, p = 0.011) and remaining

persistently higher than baseline at 3 months (21.40 ± 5.66‰, p < 0.001 and p = 0.054

compared to pre-treatment and 1 month post-treatment values, respectively) (Table

S7.2).

Moreover, of notice, the BNMN increment (net balance) after 131I therapy was more

pronounced in the 100 mCi group than in the 70 mCi group, despite the difference was

not significant (p > 0.05).

Finally, the CBPI (mean ± S.D.) was also determined for the 15 DTC patients submitted

to therapy with 70 mCi 131I. As depicted in Figure 7.2, this index, which indicates the

proliferation capacity of lymphocytes and may be used to calculate cytotoxicity (26), did

not change appreciably at 1 and 6 months after 131I administration but was markedly

reduced at 24 months after therapy (from 1.78 ± 0.13 to 1.53 ± 0.09, p = 0.001).

0 10 20 30

1.4

1.6

1.8

2.0

2.2

CBPI vs time (70 mCi)

Time (months)

CB

PI

Figure 7.2. Cytokinesis-Block Proliferation Index (CBPI) (mean ± S.D.) in DTC patients

before and after (1, 6 and 24 months) therapy with 131I (70 mCi).

Characteristics of the study population and cytogenetic data

The potential influence of the demographic, lifestyle and clinical characteristics of the

study population on cytogenetic data was also evaluated. As depicted in Figure 7.3, in

patients treated with 70 mCi, histology interfered with both pre-treatment BNMN levels

and its net balance 1 month after 131I therapy (Figure 7.3): basal BNMN frequency was

significantly higher in FTC than in PTC patients (8.20 ± 3.11‰ vs. 3.80 ± 3.01‰, p =

209

0.020) but, 1 month after therapy, increased only in PTC patients, resulting in a

significantly different net balance between the two histotypes (+6.20 ± 5.05‰ in PTC

vs. -1.80 ± 3.96‰ in FTC, p = 0.009). Such effect was not observed in 100 mCi-treated

patients nor when both dose groups were considered together. Likewise, no significant

effect of gender, age, or smoking habits on BNMN levels or its net balance was

detected, irrespective of the time point or dose group. Furthermore, except maybe for

gender, no significant effect on CBPI was observed for any of these variables in the 70

mCi dose group. Baseline CBPI values were borderline higher in female compared to

male patients (p = 0.045) but such finding should not be overvalued as only one male

patient was included in this dose group.

0 10 20 30

0

5

10

15

20

Hystology (70 mCi)

Time (months)

BN

MN

fre

qu

en

cy

(‰

) PTC

FTC

Figure 7.3. BNMN frequency (‰, mean ± S.D.) in DTC patients before and after (1, 6

and 24 months) therapy with 70 mCi 131I, according to tumour histotype (papillary

thyroid carcinoma (PTC) and follicular thyroid carcinoma (FTC)).

Distribution of DNA repair SNPs in the study population

Table 7.3 reports the allele frequency and genotype distribution of 9 DNA repair SNPs

among our sample of 131I-treated patients. Genotype distributions were consistent with

HWE in either dose group or their combination (p > 0.05) and, except for MSH3

rs26279, did not differ significantly from those described in our previously studied DTC

population (18). For MSH3 rs26279, non-uniform distribution was observed, with the

common allele being overrepresented in the study sample compared to the original

population (p = 0.048, in the dominant model, Table S7.1). Moreover, importantly, no

210

significant differences in genotype distributions were detected between dose groups,

for any of the SNPs, irrespective of the model of inheritance assumed (Table 7.3). No

relevant linkage association was observed between any of the SNPs.

Table 7.3. Allele and genotype frequencies in DTC patients submitted to 131I therapy.

Genotype

70 mCi (n = 15) 100 mCi (n = 11) TOTAL (n = 26)

MAF Genotype

Frequency

n (%)

MAF Genotype

Frequency

n (%)

MAF Genotype

Frequency

n (%)

MLH1 rs1799977

Ile/Ile G:

0.30

7 (46.7) G:

0.45

3 (27.3) G:

0.37

10 (38.5)

Ile/Val 7 (46.7) 6 (54.5) 13 (50.0)

Val/Val 1 (6.7) 2 (18.2) 3 (11.5)

Ile/Val+Val/Val 8 (53.3) 8 (72.7) 16 (61.5)

MSH3 rs26279

Thr/Thr G:

0.23

10 (66.7) G:

0.14

8 (72.7) G:

0.19

18 (69.2)

Thr/Ala 3 (20.0) 3 (27.3) 6 (23.1)

Ala/Ala 2 (13.3) 0 (0.0) 2 (7.7)

Thr/Ala+Ala/Ala 5 (33.3) 3 (27.3) 8 (30.8)

MSH4 rs5745325

Ala/Ala A:

0.13

11 (73.3) A:

0.32

4 (36.4) A:

0.21

15 (57.7)

Ala/Thr 4 (26.7) 7 (63.6) 11 (42.3)

Thr/Thr 0 (0.0) 0 (0.0) 0 (0.0)

Ala/Thr+Thr/Thr 4 (26.7) 7 (63.6) 11 (42.3)

PMS1 rs5742933

G/G C:

0.18

10 (71.4) C:

0.14

9 (81.8) C:

0.16

19 (76.0)

G/C 3 (21.4) 1 (9.1) 4 (16.0)

C/C 1 (7.1) 1 (9.1) 2 (8.0)

G/C+C/C 4 (28.6) 2 (18.2) 6 (24.0)

MSH6 rs1042821

Gly/Gly T:

0.17

10 (66.7) T:

0.09

9 (81.8) T:

0.13

19 (73.1)

Gly/Glu 5 (33.3) 2 (18.2) 7 (26.9)

Glu/Glu 0 (0.0) 0 (0.0) 0 (0.0)

Gly/Glu+Glu/Glu 5 (33.3) 2 (18.2) 7 (26.9)

RAD51 rs1801321

211

T/T G:

0.50

4 (26.7) G:

0.45

4 (36.4) G:

0.48

8 (30.8)

T/G 7 (46.7) 4 (36.4) 11 (42.3)

G/G 4 (26.7) 3 (27.3) 7 (26.9)

T/G+G/G 11 (73.3) 7 (63.6) 18 (69.2)

NBN rs1805794

Glu/Glu C:

0.30

7 (46.7) C:

0.14

8 (72.7) C:

0.23

15 (57.7)

