LP 6 TesteMoleculareGeneticeDermatologie Part I

7/30/2019 LP 6 TesteMoleculareGeneticeDermatologie Part I

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Disciplina de Dermatologie, Universitatea de Medicin Victor Babe Timioara

1

METODE DE DIAGNOSTIC MOLECULAR SI

GENETIC IN DERMATOLOGIE


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The Central Dogma

The central dogma (due to

Francis Crick in 1958) states

that information flows are all

unidirectional:

The central dogma states that

once `information' haspassed into protein it cannot

get out again.

DNA RNA ProteinGenomeEvolution

Selection

Transcription Translation


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Oncogenes: BAX, BCL2L1, CASP8, CDK4, ELK1,ETS1, HGF, JAK2, JUNB, JUND, KIT, KITLG, MCL1,MET, MOS, MYB, NFKBIA, NRAS, PIK3CA, PML,PRKCA, RAF1, RARA, REL, ROS1, RUNX1, SRC,STAT3, ZHX2.

Tumor Suppressor Genes: ATM, BRCA1, BRCA2,CDH1, CDKN2B, CDKN3, E2F1, FHIT, FOXD3, HIC1,IGF2R, MEN1, MGMT, MLH1, NF1, NF2, RASSF1,RUNX3, S100A4, SERPINB5, SMAD4, STK11, TP73,

TSC1, VHL, WT1, WWOX, XRCC1.

Oncogenic & Tumor Suppressor Properties: BCR,EGF, ERBB2, ESR1, FOS, HRAS, JUN, KRAS, MDM2,MYC, MYCN, NFKB1, PIK3C2A, RB1, RET, SH3PXD2A,TGFB1, TNF, TP53.

Transcription Factors: ABL1, BRCA1, BRCA2,CDKN2A, CTNNB1, E2F1, ELK1, ESR1, ETS1, FOS,FOXD3, HIC1, JUN, JUNB, JUND, MDM2, MEN1, MYB,MYC, MYCN, NF1, NFKB1, PML, RARA, RB1, REL,RUNX1, RUNX3, SMAD4, STAT3, TGFB1, TNF, TP53,

TP73, TSC1, VHL, WT1, ZHX2.

Epithelial-to-Mesenchymal Transition: BRCA2,CDKN2B, CTNNB1, ERBB2, HGF, JAK2, KIT, MCL1,NF1, RUNX3, S100A4, SMAD4, TGFB1, VHL.

Angiogenesis: AKT1, CTNNB1, EGF, ERBB2, NF1,PML, RUNX1, TGFB1.

Apoptosis: BAX, BCL2, BCL2L1, BRCA1, CASP8,E2F1, MCL1, MGMT, TNF, VHL.

Cell Adhesion: APC, CDH1, CDKN2A, CTNNB1,KITLG, NF1, NF2, TGFB1.

Cell Cycle: ATM, BRCA1, BRCA2, CCND1, CDK4,CDKN1A, CDKN2A, CDKN2B, CDKN3, E2F1, HGF,MEN1, STK11, TP53.

Chemotaxis, Cell Migration & Motility: HRAS, JAK2,MET, NF1, NF2, PRKCA, SERPINB5, STAT3.

DNA Damage & Repair: ABL1, APC, ATM, BRCA1,

BRCA2, CDKN1A, MEN1, MGMT, MLH1, PML, TP53,TP73, XRCC1.


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Immunohistochemistry (IHC)


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Nuclear markers

Cytoplasmic marker

Membranous Marker


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Immunohistochemistry

Immunohistochemistry or IHC refers to the processof localizing antigens (e.g. proteins) in cells of atissue section exploiting the principle of antibodiesbinding specifically to antigens in biological tissues.

Immunohistochemical staining is widely used in thediagnosis of abnormal cells such as those found incancerous tumors.

Specific molecular markers are characteristic of

particular cellular events such as proliferation orcell death (apoptosis).

IHC is also widely used in basic research tounderstand the distribution and localization ofbiomarkers and differentially expressed proteins indifferent parts of a biological tissue.

Visualising an antibody-antigen interaction can beaccomplished in a number of ways. In the mostcommon instance, an antibody is conjugated to an

enzyme, such as peroxidase, that can catalyse acolour-producing reaction.


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Surface Markers - CD CD markers, an abbreviation for human cluster of differentiation markers, are a classification

system for monoclonal antibodies against cell surface molecules on leukocytes and antigens from

other cells. Currently, more than 400 CD markers have been identified, although not all of them are of

diagnostic value.

Immunophenotyping can be used on paraffin-embedded samples, frozen sections, or with flowcytometry.

When faced with a possible cutaneous lympho-proliferative disorder, the dermatopathologistevaluates the overall histological architectural pattern of the biopsy.

Interpretation of CD marker staining on fixed tissue samples should be based on the cellular

distribution of staining (i.e., membranous, cytoplasmic, nuclear). Negative and positive controls are also used in the staining process to allow for comparison, toconfirm the specificity and sensitivity of the staining process, and to assist in determining theaffinity of a particular stain.


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The first step in the immunophenotypic evaluation is determination if the dominant population ofcells are B-cells, T-cells, or neither.

Three markers are typically used for this initial classification: CD20, CD3, and CD45.

T-cell processes are typically CD3+, CD20-, CD45+.

B-cell processes are typically CD3-, CD20+, and CD45+.

CD markers are specific for a particular cell type or origin, but there can be overlap.