Glu/Gln 7 (46.7) 3 (27.3) 10 (38.5)

Gln/Gln 1 (6.7) 0 (0.0) 1 (3.8)

Glu/Gln+Gln/Gln 8 (53.3) 3 (27.3) 11 (42.3)

XRCC3 rs861539

Thr/Thr C:

0.47

5 (33.3) T:

0.36

5 (45.5) T:

0.46

10 (38.5)

Thr/Met 4 (26.7) 4 (36.4) 8 (30.8)

Met/Met 6 (40.0) 2 (18.2) 8 (30.8)

Thr/Met+Met/Met 10 (66.7) 6 (54.5) 16 (61.5)

XRCC5 rs2440

T/T C:

0.47

5 (33.3) C:

0.50

2 (22.2) C:

0.48

7 (29.2)

T/C 6 (40.0) 5 (55.6) 11 (45.8)

C/C 4 (26.7) 2 (22.2) 6 (25.0)

T/C+C/C 10 (66.7) 7 (77.8) 17 (70.8)

MAF, minor allele frequency. All comparisons of genotype distributions were performed

by the two-sided Fisher’s exact test (whenever 2x2 contingency tables are possible) or

the χ2 test (remaining cases). No significant differences among the 70 and 100 mCi dose

groups were observed.

DNA repair SNPs and cytogenetic data

The influence of DNA repair SNPs on BNMN frequencies and the corresponding

variation from pre-treatment values is shown in Figure 7.4, Table 7.4, Table 7.5 and

Tables S7.3–S7.5.

Prior to 131I administration, BNMN frequency was higher in patients carrying the MLH1

rs1799977 variant allele than in those homozygous for the common allele, with the

difference being significant in the 100 mCi dose group (p = 0.012) and in the pool of

both groups (p = 0.019).

212

0 10 20 30

0

5

10

15

20

MLH1 rs1799977 (70 mCi)

Time (months)

BN

MN

fre

qu

en

cy

(‰

) Ile/Ile

Ile/Val+Val/Val

(a) MLH1 rs1799977, 70 mCi

0 1 2 3 4

0

10

20

30

40

MLH1 rs1799977 (100 mCi)

Time (months)

BN

MN

fre

qu

en

cy

(‰

) Ile/Ile

Ile/Val+Val/Val

(b) MLH1 rs1799977, 100 mCi

0 1 2 3 4

0

10

20

30

40

MSH3 rs26279 (100 mCi)

Time (months)

BN

MN

fre

qu

en

cy

(‰

) Thr/Thr

Thr/Ala+Ala/Ala

(c) MSH3 rs26279, 100 mCi

0 1 2 3 4

0

10

20

30

40

MSH4 rs5745325 (100mCi)

Time (months)

BN

MN

fre

qu

en

cy

(‰

) Ala/Ala

Ala/Thr+Thr/Thr

(d) MSH4 rs5745325, 100 mCi

0 1 2 3 4

0

10

20

30

40

NBN rs1805794 (100 mCi)

Time (months)

BN

MN

fre

qu

en

cy

(‰

) Glu/Glu

Glu/Gln+Gln/Gln

(e) NBN rs1805794, 100 mCi

Figure 7.4. BNMN frequency (‰, mean ± S.D.) in DTC patients before and after (1, 3/6

and 24 months) therapy with 131I, according to genotype and 131I dose group: (a) MLH1

rs1799977, 70 mCi; (b) MLH1 rs1799977, 100 mCi; (c) MSH3 rs26279, 100 mCi; (d)

MSH4 rs5745325, 100 mCi; (e) NBN rs1805794, 100 mCi.

213

Table 7.4. Frequency of micronucleated cells (‰BNMN, mean ± S.D.) in each 131I dose group at t0, t1, t3/t6 and t24, according to genotype (only

SNPs presenting significant findings are shown).

Genotype

70 mCi Group (n = 15), ‰ BNMN (mean ± SD) 100 mCi Group (n = 11), ‰ BNMN (mean ±

SD)

70 + 100 mCi Groups (n =

26), ‰ BNMN (mean ± SD)

t0 t1 t6 t24 t0 t1 t3 t0 t1

MLH1 rs1799977

Ile/Ile 4.14 ± 3.29 12.14 ± 3.58 10.86 ± 7.11 9.20 ± 1.30 5.33 ± 1.16 24.00 ± 3.46 21.50 ± 7.78 4.50 ± 2.80 15.70 ± 6.63

Ile/Val + Val/Val 6.25 ± 3.85 5.88 ± 3.36* 7.25 ± 4.46 10.00 ± 3.74 11.25 ± 4.62* 14.75 ± 2.77* 21.38 ± 5.71 8.75 ± 4.85* 10.31 ± 5.46*

MSH3 rs26279

Thr/Thr 5.50 ± 3.63 8.90 ± 3.81 9.90 ± 7.09 10.13 ± 1.64 8.00 ± 2.73 16.88 ± 5.79 19.00 ± 4.93 6.61 ± 3.42 12.44 ± 6.18

Thr/Ala + Ala/Ala 4.80 ± 4.03 8.60 ± 6.54 7.00 ± 1.58 8.33 ± 5.13 14.00 ± 7.00 18.33 ± 3.51 27.00 ± 2.00* 8.25 ± 6.78 12.25 ± 7.31

MSH4 rs5745325

Ala/Ala 5.18 ± 3.79 8.91 ± 5.07 9.09 ± 6.64 9.63 ± 3.34 13.25 ± 5.68 13.75 ± 3.50 25.50 ± 4.73 7.33 ± 5.55 10.20 ± 5.09

Ala/Thr + Thr/Thr 5.50 ± 3.70 8.50 ± 3.87 8.50 ± 4.04 9.67 ± 0.58 7.57 ± 2.88 19.29 ± 4.99 18.67 ± 4.68 6.82 ± 3.19 15.36 ± 7.00*

NBN rs1805794

Glu/Glu 5.43 ± 4.61 10.00 ± 4.51 8.14 ± 4.56 9.86 ± 2.12 9.00 ± 4.84 19.13 ± 4.64 19.57 ± 4.89 7.33 ± 4.92 14.87 ± 6.46

Glu/Gln + Gln/Gln 5.13 ± 2.85 7.75 ± 4.80 9.63 ± 7.15 9.25 ± 4.11 11.33 ± 5.13 12.33 ± 2.52* 25.67 ± 5.77 6.82 ± 4.40 9.00 ± 4.69*

*p < 0.05; p-value for variant allele carriers versus common allele homozygotes determined by the Student t test (whenever a normal distribution could not be

excluded through the Shapiro-Wilk test) or the Mann-Whitney U test (remaining cases). Significant findings highlighted in bold.