CD markers serve as an imperfect attempt to identify and classify some neoplastic cells. It is

probably more accurate and practical to state that the pattern of CD marker expression is stronglysuggestive of a certain cell type or lineage, but may not be definitive


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Flow cytometric immunophenotyping

Some antibodies do not work with sectionscut from paraffin-embedded samples or withfrozen sections and necessitate flowcytometry. However, flow cytometry requiresthat cells being immunophenotyped beindividually suspended in liquid, an easy taskfor circulating cells in peripheral bloodsamples, but more complicated whendealing with skin samples.

It allows simultaneous multiparametricanalysis of the physical and/or chemicalcharacteristics of up to thousands ofparticles per second.

Flow cytometry uses the principles of lightscattering , light excitation, and emission of

fluorochrome molecules to generate specificmulti-parameter data from particles and cellsin the size range of 0.5um to 40um diameter.
http://www.sonyinsider.com/wp-content/uploads/2010/02/Flow-Cytometry-Diagram2.jpg


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Flow cytometric immunophenotyping In the flow cytometric evaluation of mature B-cell lymphoid neoplasms, it is useful to consider 4 broad groups as determined by their expression of CD5 and CD10.

For each group, additional flow cytometric data in combination with the morphology can narrow down the diagnostic.


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Flow cytometric immunophenotyping Among mature lymphoid neoplasms with a T-cell phenotype, expression of CD4 and CD8 can be used to formulate a list of diagnostic

possibilities and determine what additional information is required for further classification


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Clonality Diagnosis


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T-Cell Receptor and Immunoglobulin Gene

Rearrangements in Diagnosing Skin Disease

The most important advance in the molecular immunological features of lymphomas has been the

recognition that each normal T and B cell bears a unique antigen receptor on its cell surface that

serves as a specific marker for that cell and all of its clonal progeny.

If the cell should undergo malignant transformation, then this same structure becomes a tumor-

specific marker, as well.

For B cells, this marker is the immunoglobulin (Ig) molecule.

For T cells, it is the T-cell receptor (TCR).


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B-Cell Receptor B cell development occurs through several stages, each stage representing

a change in the genome content at the antibody loci.

An antibody is composed of two identical light (L) and two identical heavy (H)chains, and the genes specifying them are found in the 'V' (Variable) regionand the 'C' (Constant) region.

In the heavy-chain 'V' region there are three segments; V, D and J, whichrecombine randomly, in a process called VDJ recombination, to produce aunique variable domain in the immunoglobulin of each individual B cell.

Similar rearrangements occur for light-chain 'V' region except there are onlytwo segments involved.

Stage Heavy chain Light chain

Progenitor (or pre-pro) B cells germline germline

Early Pro (or pre-pre)-B cells undergoes D-J rearrangement germline

Late Pro (or pre-pre)-B cells undergoes V-DJ rearrangement germline

Large Pre-B cells is VDJ rearranged germline

Small Pre-B cells is VDJ rearranged undergoes V-J rearrangement

Immature B cells is VDJ rearranged VJ rearranged

Mature B cells is VDJ rearranged VJ rearranged

The B-cell receptor is atransmembrane receptor proteinlocated on the outer surface of B-cells.

When a B-cell is activated by itsfirst encounter with an antigen thatbinds to its receptor (its "cognateantigen"), the cell proliferates anddifferentiates to generate apopulation of antibody-secretingplasma B cells and memory B cells.
http://8e.devbio.com/image.php?id=118


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T-Cell Receptor The TCR, which is anchored in the cell membrane,

consists of two halves which form a pair (or dimer) ofprotein chains. The halves are called the alpha () andbeta () fragments (in / T cells, the halves are gamma() and delta () fragments).

Each fragment is divided in turn into a constant (C) andvariable (V) region. The constant region has an end whichis anchored in the cell membrane.

The variable region faces outward and binds to the HLAmolecule and the antigen it presents. On the chain, thevariable region is called V and the constant region iscalled C; on the chain they are called V and Crespectively.

Processes for TCR formation are similar to thosedescribed for B cell antigen receptors

The TCR alpha chain is generated by VJ recombination,whereas the beta chain is generated by V(D)Jrecombination (both involve a somewhat random joining ofgene segments to generate the complete TCR chain).

Similarly, generation of the TCR gamma chain involves VJrecombination, whereas generation of the TCR delta chain

occurs by V(D)J recombination.


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Clonality

Mycosis fungoides can arise from a background of chronic inflammation via the gradual selection

of one dominant T-cell clone that becomes increasingly malignant over time, probably as a result

of sequential somatic mutations.

Cutaneous patches containing superficial T-cell infiltrates with deletion of certain antigens and the

presence of dominant clonality are often diagnosed as mycosis fungoides, even when the

histopathological features are not fully diagnostic.

Clinically nodular skin lesions composed of atypical lymphoid infiltrates that exhibit abnormal

patterns of antigen expression and contain molecular evidence of dominant clonality are usually

regarded as lymphomas, even when this diagnosis cannot be made on morphological grounds

alone.

Thus, the principle has emerged that cutaneous lymphomas do not necessarily arise de novo but

can instead develop gradually from different types of chronic inflammatory processes.


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Clonality

Once a diagnosis of lymphoma has been established, TCR or IgH gene rearrangement assays

can also be used to determine the disease stage of patients and to monitor their response to

therapy.

Occult involvement of lymph nodes by mycosis fungoides is prognostically relevant.

Because of their enhanced sensitivity relative to routine histological testing, molecular assays can

more accurately define remission and detect early relapse.

Patients who stop treatment when representative skin biopsy specimens are nonspecifichistologically but still positive by molecular analysis tend to relapse rapidly.


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Polymerase Chain Reaction (PCR)

andSingle Nucleotide Polymorphism

Wh I h H G ?


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What Is the Human Genome?

Human Cell

Nucleus

Chromosomes

DNA d Ch St t


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DNA and Chromosome Structure

DNA molecule(chromosome)

Chemicalbases

A

T

G

C

Th G C t i G


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The Genome Contains Genes

Gene 2 Coding region Protein 2

Protein 1

Noncoding region

Noncoding region

Gene 1 Coding region

V i ti i th H G


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Variation in the Human Genome

Person 1 Person 2

= Variations in DNA

Wh t I V i ti i th G ?


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What Is Variation in the Genome?

Common Sequence

Variations

Polymorphism

Deletions

Translocations

Insertions

Chromosome

V i ti C i N Ch


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Variations Causing No Changes

= Variations in DNA that cause no changes

V i ti C i H l Ch


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Variations Causing Harmless Changes

= Variations in DNA that cause harmless changes

V i ti C i L t t Ch


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Variations Causing Latent Changes

Many years laterMany years later

= Variations in DNA that cause latent effects

SNP A th M t C


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SNPs Are the Most CommonType of Variation

At least 1 percent

of the populationMost of the population

Commonsequence

G to C

SNPsite

Variantsequence

Wh A SNP Si ifi t?


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Why Are SNPs Significant?

Person 1 Person 2

= SNP variations in DNA

SNP marks Gene A

Gene BGene A

SNP may cause Gene Bto make altered protein

Amino Acids


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Amino Acids

Lysine side chain

20 Different Amino Acids

Basic Structureof an Amino Acid

Graphic Representationof an Amino Acid

Lysine

Carboxyl group

Amino group

Genes to Proteins I


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Genes to Proteins I

DNA

T

AC

G

C

A

A

T

A

TG

C

A

T

T

A

U

G

C

G

U

U

A

U

AC

G

U

A

A

mRNA

Genes to Proteins II


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Genes to Proteins II

Genes to Proteins III


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Genes to Proteins III

Ribosome

mRNA

tRNA

A

Codons:AUG=Methionine=StartCGU=ArginineUAU=TyrosineACG=Threonine

UAA=Stop

Methionine

Arginine

Threonine

Tyrosine

U G C G U U A U A C U A AG

StopTyrosineMethionine

ThreonineArginine

Protein Folding and Function


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Protein Folding and Function

Amino acid chain grows

and folds

into a 3-D structure.

SNPs in Coding Regions


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SNPs in Coding RegionsNo Changes in Protein

DNA SNP C to G

RNA CodonCUG to CUC

ProteinLeucine to Leucine

No change in shape

Leucine Leucine

mRNA

G A C

C U G C U C

CUG CUC

G A G



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SNPs in Coding RegionsSubtle, Harmless Changes in Protein

DNA SNP A to C

RNA CodonGAU to GAG

ProteinAspartic acid

to Glutamic acid

Slight change in shape

Aspartic acid Glutamic acid

mRNA

C T A

G A U G A G

GAU GAG

C T C



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SNPs in Coding RegionsHarmful Changes in Protein Mutations

DNA SNP T to A

RNA CodonGAU to GUU

ProteinAspartic acid

to Valine

Change in shape

Aspartic acid Valine

mRNA

C T

G A U G U U

GAU GUU

C AA A


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PCR Requirements

Magnesium chloride: .5-

2.5mM

Buffer: pH 8.3-8.8

dNTPs: 20-200M

Primers: 0.1-0.5M

DNA Polymerase: 1-2.5

units

Target DNA: 1 g


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Gel electrophoresis

Heterozygous = having two

different alleles for a single

trait.

Wild type

Mutant

Homozygous = having identical

alleles for a single trait.



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SNPs in Coding RegionsSubtle Changes in Proteins

That Only Switch on Under Certain ConditionsSmoking

Switched-ongenes

Pattern AMany years later

= SNPs causing latent effects

Pattern BMany years later

SNP Profiles and Response to


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SNP Profiles and Response toDrug Therapy

Does Not Respond to Standard Drug Treatment

Breast Cancer Patients

Individual SNP Profiles Are Sorted

SNP profile A SNP profile B

SNP profile D

SNP profile E SNP profile C

Responds to Standard Drug Treatment


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Gene SNP

TNFa Chromosome: 6; Location: 6p21.3 rs2228088, rs3179060, rs35131721, rs4645843, rs1800620, rs1800618, rs11574936,

IL-1a Chromosome: 2; Location: 2q14 rs3783588, rs55910084, rs1801715, rs3783581, rs17562, rs17561, rs61538608, rs20540, rs3783531,

IL-2 Chromosome: 4; Location: 4q26-q27 rs1051753, rs2069763, rs3087209,

IL-4 Chromosome: 5; Location: 5q31.1 rs4986964, rs56279116, rs55743996, rs35648164, rs71645915,

IL-6 Chromosome: 7; Location: 7p21 rs34280821, rs2069830, rs11544633, rs56383910, rs34012176, rs71708959,

rs2069860, rs13306435, rs34709428, rs2069849,

IL-8 Chromosome: 4; Location: 4q13-q21 rs1803205, rs71745371,

IL-12 Chromosome: 5; Location: 5q31.1-q33.1 rs34012639, rs55780930, rs2230052, rs56272177, rs35990253, rs55691228, rs56043315, rs1042154,

rs1042155,

IL-13 Chromosome: 5; Location: 5q31 rs55733734, rs56035208, rs34255686, rs34654684, rs20541, rs56258826,