214

Table 7.5. Variation in the frequency of micronucleated cells from baseline (‰BNMN, mean ± S.D.) in each 131I dose group at t1, t3/t6 and t24,

according to genotype (only SNPs presenting significant findings are shown).

Genotype 70 mCi Group (n = 15), ‰ BNMN (mean ± SD)

100 mCi Group (n = 11), ‰ BNMN

(mean ± SD)

70 + 100 mCi

Groups (n = 26),

‰ BNMN (mean

± SD)

Δt1 Δt6 Δt24 Δt1 Δt3 Δt1

MLH1 rs1799977

Ile/Ile 8.00 ± 4.97 6.71 ± 6.85 5.00 ± 3.39 18.67 ± 3.06 16.50 ± 6.36 11.20 ± 6.71

Ile/Val + Val/Val −0.38 ± 3.70* 1.00 ± 4.90 3.50 ± 4.37 3.50 ± 4.57* 10.13 ± 5.28 1.56 ± 4.49*

MSH4 rs5745325

Ala/Ala 3.73 ± 6.83 3.91 ± 7.05 4.13 ± 3.91 0.50 ± 3.11 12.25 ± 5.32 2.87 ± 6.13

Ala/Thr + Thr/Thr 3.00 ± 3.56 3.00 ± 4.90 4.33 ± 4.51 11.71 ± 7.27* 10.83 ± 6.49 8.55 ± 7.41*

*p < 0.05; p-value for variant allele carriers versus common allele homozygotes determined by the Student t test (whenever a normal

distribution could not be excluded through the Shapiro-Wilk test) or the Mann-Whitney U test (remaining cases). Significant findings

highlighted in bold.

215

One month after 131I administration, MLH1 rs1799977 variant allele carriers always

presented significantly lower BNMN levels than patients homozygous for the common

allele, either when considering absolute values (p = 0.004, p = 0.012 and p = 0.034 in

the 70 mCi, 100 mCi, and in the pool of both groups, respectively) or the net variation

from baseline (p = 0.002, p = 0.001 and p < 0.001 in the 70 mCi, 100 mCi and in the

pool of both groups, respectively). BNMN frequency one month after therapy was also

significantly lower in carriers of the variant allele for NBN rs1805794 (p = 0.043 in the

100 mCi group and p = 0.017 in the pool of both groups), with the difference in net

BNMN values almost being significant (p = 0.099 in the 100 mCi dose group and p =

0.058 in the pool of both groups). Further, carriers of at least one MSH4 rs5745325

variant allele exhibited higher levels of 131I-induced BNMN than patients homozygous

for the common allele (p = 0.018 in the 100 mCi group, p = 0.043 in the combination of

both groups), with the difference in absolute BNMN frequencies being significant in the

pooled analysis of both groups (p = 0.039) and almost significant in the 100 mCi group

(p = 0.084).

Three months after therapy, significantly higher BNMN frequencies were found in

patients from the 100 mCi group carrying the MSH3 rs26279 variant allele (p = 0.030).

No other significant difference in either absolute or therapy-induced BNMN frequencies

was found between the different genotypes of the DNA repair SNPs, at any time point.

Likewise, no influence of genotype in CBPI, either absolute or relative to baseline

values, was detected for any of the DNA repair SNPs considered in this study, at any

time point (Table S7.6).

Discussion

We have previously demonstrated a significant increase in BNMN frequency in

peripheral lymphocytes from 19 DTC patients treated with 70 mCi 131I (22). In the

present exploratory study, in order to confirm these findings, to evaluate the long-term

persistence of such 131I-induced DNA damage and to determine whether it may be

influenced by DNA repair SNPs, we extended our analysis at 2 years after 131I

administration in this group of patients, included a new group of patients submitted to

RAI therapy with 100 mCi and profiled 9 DNA repair SNPs in patients from both

groups.

In line with our previously reported results, we observed, in the 100 mCi dose group, a

significant and persistent increase in BNMN frequency after 131I therapy, with mean

levels being always higher than in the 70 mCi group, irrespective of the time point

216

considered. Replication across two independent sets of patients and observation of a

dose effect strongly suggests a causal relation between RAI therapy and systemic

chromosomal damage in lymphocytes, as assessed by the CBMN assay. Such

correlation has been repeatedly demonstrated (both in thyroid patients following RAI

therapy (27-32) and in other settings where exposure to low levels of low-LET (linear

energy transfer) ionizing radiation occurs (28, 33)) and is expected since 131I may be

taken up by extra-thyroidal cells (7) and emit β- and -radiation capable of inducing

dose-dependent chromosomal damage detectable by cytogenetic analysis (e.g.,

micronuclei) (27, 28, 32). The ability of 131I to induce cytogenetic damage in peripheral

lymphocytes in a dose-dependent manner is, in fact, clear and well-established,

allowing BNMN frequency to be used as a valid, highly sensitive, and specific

biomarker of effect for biological dosimetry of RAI therapy and, hence, to predict its

associated genotoxic risk in dividing mammalian cells (27, 28, 32, 34, 35).

A less clear picture exists, however, concerning the long-term persistence (kinetics of

the recovery) of such IR-induced cytogenetic damage. Our results from the 70 mCi

dose group suggest that 131I-induced damage in peripheral lymphocytes persists for at

least 2 years. Despite negative results have also been published (36, 37), our results

are in line with most prior follow-up studies on RAI therapy or other low-dose IR

exposures (e.g., for diagnostic purposes) (28, 29, 38-41). Considering the half-life of

131I (ranging from 1 to 8 days in thyroidectomized and non-thyroidectomized TC

patients, respectively) (28) and of circulating lymphocytes (about 3 years) (28, 38),

such repeated demonstration of persistent cytogenetic damage is somehow surprising

and challenge the widely held views about the mechanisms of IR-induced DNA

damage. Possible explanations for the long-term genomic instability of lymphocytes

from 131I-exposed subjects include the introduction, upon irradiation, of DNA damage

and cytogenetic alterations (1) in a subset of long-lived naïve T lymphocytes, quiescent

cells that survive for prolonged periods of time in a resting stage, retaining the initially

inflicted DNA damage and expressing it as micronuclei when stimulated to proliferate in

the CBMN assay (38) (42, 43), (2) in hematopoietic stem and progenitor cells that,

through clonal expansion, may give rise to mature T lymphocytes with stable and

unstable aberrations, perpetuating genomic instability in time (transgenerational effect)