IL-17 Chromosome: 6; Location: 6p12 rs17880588, rs17878530,

IL-22 Chromosome: 12; Location: 12q15 rs2227507,

IL-23 Chromosome: 12; Location: 12q13.3 rs61937689, rs11465746, rs11171806, rs71772333,

VEGF Chromosome: 6; Location: 6p12 rs25648, rs45533131, rs62401172,

Stanford University
http://www.stanford.edu/http://www.pharmgkb.org/index.jsphttp://www.stanford.edu/http://www.stanford.edu/http://www.stanford.edu/


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Adalimumab, Etanercept

rs983332 at chr1:87904968This variant is significantly associated with the efficacy of anti-TNF (Adjusted P-value: 0.000005; OR: 10.2 (2.6, 59.2)). The study is a genome-wide associationstudy using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs928655 at chr1:89622162 in GBP6This variant is significantly associated with the efficacy of anti-TNF (Adjusted P-value: 0.00003; OR: 5.5 (1.8, 20.2)). The study is a genome-wide association study

using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy. rs13393173 at chr2:169097337 in LASS6This variant is significantly associated with the efficacy of anti-TNF (Adjusted P-value: 0.000004; OR: 6.8 (1.7, 40.3)). The study is a genome-wide association studyusing the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs437943 at chr4:35048493This variant is significantly associated with the efficacy of anti-TNF (Adjusted P-value: 0.000004; OR: 4.6 (1.8, 12.3)). The study is a genome-wide association studyusing the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs1800629 at chr6:31651010 in LTA, TNFThe TNF:(-308)G>A polymorphism is a weak marker for response to anti-TNF treatment, with A-allele carriers being significantly less l ikely to respond than patientswith the GG genotype.


rs854547 at chr7:94761792 in PPP1R9AThis variant is significantly associated with the efficacy of anti-TNF (Adjusted P-value: 0.000006; OR: 3.6 (1.5, 9.3)). The study is a genome-wide association studyusing the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs854548 at chr7:94763756 in PON1, PPP1R9AThis variant is significantly associated with the efficacy of anti-TNF (Adjusted P-value: 0.000003; OR: 8.5 (2.6, 36.5)). The study is a genome-wide association studyusing the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs854555 at chr7:94768327 in PON1This variant is significantly associated with the efficacy of anti-TNF (Adjusted P-value: 0.000002; OR: 4.6 (1.8, 12.3)). The study is a genome-wide association studyusing the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs868856 at chr9:27479251 in MOBKL2BThis variant is significantly associated with the efficacy of anti-TNF (Adjusted P-value: 0.0000005; OR: 4.9 (1.8, 14.0)). The study is a genome-wide associationstudy using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs7046653 at chr9:27480967 in MOBKL2BThis variant is significantly associated with the efficacy of anti-TNF (Adjusted P-value: 0.0000005; OR: 4.9 (1.8, 14.0)). The study is a genome-wide associationstudy using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs2814707 at chr9:27526397 in MOBKL2BThis variant is significantly associated with the efficacy of anti-TNF (Adjusted P-value: 0.000002; OR: 5.2 (1.8, 16.7)). The study is a genome-wide association studyusing the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.


rs774359 at chr9:27551049 in C9orf72This variant is significantly associated with the efficacy of anti-TNF (Adjusted P-value: 0.0000006; OR: 5.4 (1.9, 17.3)). The study is a genome-wide associationstudy using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.




Stanford University
http://www.pharmgkb.org/do/serve?objId=PA134964409&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134925480&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA30474&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA435&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33661&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33529&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33661&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33529&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134908144&objCls=Genehttp://www.pharmgkb.org/index.jsphttp://www.pharmgkb.org/do/serve?objId=PA134908144&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33529&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33661&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33529&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33661&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA435&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA30474&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134925480&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134964409&objCls=Genehttp://www.stanford.edu/http://www.stanford.edu/http://www.stanford.edu/http://www.stanford.edu/http://www.pharmgkb.org/index.jsp


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Infliximab

rs1061622 at chr1:12175542 in TNFRSF1BFor this SNP in the TNFRSF1B gene a significant correlation was found between 196R allele carriers and low response to infliximab therapy.

rs983332 at chr1:87904968This variant is significantly associated with the efficacy of anti-TNF treatment (Adjusted P-value: 0.000005; OR: 10.2 (2.6, 59.2)). The study is a genome-wideassociation study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs928655 at chr1:89622162 in GBP6This variant is significantly associated with the efficacy of anti-TNF treatment (Adjusted P-value: 0.00003; OR: 5.5 (1.8, 20.2)). The study is a genome-wideassociation study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs396991 at chr1:159781166 in FCGR3AThis variant may be a useful marker to predict response to infliximab in Japanese patients with rheumatoid arthritis.

rs13393173 at chr2:169097337 in LASS6This variant is significantly associated with the efficacy of anti-TNF treatment (Adjusted P-value: 0.000004; OR: 6.8 (1.7, 40.3)). The study is a genome-wideassociation study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.


rs1800629 at chr6:31651010 in LTA, TNFThe TNF:(-308)G>A polymorphism is a weak marker for response to anti-TNF treatment, with A-allele carriers being significantly less l ikely to respond than patientswith the GG genotype.