(38, 42, 43), and (3) in non-irradiated lymphocytes (a delayed non-targeted effect), as a

result of the long-term production and plasma secretion of soluble clastogenic factors

by irradiated cells (oxidative stress by-products such as ROS (reactive oxygen species)

and inflammatory cytokines such as TNF-) that may further extend IR-induced

217

cytogenetic damage in time (“bystander effect”) (44). The two latter explanations are

generally favoured, as a large number of studies exist demonstrating either the high

frequency of gene mutations and chromosomal aberrations in the progeny of irradiated

cells or the production and plasma release of factors with clastogenic activity by

irradiated cells (including one on 131I-treated patients) (37). Overall, current evidence

(44-47) supports the notion that a potent long-term inflammatory-type response

develops upon IR exposure, irradiated cells producing danger signals (oxidative stress

by-products and inflammatory cytokines) capable of exerting an array of persistent

bystander effects in non-irradiated cells (altered levels of damage-inducible and stress-

related proteins), leading to delayed genomic instability (chromosomal aberrations,

sister chromatid exchanges, micronuclei formation/induction or mutations), hence,

predisposing to malignancy (altered proliferation or transformation). Such long-term

inflammatory-type response could also be responsible for the marked reduction in

CBPI that we observed at 24 months after 131I therapy.

In this study, complying with current recommendations, we also investigated the role of

potential confounding factors on BNMN frequency. As reviewed elsewhere (48-50) and

demonstrated through meta-analysis in the International Human MicroNucleus (HUMN)

Project (51), age and gender are well-established factors, with increasing age and

female gender being consistently associated with higher BNMN levels in peripheral

blood lymphocytes. The influence of age has been demonstrated, in particular, in 131I-

treated patients (28, 31). Data on the potential role of smoking status on BNMN levels

are somewhat more inconsistent, many studies failing to find an association except,

maybe, in heavy smokers and in those with relevant occupational exposures (48-51). In

this study, no significant effect of gender, age, or smoking habits on BNMN levels or its

net balance was detected, irrespective of the time point or dose group. The study was

probably underpowered to detect such effects. It is also possible that the effect of these

variables may have been masked by the impact of internal IR exposure after 131I

administration.

We did observe, however, in the 70 mCi group only, differences on BNMN levels

between the two TC histotypes, as FTC patients presented significantly higher basal

BNMN frequency than PTC patients but significantly lower therapy-induced BNMN

levels at one month after 131I administration. This is suggestive of higher background

genomic instability in FTC but higher sensitivity to the DNA damaging effects of IR in

PTC. Considering the small sample size and the non-reproducibility of the findings

between the two dose groups, extreme caution must be taken in the interpretation of

218

these results. Nevertheless, the available evidence supports both findings: PTC usually

presents as a microsatellite stable tumour, with no appreciable levels of either loss of

heterozygosity (LOH) or aneuploidy (stable chromosome profile) (52-54). On the

contrary, a considerable degree of chromosomal instability appears to be a hallmark

feature of FTC, which presents a consistently higher frequency of chromosomal

abnormalities, LOH, allelic loss, and a higher mutational burden compared to PTC (52,

53, 55-57). Microsatellite instability (MSI), despite uncommon in TC, also appears to be

more frequent in FTC than in PTC (53-55). The available evidence thus largely

supports our observation of higher background genomic instability in FTC. Moreover,

considering that activating RAS mutations are commonly observed in FTC but not in

PTC (53, 58, 59), the association between increased RAS expression and decreased

frequency of IR-induced MN reported by Miller et al (60) is coherent with our own

observation of lower 131I-induced BNMN frequency in FTC, supporting the idea that this

histotype is less sensitive to the DNA damaging effects of IR than PTC. Such

hypothesis (i.e., higher sensitivity to IR in PTC) is further reinforced by a recent

observation, through meta-analysis, of increased efficacy of RAI therapy in PTC

patients, compared to FTC (61) but more studies are needed for a solid conclusion to

be drawn.

Moreover, in the present study, we further evaluated the potential impact of selected

HR, NHEJ, and MMR pathway SNPs on BNMN levels, before and after the

administration of 131I. To our knowledge, this is the first study doing so. Significant

genotype effects on MN frequency and/or its net balance were observed for HR (NBN)

and MMR (MLH1, MSH3, MSH4) repair pathway SNPs across different time points.

This was expected because (1) IR exposure results in increased DNA damage, most

notably, single- and double-strand breaks, oxidative lesions (e.g., 8-oxo-dG), DNA-

protein crosslinks (DPCs) and clustered DNA lesions (62-67); (2) the HR pathway,

acting in the S/G2 stages of the cell cycle, is the major DNA repair pathway involved in

the error-free correction of DSBs (11, 33, 35, 68); (3) MMR proteins, besides their

canonical actions on the post-replication repair of mispaired nucleotides and insertion–

deletion loops, have also been demonstrated to play an important role on the damage

response to IR-induced DSBs, either through cooperation with HR or through signalling

for cell-cycle arrest and apoptosis (64, 69-71); (4) DSBs, if left unrepaired, e.g., due to

the presence of SNPs that reduce the DNA repair capacity, may give rise to

chromosome breakage and MN formation upon replication (28, 33, 35, 72). The

potential influence of functional DSB repair SNPs on 131I-induced BNMN frequency is,

219

therefore, fully justified. A literature review on the functional impact of these SNPs and

their putative association with response to radio and/or chemotherapy was performed

and is presented below (Table 7.6).

Table 7.6. Literature review on the functional impact of the studied SNPs and their

putative association with radio and/or chemosensitivity (only SNPs presenting

significant findings in the present study are shown).

Gene dbSNP

Cluster ID

(rs no.)

Functional Impact Clinical Association Studies (Radio

and/or Chemosensitivity)

MLH1 rs1799977 Missense SNP

located in a highly

conserved N-

terminal ATPase

domain, vital for

MLH1 function

(73)(1); G allele

associated with

reduced

expression (74-

77)(2-5).

GG genotype associated with increased

radiosensitivity in cancer patients,

translating into increased efficacy (78) or

toxicity (79) of radiotherapy (alone or

combined with chemotherapy).

MSH3 rs26279 Missense SNP

located in the

ATPase domain,

critical for protein

activity (80);

altered expression

has been

suggested (81) but

not confirmed (82).