rs10945919 at chr6:164106667

This variant is significantly associated with the efficacy of anti-TNF treatment (Adjusted P-value: 0.0000003; OR: 4.6 (1.8, 12.3)). The study is a genome-wideassociation study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs854547 at chr7:94761792 in PPP1R9AThis variant is significantly associated with the efficacy of anti-TNF treatment (Adjusted P-value: 0.000006; OR: 3.6 (1.5, 9.3)). The study is a genome-wideassociation study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs854548 at chr7:94763756 in PON1, PPP1R9AThis variant is significantly associated with the efficacy of anti-TNF treatment (Adjusted P-value: 0.000003; OR: 8.5 (2.6, 36.5)). The study is a genome-wideassociation study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs854555 at chr7:94768327 in PON1This variant is significantly associated with the efficacy of anti-TNF treatment (Adjusted P-value: 0.000002; OR: 4.6 (1.8, 12.3)). The study is a genome-wideassociation study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

rs868856 at chr9:27479251 in MOBKL2BThis variant is significantly associated with the efficacy of anti-TNF treatment (Adjusted P-value: 0.0000005; OR: 4.9 (1.8, 14.0)). The study is a genome-wideassociation study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.




rs774359 at chr9:27551049 in C9orf72This variant is significantly associated with the efficacy of anti-TNF treatment (Adjusted P-value: 0.0000006; OR: 5.4 (1.9, 17.3)). The study is a genome-wideassociation study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.


rs6028945 at chr20:38254219This variant is significantly associated with the efficacy of anti-TNF treatment (Adjusted P-value: 0.0000002; OR: 11.2 (2.3, 108.1)). The study is a genome-wide

association study using the Illumina HapMap300 SNP chip on 89 RA patients prospectively followed after beginning of anti-TNF therapy.

Stanford University
http://www.pharmgkb.org/do/serve?objId=PA36610&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134964409&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA28065&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134925480&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA30474&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA435&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33661&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33529&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33661&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33529&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134908144&objCls=Genehttp://www.pharmgkb.org/index.jsphttp://www.pharmgkb.org/do/serve?objId=PA134908144&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134886513&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33529&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33661&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33529&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA33661&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA435&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA30474&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134925480&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA28065&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134964409&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA36610&objCls=Genehttp://www.stanford.edu/http://www.stanford.edu/http://www.stanford.edu/http://www.stanford.edu/http://www.pharmgkb.org/index.jsp


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Methotrexate rs4846051 at chr1:11777044 in MTHFR

The C allele of this variant was associated with increased risk of toxicity in African American Rheumatoid Arthritis patients receiving methotrexate.

rs1801131 at chr1:11777063 in MTHFRAt 6 months methotrexate and folic acid therapy, of early rheumatoid arthritis patients with the MTHFR 1298AA genotype showed good improvement relative tocombined CA and AA genotypes (OR 2.3), while 1298C allele carriers developed more adverse drug events (OR 2.5) (e.g. pneumonitis, gastrointestinal ADEs, skin

and mucosal ADEs, and elevated liver rs1801133 at chr1:11778965 in CLCN6, MTHFRThis variant is associated with methotrexated-induced mucositis, thrombocytopenia and hepatic toxicity

rs1801133 at chr1:11778965 in CLCN6, MTHFRIn 330 patients who completed 3 months methotrexate treatment for psoriasis, no significant genotypic associations were found between clinical outcome (e.g.efficacy, toxicity) and 50 SNPs in pathway genes for methotrexate metabolism (ATIC, FPGS, GGH, MTHFR), including 47 common ( >5% minor allele frequency)haplotype-tagging SNPs (r(2) > 0.8) plus 3

rs1801133 at chr1:11778965 in CLCN6, MTHFRMTHFR rs1801133, 667CT or 667TT genotypes were associated with an increased risk of methotrexate treatment discontinuation due to adverse events (relativerisk 2.01), mostly as a result of increased risk of elevated levels of liver enzyme alanine aminotransferase (relative risk 2.38) in rheumatoid arthritis patients.

rs1801133 at chr1:11778965 in CLCN6, MTHFRIn a retrospective analysis of 61 Italian patients experiencing methotrexate toxicity during treatment for acute lymphoblastic leukemia or acute promyelocyticleukemia, carriers of the MTHFR 677TT genotype (60%) showed significantly greater drug-induced toxicity (p=0.03) compared to CC and CT genotypes.

rs1801133 at chr1:11778965 in CLCN6, MTHFRRisk or phenotype-associated allele: CT and TT genotypes. Phenotype: The 677 CT or TT genotypes were associated with greater incidence of discontinuation ofmethorexate treatment because of adverse events, mainly due to elevation of liver enzymes. Study size: 236. Study population/ethnicity: Patients who startedmethorexate treatment with (n = 157) or without (n = 79) folic or folinic acid supplementation for rheumatoid arthritis. Significance metric(s): RR = 2.01 Type ofassociation: CO, GN.

rs13120400 at chr4:89252551 inABCG2SNP is associated with clinical reponse to methotrexate in patients with psoriasis.

rs17731538 at chr4:89274403 inABCG2SNP is associated with clinical reponse to methotrexate in patients with psoriasis.

rs11545078 at chr8:64101318 in GGHGGH 452C>T has been associated with decreased catalytic activity and higher accumulation of long-chain methotrexate-polyglutamate.

rs1800909 at chr8:64113866 in GGHThis study found that only patients with the GGH 16C-allele and one or no copies of the GGH 452C-16T haplotype were associated with good clinical improvementat 3 months upon treatment with methotrexate.

rs4149081 at chr12:21269288 in SLCO1B1Risk or phenotype-associated allele: G allele, with additive genotypic effect. Phenotype: Genome-wide analysis of 398,699 germline SNPs showed association ofthe rs4149081 G allele with increased methotrexate (MTX) plasma clearance, with an additive effect per G allele (increase of 12.7 mL/min/m(2) per allele in 434subjects), after adjusting for age, race, sex, and MTX regimen. Variants rs11045879 and rs4149081 were in linkage disequilibrium (r(2) = 1). The G allele was

associated with increased risk of gastrointestinal toxicity (mucositis) (OR = 15.3, p = 0.03). Pharmacokinetics differed by e thnicity (MTX clearance:African>Caucasian). Study size: 434 (discovery cohort), 206 (independent validation cohort), 640 (combined cohort). Study population/ethnicity: Multiethnic children(5.92 median age , 1.02-18.85 range) with ALL given 3,014 courses of methotrexate at 2-5 g/m(2) enrolled in Tennessee. Significance metric(s): increased MTXclearance: p = 1.7 x 10(-9) (n = 434), p = 0.017 (n = 206), p = 6.7 x 10(-10) (n = 640); increased GI toxicity: OR = 15.3, p = 0.03. Type of association: CO; GN; PK;ADR; TOX
http://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA26551&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA26551&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA26551&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA26551&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA26551&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA390&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA390&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA432&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA432&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA134865839&objCls=Genehttp://www.pharmgkb.org/index.jsphttp://www.pharmgkb.org/do/serve?objId=PA134865839&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA432&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA432&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA390&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA390&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA26551&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA26551&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA26551&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA26551&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA26551&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Genehttp://www.pharmgkb.org/do/serve?objId=PA245&objCls=Gene


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Fluorescence in Situ Hybridisation (FISH)


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Molecular Cytogenetic Analysis of Chromosomal Translocation

Translocations generate novelchromosomes. In a translocation, asegment from one chromosome istransferred to a nonhomologouschromosome or to a new site on the samechromosome.

The genomes of closely related species,they can see that translocations haveoccurred many times during the course ofevolution.

Translocations that give an organism anadaptive advantage are very rare.

Translocations are more often associatedwith negative consequences like cancer.

In many cases, are considered to be theprimary cause of various cancers.

Nonreciprocal translocations are one-way translocations in which a

chromosomal segment is transferred to a nonhomologous chromosome. a)

An idiogram of a reciprocal translocation between chromosomes 12 and

17. b) An ideogram of a Robertsonian translocation between

chromosomes 14 and 21.


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Translocations Can Produce Oncogenes

The translocation places the coding sequence of one gene (Gene B) in proximity to the regulatorysequence for a different gene (Gene A).

The translocation involving chromosomes 8 and 14 places the MYC proto-oncogene fromchromosome 8 under the control of the powerful immunoglobin heavy chain gene (IGH) promoteron chromosome 14.

The MYC protein normally signals for cell proliferation, and the translocation causes high levels ofMYC overexpression in lymphoid cells, where the IGH promoter is normally active.

Aberrant oncogene expression from chromosomal translocation frequently leads to cellular

immortalization and clonal expansion.

Translocations Mb ( j b k i t i 150 b )

Mb ( j b k i t i 150 b )


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Translocations

Can Produce

Oncogenes

A rearrangement of the bcl-2proto-oncogene onchromosome 18 with theimmunoglobulin heavy chainregion on chromosome 14,leads to deregulated BCL-2

production. Bcl-2 has been shown to

prevent programmed celldeath (apoptosis) thusimmortalizing the cell.

The t(14;18) translocation ischaracteristic of B-celllymphomas, occurring in up to90% of follicular lymphomas.

It is also found in 20% to 30%of diffuse large B-celllymphomas, where it is anindicator of poor prognosis.

Bcl2 Chromosome 18

Mbr (major breakpoint region, 150 bp)

JH

C

Double strand DNA break by RAG1/2

Chromosome 14

Bcl2 C t(14;18) translocation

bcl2 CE C 3E

Unregulation of Bcl2 expression by IgH enhancers

Translocation takes place in B cell precursors.

Transformation takes place

during B cell activation in GC.

Bcl2 Chromosome 18

Mbr (major breakpoint region, 150 bp)

JH

C

Double strand DNA break by RAG1/2

Chromosome 14

Bcl2 C t(14;18) translocation

bcl2 CE C 3E

Unregulation of Bcl2 expression by IgH enhancers

Translocation takes place in B cell precursors.

Transformation takes place

during B cell activation in GC.

activation

Germinal center Germinal center

apoptosis

IgH-Bcl2

activation


Plasma cells

Memory cells

follicular lymphoma

Apoptosis inhibitedMost follicular lymphoma Ig V regions containsomatic hypermutation.

activation


apoptosis

IgH-Bcl2

activation


Plasma cells

Memory cells

follicular lymphoma

Apoptosis inhibitedMost follicular lymphoma Ig V regions containsomatic hypermutation.


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Depending on probe design (eg, the

distance between the regionsrecognized) and the state of thegenomic DNA at the time of fixation,a fused signal may appear either asa colocalized red and green signal oras a single yellow signal.

When using break-apart probes,red/green signal pairs will

occasionally appear to be slightlyseparated because of the secondarystructure of the target DNA.