GG genotype associated with decreased

incidence of radiation dermatitis in breast

cancer patients receiving radiotherapy

(83), decreased overall survival in head

and neck squamous cell carcinoma

patients submitted to radiochemotherapy

(81) and decreased response to platinum-

based chemotherapy in advanced non-

small cell lung cancer patients (84).

MSH4 rs5745325 Missense SNP

located in the N-

terminal domain,

involved in the

interaction with

None to be reported.

220

eIF3f (85).

NBN rs1805794 Missense SNP

located in the

BRCT domain, a

region involved in

the interaction with

BRCA1 (86-89);

conflicting results

from functional

studies (88, 90-92).

No association detected in most studies

focusing on response to radiotherapy (79,

93-96) or chemotherapy (97-99);

conflicting results also reported as the C

allele has been associated with either

improved (86, 100) or worse (68, 101)

prognosis upon platinum-based

chemotherapy; increased frequency of

binucleated lymphocytes with

nucleoplasmic bridges in Glu/Gln children

with high IR exposure, opposite to Gln/Gln

children (102).

MLH1, together with PMS2, forms the MutL heterodimer, a complex critical for the

maintenance of genomic integrity (103, 104). The common rs1799977 (c.665A>G,

Ile219Val) missense SNP is located in a region that codes for a highly conserved N-

terminal ATPase domain, vital for MLH1 function. However, since both alleles code for

nonpolar pH-neutral amino acids, the substitution is considered conservative and not

expected to result in drastic changes in protein properties and function (73). Several

functional studies support this hypothesis (73, 74, 105-107) but the existence of a more

subtle effect should not be excluded (73, 106, 108, 109) as an association between the

G variant allele and reduced MLH1 expression has been demonstrated repeatedly in

cancer patients (74-77). Moreover, two recent meta-analyses have associated this

variant with increased risk of colorectal cancer (110, 111). Considering the important

role that MLH1 plays in the maintenance of genome integrity and cancer avoidance,

both observations are compatible with our own observation of increased baseline

BNMN levels in TC patients carrying the G allele. A different picture emerges, however,

upon IR exposure: as previously stated, MMR proteins such as MLH1 play a dual role

in the DNA damage response to IR, triggering cell-cycle arrest and allowing for either

DSB repair or apoptosis (11, 64). MMR proficiency is thus expected to result in higher

repair efficiency of IR-induced damage (hence, lower cytogenetic levels) and,

simultaneously, higher cytotoxicity upon IR exposure (hence, increased sensitivity to

radiotherapy). Indeed, alongside with increased cancer susceptibility, the MLH1

rs1799977 variant GG genotype has been associated with increased radiosensitivity in

221

cancer patients, translating into increased efficacy (78) or toxicity (79) of radiotherapy

(alone or combined with chemotherapy). This is suggestive of increased MMR

proficiency in such patients and supports our own observation of significantly lower

BNMN levels, one month after 131I therapy, in TC patients carrying the G allele. How

the same allele may be associated with decreased function under basal conditions and

increased function after IR exposure remains to be explained: MLH1 has been

demonstrated to be upregulated upon IR exposure (112, 113), it is possible that such

upregulation might be more pronounced in G allele carriers, but this is highly

speculative. Nevertheless, the high level of significance in our observations (especially

when considering the change in MN frequency from baseline) and their cross-validation

in independent groups strengthen our conclusions and warrant further studies to clarify

this issue.

Two other MMR polymorphisms presented significant findings in our study, MSH3

rs26279 and MSH4 rs5745325. Like MLH1, MSH3 also appears to be involved in the

repair and damage response to IR-associated lesions such as DSBs and inter-strand

crosslinks (84, 114). MSH3 rs26279 (c.3133A>G; Thr1045Ala) is a common SNP that

results in an amino acid change in the ATPase domain of MLH3. This domain is critical

for MSH3 activity, suggesting a functional impact for this variant (80). Such hypothesis

remains to be verified as, to the best of our knowledge, functional studies are lacking.

An association with altered MSH3 expression levels has been suggested (81) but not

confirmed (82). The MSH3 rs26279 G allele or GG genotype has been consistently

associated with cancer risk in all 3 meta-analysis that we are aware of, particularly for

colon and breast cancer (115-117), suggesting decreased DNA repair capacity in G

allele carriers. Further, MSH3 rs26279 GG homozygosity has also been associated

with decreased incidence of radiation dermatitis in breast cancer patients receiving

radiotherapy (83), decreased overall survival in head and neck squamous cell

carcinoma patients submitted to radiochemotherapy (81), and decreased response to

platinum-based chemotherapy in advanced non-small cell lung cancer patients (84),

suggesting decreased sensitivity to DNA damaging agents such as IR or platinum in

GG homozygous individuals. Such phenotype is commonly associated with MMR

deficiency (64, 69, 70, 118, 119). If we consider, once again, the dual role that MMR

proteins such as MSH3 play in damage repair and apoptosis, these results are

compatible with decreased G allele function, resulting in decreased DNA repair and

apoptosis, increased damage tolerance, resistance to radio/chemotherapy, and

reduced efficacy and cytotoxicity of such therapeutic agents. Our own observation of

222

increased MN levels in TC patients carrying the G allele, 6 months after receiving 100

mCi 131I, fits comfortably into this picture.

Likewise, in our study, MN frequency was also significantly increased (absolute and

change from baseline values) in TC patients carrying the A allele of MSH4 rs5745325,

one month after 131I administration. MSH4 rs5745325 (c.289G>A; Ala97Thr) has only

seldom been evaluated: on single SNP analysis, two prior studies by our team failed to

detect an association with either thyroid (21) or breast cancer risk (120). The same was

observed in the only two other association studies that we found focusing on this SNP

(121, 122). Interestingly, in three out of these four studies, significant associations were

detected when interactions with other SNPs – MSH6 rs1042821 (21), MLH3 rs175080

(120), and CHRNA5 rs16969968 (121) – were considered. Besides the important role

that MSH4 plays in recombinational repair during meiosis (123), it is also suggested to

participate, through interaction with a vast array of binding partners, in DSB-triggered

damage response and repair (85, 123, 124). It is possible that MSH4 rs5745325

interferes with the binding properties of MSH4, with impact on its putative contribution

to the DNA damage response and repair. The interaction of MSH4 with eIF3f (a subunit

of the eIF3 complex implicated in apoptosis regulation and tumour development), for

example, occurs at the region comprising the first 150 amino acids of the N-terminal

domain of MSH4 (where rs5745325 is located) and has been demonstrated to foster

hMSH4 stabilization and to modulate sensitivity to IR-induced DNA damage (85). This

is in line with our own findings.