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(A) Interphase nuclei hybridized with the LSI IGH break apart probe (Vysis).The two nuclei at the top display a significant dissociation of the red and

green signals (arrows) indicating the presence of a translocation affectingthe IGH.

(B) Interphase nucleus with the LSI MYC/IGH double fusion probe (Vysis).The presence of two fused red and green signals (arrows) indicates that atranslocation t(8;14)(q24;q32) juxtaposing the MYC and IGH loci has takenplace. The isolated red and green signals point to the unrearranged MYCand IGH alleles, respectively.


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Deregulation of BCL6 either by juxtaposition next to an IG locus or by promotor substitution due toa chromosomal translocation can be detected in about 30% of systemic diffuse-large B-celllymphomas (DLCBL).

t(14;18) cytogenetically identical to that occurring in FL can lead to activation of the MALT1oncogene. This gene is also targeted by a recurrent t(11;18)(q21;q21) present in approximately30% of systemic marginal zone lymphomas of MALT type, which leads to fusion of the MALT1gene with the apoptosis inhibitor-2 (API2) gene in 18q21.


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Molecular Cytogenetic Analysis of Chromosomal Translocation in

Primary Cutaneous B-cell Lymphomas

Overall, translocations affecting one IG locus are estimated to be present in at leasthalf of the nodal B-cell non-Hodgkin lymphomas. In contrast to systemic B-cell

lymphomas only few data exist on the presence of recurrent translocations in primary

cutaneous B-cell lymphomas (PCBCL).

The t(14;18) translocation does not occur in PCBCL, which suggests the involvement

of different pathogenetic mechanisms compared with their nodal counterparts.

The detection of a t(14;18) translocation in cutaneous B-cell lymphoma should

suggest the presence of systemic disease, which underlies the need for exhaustive

staging procedures.


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Gene Microarray Expression Technology

Oncogenes: BAX, BCL2L1, CASP8, CDK4, ELK1,ETS1, HGF, JAK2, JUNB, JUND, KIT, KITLG, MCL1,


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ETS1, HGF, JAK2, JUNB, JUND, KIT, KITLG, MCL1,MET, MOS, MYB, NFKBIA, NRAS, PIK3CA, PML,PRKCA, RAF1, RARA, REL, ROS1, RUNX1, SRC,STAT3, ZHX2.

Tumor Suppressor Genes: ATM, BRCA1, BRCA2,CDH1, CDKN2B, CDKN3, E2F1, FHIT, FOXD3, HIC1,IGF2R, MEN1, MGMT, MLH1, NF1, NF2, RASSF1,RUNX3, S100A4, SERPINB5, SMAD4, STK11, TP73,TSC1, VHL, WT1, WWOX, XRCC1.

Oncogenic & Tumor Suppressor Properties: BCR,EGF, ERBB2, ESR1, FOS, HRAS, JUN, KRAS, MDM2,MYC, MYCN, NFKB1, PIK3C2A, RB1, RET, SH3PXD2A,TGFB1, TNF, TP53.

Transcription Factors: ABL1, BRCA1, BRCA2,CDKN2A, CTNNB1, E2F1, ELK1, ESR1, ETS1, FOS,FOXD3, HIC1, JUN, JUNB, JUND, MDM2, MEN1, MYB,MYC, MYCN, NF1, NFKB1, PML, RARA, RB1, REL,RUNX1, RUNX3, SMAD4, STAT3, TGFB1, TNF, TP53,TP73, TSC1, VHL, WT1, ZHX2.

Epithelial-to-Mesenchymal Transition: BRCA2,CDKN2B, CTNNB1, ERBB2, HGF, JAK2, KIT, MCL1,NF1, RUNX3, S100A4, SMAD4, TGFB1, VHL.

Angiogenesis: AKT1, CTNNB1, EGF, ERBB2, NF1,PML, RUNX1, TGFB1.

Apoptosis: BAX, BCL2, BCL2L1, BRCA1, CASP8,E2F1, MCL1, MGMT, TNF, VHL.

Cell Adhesion: APC, CDH1, CDKN2A, CTNNB1,KITLG, NF1, NF2, TGFB1.

Cell Cycle: ATM, BRCA1, BRCA2, CCND1, CDK4,CDKN1A, CDKN2A, CDKN2B, CDKN3, E2F1, HGF,MEN1, STK11, TP53.

Chemotaxis, Cell Migration & Motility: HRAS, JAK2,MET, NF1, NF2, PRKCA, SERPINB5, STAT3.

DNA Damage & Repair: ABL1, APC, ATM, BRCA1,BRCA2, CDKN1A, MEN1, MGMT, MLH1, PML, TP53,

TP73, XRCC1.


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Non-Hodgkin lymphoma (NHL) Non-Hodgkin lymphoma (NHL) is a heterogeneous, complex, and progressive clonal expansion of

B-, T-lymphocytes and rarely NK-cells or their precursors.

Our taxonomy of lymphomas, which is based mostly on histopathology and immunophenotyping,

includes about 30 distinct entities arising from diverse cells types. The genetic complexity of lymphomas probably explains the clinical diversity with traditional

methods and genomic expression analysis.

Microarrays technique is effective in deciphering this clinical diversity.

A number of published studies identify gene expression signatures for major non-Hodgkinlymphoma types and subtypes, and uncover gene expression patterns that correlate with variouscharacteristics of non-Hodgkin lymphoma.