Finally, we also observed a significant association between NBN rs1805794 and

BNMN frequency, one month after the administration of 100 mCi 131I. Nibrin plays a

pivotal role in the initial steps of the cellular response to DNA damage, directly initiating

DSB repair through the RAD51-dependent HR pathway and further contributing to cell

cycle checkpoint activation through an ATM-dependent pathway (68, 125-127).

Inactivating germline mutations in the NBN gene (which encodes for the Nibrin protein)

markedly impair DSB repair and cause the Nijmegen breakage syndrome,

characterized by chromosomal instability, increased cancer susceptibility, and

increased sensitivity to DSB-causing agents such as IR or cisplatin. These features

highlight the importance of Nibrin for genome stability (hence, cancer prevention) (86,

93, 125, 127). NBN overexpression also appears to be associated with poor prognosis

in several types of cancer (68), which is consistent with a putative increase in DNA

repair efficiency, hence, resistance to cytotoxic therapy. Among the numerous NBN

polymorphisms, rs1805794 (c.553G>C; Glu185Gln) is the most frequently investigated.

223

This missense variant results in an amino acid change in the BRCT (BRCA1 C

Terminus) domain (amino acids 108-196), a domain involved in the interaction of Nibrin

with BRCA1. The resulting complex (the BRCA1-associated genome surveillance

complex, BASC) is responsible for the recognition and repair of aberrant DNA (86-89).

NBN rs1805794 has been suggested to interfere with the interaction properties of

Nibrin and thus with DNA repair capacity, sensitivity to DNA damaging agents (such as

IR) and cancer susceptibility. Accordingly, NBN rs1805794 has been repeatedly

associated with cancer risk, as demonstrated by numerous meta-analysis (68, 88, 89,

125, 128-132) but conflicting reports exist (126, 127, 133, 134). Interestingly, the

association may vary according to ethnicity (88, 130) and tumour site (125), as one of

these meta-analysis has demonstrated, for example, increased risk of leukaemia,

nasopharyngeal, and urinary system cancers but decreased risk of lung, gastric, and

digestive system cancers (125). Furthermore, final conclusive evidence on the

significance of NBN rs1805794 is still lacking, as the functional studies performed thus

far have yielded negative or conflicting results: while lymphocytes from healthy

individuals homozygous for the G allele have been reported to present higher DNA

damage levels (as assessed by the Comet assay) than lymphocytes from C allele

carriers (90), opposite results have been reported in ex vivo X-ray irradiated cells from

healthy subjects (88). Further ex vivo irradiation studies have failed to observe a

significant influence of NBN rs1805794 on DNA repair capacity and radiosensitivity (91,

92). Furthermore, since a putative functional impact of this SNP on DNA repair capacity

could possibly influence patient sensitivity to radio and/or chemotherapy, association

studies correlating NBN rs1805794 genotype with therapy response, toxicity, or

prognosis have also been performed. Again, most studies failed to find an association

in radiotherapy (79, 93-96) or chemotherapy (97-99) treated patients, while other

studies presented opposite findings, associating the NBN rs1805794 C allele with

either improved (86, 100) or worse (68, 101) prognosis upon platinum-based

chemotherapy. Interestingly, increased frequency of binucleated lymphocytes with

nucleoplasmic bridges was observed in peripheral lymphocytes from children with high

environmental exposure to IR that were heterozygous for NBN rs1805794, while the

reverse pattern was observed in children homozygous for the Gln allele (102). This

may be suggestive of molecular heterosis, a hypothesis that, considering the high

interethnic variability of the NBN rs1805794 distribution, could help in explaining such

divergent results. Overall, despite extensively investigated, the functional significance

of NBN rs1805794, as well as its putative role in sensitivity to DNA damaging agents

224

(such as IR) and cancer susceptibility remains elusive, warranting further studies to

clarify this issue.

Conclusions

In conclusion, our results confirm that BNMN levels in peripheral lymphocytes from

DTC patients increase significantly immediately 1 month after 131I therapy and further

suggest that these remain stable and persistently higher than baseline for at least 2

years. Furthermore, a marked reduction in CBPI is observed at 24 months after 131I

administration. Moreover, HR and MMR SNPs (MLH1 rs1799977, MSH3 rs26279,

MSH4 rs5745325, and NBN rs1805794) were, for the first time, associated with IR-

induced MN, a cytogenetic marker of DNA damage, in TC patients submitted to 131I

therapy. Among such findings, a highly significant and independently replicated

association was observed for MLH1 rs1799977, strongly suggesting a role for this

particular SNP on the personalization of RAI therapy in TC cancer patients. Baseline

and post-therapy MN levels also diverged according to tumour histotype. These results

should be regarded as merely suggestive and proof of concept, as the sample was

small and the number of tests was high, increasing the likelihood of false-positive

results. Nevertheless, our findings suggest that TC therapy with 131I may pose a long-

term challenge to cells other than thyrocytes and that the patient genetic profile may

influence the individual sensitivity to this therapy. Such hypotheses are of relevance to

the efficacy and safety of 131I therapy, a widespread practice in TC patients. As such,

extending the benefit already achieved with the latest guidelines on TC treatment in

terms of risk/benefit ratio through improved clinical assessment of the potential long-

term risks of 131I therapy is desirable. Likewise, despite the micronucleus test is

considered the gold standard methodology in genetic toxicology testing and often used

as a “stand-alone” test in numerous and relevant papers in this area, other tests should

also be employed to validate these results. Furthermore, potential radiogenomic

markers such as those suggested here should be evaluated in larger samples,

preferentially through multi-centre independent studies adequately powered to provide

more robust evidence and, eventually, to allow for gene-gene and gene-environment

interactions to be assessed. Identifying the most clinically relevant variables, genetic or

non-genetic, and accurately estimating their impact on 131I therapy response rate and

adverse event risk for each individual TC patient is the ultimate goal, under a

personalized medicine approach.

225

Funding

This research was funded by FCT – Fundação para a Ciência e a Tecnologia

(Portuguese Foundation for Science and Technology) through Project

UID/BIM/00009/2019 – Centre for Toxicogenomics and Human Health.