Mature T-cell and NK-cell neoplasms Mycosis fungoides (MF)

Variants of MF Pagetoid reticulosis (localized disease)

Folliculotropic, syringotropic, granulomatous variants

Subtype of MF

Granulomatous slack skin

Sezary syndrome

CD30+ T-cell lymphoproliferative disorders of the skin

Lymphomatoid papulosis

Primary cutaneous anaplastic large cell lymphoma

Subcutaneous panniculitis-like T-cell lymphoma Primary cutaneous peripheral T-Cell lymphoma (PTL),unspecified

Subtypes of PTL

Primary cutaneous aggressive epidermotropic CD8+T-cell lymphoma (provisional)

Cutaneous gamma/delta-positive T-cell lymphoma(provisional)

Primary cutaneous CD4+ small/medium-sizedpleomorphic T-cell lymphoma (provisional)

Extranodal NK/T-cell lymphoma, nasal type

Hydroa vacciniforme-like lymphoma (variant)

Adult T-cell leukemia/lymphoma

Angioimmunoblastic T-cell lymphoma

Mature B-cell neoplasms Cutaneous marginal zone B-cell lymphoma (MALT-type)

Primary cutaneous follicle center lymphoma

Growth patterns

Follicular

Follicular and diffuse

Diffuse

Cutaneous diffuse large B-cell lymphoma, leg type

Cutaneous diffuse large B-cell lymphoma, others

Intravascular large B-cell lymphoma

Lymphomatoid granulomatosis Chronic lymphocytic leukemia

Mantle cell lymphoma

Burkitt lymphoma

Immature hematopoietic malignancies

Blastic NK-cell lymphoma CD4+/CD56+ hematodermicneoplasm

Precursor lymphoblastic leukemia/lymphoma

T-lymphoblastic lymphoma

B-lymphoblastic lymphoma

Myeloid and monocytic leukemias

Hodgkin lymphoma


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Current Microarray Technology

Tissue Lysis mRNA cDNA

OpticalDetection

Scanning

Image Analysis

Data Analysis

Amplification

Fluorescent Labeling


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In standard microarrays, the probes are attached via surface engineering to a solid surface by acovalent bond to a chemical matrix (via epoxy-silane, amino-silane, lysine, polyacrylamide orothers).

The solid surface can be glass or a silicon chip, in which case they are colloquially known as anAffy chip when an Affymetrix chip is used.

The core principle behind microarrays is hybridization between two DNA strands, the property ofcomplementary nucleic acid sequences to specifically pair with each other by forming hydrogenbonds between complementary nucleotide base pairs.

A high number of complementary base pairs in a nucleotide sequence means tighter non-covalentbonding between the two strands.

After washing off of non-specific bonding sequences, only strongly paired strands will remainhybridized.

So fluorescently labelled target sequences that bind to a probe sequence generate a signal thatdepends on the strength of the hybridization determined by the number of paired bases, thehybridization conditions (such as temperature), and washing after hybridization.


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Two-color microarrays or two-channel microarrays are typicallyhybridized with cDNA preparedfrom two samples to be compared(e.g. diseased tissue versushealthy tissue) and that are labeledwith two different fluorophores.

Fluorescent dyescommonly used for cDN

A


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Microarray analysis

commonly used for cDNAlabeling include Cy3, whichhas a fluorescenceemission wavelength of 570nm (corresponding to thegreen part of the lightspectrum), and Cy5 with afluorescence emissionwavelength of 670 nm(corresponding to the redpart of the light spectrum).

The two Cy-labeled cDNAsamples are mixed andhybridized to a singlemicroarray that is thenscanned in a microarrayscanner to visualizefluorescence of the twofluorophores after excitationwith a laser beam of a

defined wavelength. Relative intensities of each

fluorophore may then beused in ratio-basedanalysis to identify up-regulated and down-regulated genes.


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Repression Induction


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Components of DNA Microarray image analysis are

(1) Grid Alignment Problem,

(2) Foreground Separation,

(3) Quality Assurance,

(4) Quantification and

(5) Normalization.


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Variations in microarray image Data processing:

grid geometry,

foreground and background intensity,

spot morphology

Right image shows variations of spots; a regular

spot, an inverse spot or a ghost shape, a

spatially deviating spot inside of a grid cell, a

spot radius deviation, a tapering spot or a comet

shape, spot with a hole or a doughnut shape, a

partially missing spot and a scratched spot.

Examples of accurate (top) and inaccurate

(bottom) foreground separation


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Hierarchical clustering Microarray data sets are commonly very large, and analytical precision is influenced

by a number of variables. Statistical challenges include taking into account effects of

background noise and appropriate normalization of the data. For statistical analysis and visualization of gene expression data a large number of

commercial and non-commercial software tools have been developed (e.g., Gene

Spring, Gene Cluster, Cluster, and Treevoew, SAM and dCHIP).

Hierarchical clustering output as dendogram or tree attached to a heatmap

representation of the clustered matrix

Clustering aims at grouping objects, such as genes, together, according to somemeasure of similarity, so that objects within one group or cluster are more similar to

each other than to objects in other groups. It is a mean to visualize patterns of gene

expression in the data.


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Hierarchical clustering The final, computational form, of

the Pearson correlation coefficien:

To return to the context ofhierarchical clustering, a Pearsoncorrelation coefficient must becomputed for every possible genecomparison.

When clustering an entire genome

of 6,000 or more genes this canmean a considerable number ofcomparisons must be performed,yet the results can providevaluable generalizations about thegenes' relationships

Documents

LP 6 TesteMoleculareGeneticeDermatologie Part I