Acknowledgements

The authors warmly acknowledge the generous collaboration of patients and controls in

this study as well as of our colleague Ana Paula Azevedo for technical support.

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Chapter VIII

Final conclusions

240

241

Chapter VIII – Final conclusions

Through this work we sought to evaluate the potential contribution of multiple SNPs,

across different DNA repair pathways, 1) to DTC susceptibility and 2) to DNA damage

levels (MN frequency) in lymphocytes from 131I-treated DTC patients. To our

knowledge, no prior study has investigated such genetic effects on 131I-induced DNA

damage. Also, for many of these SNPs (e.g. BER, MMR), it was the first time they were

evaluated in the context of DTC susceptibility.

Significant associations with DTC risk were observed for CCNH rs2230641, MSH6

rs1042821, XPC rs2228001 and XRCC3 rs861539, the latter through restricting our

prior analysis of TC risk to DTC cases only. The association of XRCC3 rs861539 with

susceptibility to TC (or to its well-differentiated/papillary forms) had been frequently

reported in prior studies (1-7) and was confirmed in this work. This was not the case,

however, for XRCC1 rs1799782 and rs25487, also investigated here and previously

reported to be associated with susceptibility to TC (or to its well-differentiated/papillary

forms) (5, 6, 8-12). Additional genotype-disease associations were observed upon

stratification according to histological, gender or age criteria. More relevantly, when

investigating the joint effect of multiple SNPs, a clear-cut gene-dosage effect between

the number of risk genotypes and DTC risk was observed, together with a high number

of significant results on paired SNP analysis.

Finally and worth mentioning, significant associations were also observed between HR

and MMR SNPs (MLH1 rs1799977, MSH3 rs26279, MSH4 rs5745325, and NBN

rs1805794) and MN levels in peripheral lymphocytes from DTC patients submitted to

131I-based RAI therapy. Of notice, the association with MLH1 rs1799977 with 131I-

induced MN levels one month after therapy was particularly robust, as a highly

significant p value was observed and independently replicated across two 131I dose

groups.

The involvement of SNPs across different DNA repair pathways (XRCC3 rs861539 of

the HR pathway, CCNH rs2230641 and XPC rs2228001 of the NER pathway and

MSH6 rs1042821 of the MMR pathway) in DTC susceptibility is expected: several DNA

damaging agents, able to induce different lesions repairable by corresponding different

pathways, have been proposed to contribute to DTC (13-17) and even IR, the best-

established risk factor for DTC, induces a complex pattern of DNA lesions - including

single- and double-strand breaks, oxidative lesions (e.g., 8-oxo-dG), DNA-protein

crosslinks (DPCs) and clustered DNA lesions - that require different pathways (and

242

their crosstalk) for successful repair (18-24). Moreover, many of these DNA repair

proteins, besides their canonical actions in a specific DNA repair pathway, also play

additional roles on cellular processes such as signalling for cell cycle arrest and

apoptosis (25-30).

The observation of additional genotype-disease associations upon stratification (e.g.

XRCC3 rs861539, NBN rs1805794, XPC rs2228001, ERCC5 rs2227869 and MUTYH

rs3219489 in PTC; MSH6 rs1042821, MLH3 rs175080 and XRCC2 rs3218536 in FTC;

XRCC3 rs861539, MSH6 rs1042821, XPC rs2228001, CCNH rs2230641, ERCC5

rs2227869 and ERCC5 rs17655 in women; XPC rs2228001 and XRCC5 rs2440 in

younger patients; XRCC3 rs861539, CCNH rs2230641, ERCC6 rs2228529 and RAD51

rs1801321 in older patients) suggests the existence of histotype, gender and age-

specific SNP effects on DTC susceptibility. If we recall that distinct molecular profiles

exist between PTC and FTC (31-34) and that DTC differentially affects men and

women (16, 35), the existence of such group-specific effects is plausible and coherent

with our knowledge of the disease. Because of small sample size and unbalanced

group size upon stratification, however, we cannot exclude the possibility that these

findings could simply result from type I errors or reflect the overall effect on the largest

groups.

Also, the cumulative increase in DTC risk that was observed for increasing number of

risk alleles as well as the high number of SNP pairs presenting significant findings

(even when using a more stringent p value of 0.01 to avoid false positive results from

multiple testing) are suggestive of additive (or even multiplicative) effects of different

SNPs on DNA repair activity and, hence, cancer risk. This is biologically plausible since

the different DNA repair proteins physically and functionally interact with each other,

within the same or different DNA repair pathways (6, 23, 24, 36-38). Moreover, it

establishes ground for a polygenic approach to risk assessment (e.g. through genetic

risk scores) (39-43) in DTC, a multifactorial disease that likely develops as a

consequence of the interaction of multiple genetic and environmental factors (13, 44,

45).

Finally, HR (NBN rs1805794) and MMR (MLH1 rs1799977, MSH3 rs26279, MSH4

rs5745325) SNPs were also significantly associated with MN levels (a cytogenetic

marker of DNA damage) in peripheral lymphocytes from DTC patients submitted to 131I-

based RAI therapy, across different time points. This is unsurprising since 131I has been

demonstrated to be taken up by lymphocytes and other cells (besides thyrocytes),

emitting IR that, as stated above, induces a vast array of DNA lesions (46-48). Among

243

these lesions, DSBs, for example, can be repaired by the HR pathway (where NBN

plays a pivotal role) or, if left unrepaired, may give rise to chromosome breakage and

MN formation upon replication (49-54). MMR proteins such as MLH1, MSH3 or MSH4,

besides their canonical actions, have also been demonstrated to play an important role

in recombinational processes and are likely to participate in the damage response to

IR-induced DSBs, either through cooperation with HR or through signalling for cell-

cycle arrest and apoptosis (25, 28-30, 55-57). The potential contribution of these DNA

repair SNPs to 131I-induced micronuclei in DTC patients, despite not previously

demonstrated, is therefore fully justified and coherent with the evidence available.

Because of small sample size – the main limitation of our work - these results should

be interpreted with caution and regarded solely as a proof of concept. Such limitation

may have resulted in failure to replicate the previously reported associations of XRCC1

SNPs (rs1799782 and rs25487) with TC risk (5, 6, 8-12) and, eventually to detect

additional associations, either with DTC risk or with MN levels upon 131I therapy.

Moreover, considering the substantial number of tests performed, especially upon

stratification analysis, we cannot exclude the possibility that some of the observed

associations are due to chance (false positive results, originating from type I errors).

Finally, since no SNP functional assessment was performed, we cannot exclude the

possibility that the associations observed are due to other variants, in LD with the ones

considered here.

Despite such caveats, overall, this work suggests an involvement of DNA repair SNPs

across different pathways on DTC susceptibility, possibly through cumulative effects.

Considering the high heritability of DTC, which is only partially explained by published

GWAS (58-65), our findings may be of relevance, as they may explain part of such

“missing” heritability and thus provide valuable insight into the aetiology of this

increasingly incident disease. Despite the longstanding advances achieved all along

the last decades, through the identification of somatic mutations in a wealth of cancer

hallmark genes and a plethora of potential carcinogenic agents (88% of the agents

classified as 1, 2A and 2B by IARC are genotoxic), carcinogenesis is still short of

straightforward mechanistic pathways. Indeed, germline variants exist in the same

hallmark genes where somatic pathogenic mutations occur and they may actually lead

to early-onset cancer, whereas somatic mutations, which tend to accumulate with time

in environmental carcinogen-dependent cancers, are often associated with later-onset

cancer (66). Considering the high frequency of DTC among adolescents and young

adults (which places the median age at DTC diagnosis below that for most other types

244

of cancer) (16, 35, 67-69) and the high heritability of DTC, germline variants appear to

play a particularly relevant the role in the aetiology of this malignancy. Therefore, the

identification of further genetic susceptibility biomarkers, the validation of the existing

ones (through replication in different populations) and the in-depth study of gene-gene

and gene-environment interactions (which, despite seldomly addressed, likely play an

important role in DTC predisposition) is highly desirable as it will possibly allow the

identification of individuals who are at increased risk for DTC and, eventually, the

optimization of cancer prevention policies.

Likewise, our findings also demonstrate that DNA repair SNPs may interfere with the

extent of 131I-induced DNA damage in peripheral lymphocytes from DTC patients,

suggesting that these (and eventually other, yet unidentified) genetic variants may

influence 131I sensitivity in individual patients. This is of utmost relevance to the efficacy

and safety of 131I therapy, a widespread practice that remains the mainstay in the

management of DTC (70-73) and is being increasingly associated with occurrence of

secondary malignancies such as leukaemia (74-77). Identifying clinically relevant

variables, genetic or non-genetic, and accurately estimating their impact on 131I therapy

response and adverse event rate may allow the personalization of RAI therapy

according to the individual profile of the patient, with clinical benefits.

In order to validate and strengthen our preliminary findings, these results must be

replicated in larger independent populations, preferentially through multi-centre studies.

Such future studies should be adequately powered to provide more robust evidence on

the associations suggested in this work, to allow for the study of other potential

susceptibility and radiogenomic biomarkers (e.g., less frequent but potentially relevant

variants) and, eventually, to accommodate more sophisticated analysis such as

haplotype analysis and assessment of gene‑gene and gene‑environment interactions.

Regarding the latter, exposure to IR and other environmental factors (as well as their

potential interaction with genetic factors) should be accounted for in the design of the

study. Moreover, the potential association of these SNPs with mutational events

involved in DTC carcinogenesis (e.g., BRAF mutations and RET/PTC rearrangements)

as well as with clinical and biochemical markers of disease progression, prognosis,

therapeutic response and adverse effects should be further investigated. Likewise, the

functional significance of these SNPs should also be confirmed through in vitro studies.

Finally, despite the micronucleus test is considered the gold standard methodology in

genetic toxicology testing (78, 79), other tests should be employed to validate the

245

associations observed between DNA repair SNPs and MN frequency in 131I-treated

DTC patients.

All in all, the data presented in this Thesis does not intend to supply a complete set of

data on the genetic mechanisms associated with thyroid carcinogenesis, but simply to

add data on the possible role of DNA repair gene variants on DTC susceptibility and on

its response to conventional RAI therapy. As mentioned all along the work and herein

again, both processes involve a multiplicity of genetic and non-genetic factors that go

far beyond the issue of DNA repair, factors that must be considered together and

properly balanced if we are to grasp a wholesome picture of thyroid carcinogenesis and

its therapeutic approach.

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Appendix

Rights and permissions

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Appendix – Rights and permissions

The following articles were published in “Open Access” periodicals, under Creative

Commons licence (Attribution 4.0 International / CC BY 4.0), as clearly identified at

the end of each of both articles:

• Santos LS, Gomes BC, Bastos HN, Gil OM, Azevedo AP, Ferreira TC, Limbert

E, Silva SN, Rueff J (2019). Thyroid Cancer: The Quest for Genetic

Susceptibility Involving DNA Repair Genes. Genes (Basel). 10(8): E586.

• Santos LS, Gil OM, Silva SN, Gomes BC, Ferreira TC, Limbert E, Rueff J

(2020). Micronuclei Formation upon Radioiodine Therapy for Well-Differentiated

Thyroid Cancer: The Influence of DNA Repair Genes Variants. Genes. 11(9):

1083.

Both articles are therefore automatically authorized for full or partial reproduction,

in the terms of this licence, available at https://creativecommons.org/licenses/by/4.0/.

Moreover, the permission policies of the publisher (MDPI) of both articles can be found

in https://www.mdpi.com/openaccess#Permissions. We quote from this web page: “No

special permission is required to reuse all or part of article published by MDPI,

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Common CC BY license, any part of the article may be reused without permission

provided that the original article is clearly cited.”.

Upon e-mail request to the corresponding Journals (reproduced bellow), the following

articles were also authorized for reproduction in this PhD thesis:

• Santos LS, Branco SC, Silva SN, Azevedo AP, Gil OM, Manita I, Ferreira TC,

Limbert E, Rueff J and Gaspar JF (2012). Polymorphisms in base excision

repair genes and thyroid cancer risk. Oncol Rep. 28(5): 1859-68.

• Santos LS, Gomes BC, Gouveia R, Silva SN, Azevedo AP, Camacho V, Manita

I, Gil OM, Ferreira TC, Limbert E, Rueff J and Gaspar JF (2013). The role of

CCNH Val270Ala (rs2230641) and other nucleotide excision repair


Oncol Rep. 30(5): 2458-66.

• Santos LS, Silva SN, Gil OM, Ferreira TC, Limbert E, Rueff J (2018). Mismatch

repair single nucleotide polymorphisms and thyroid cancer susceptibility. Oncol

Lett. 15(5): 6715-6726.

No changes were made to any of these articles that are fully reproduced in this thesis.

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