Comprehensive Genomic Profiling to Optimize Precision‐Focused Cancer Managementclinicalwebcasts.com/slidecasts/2017/Singapore-SlideCAST-286.pdf · 1 Notes: Notes: Comprehensive

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Comprehensive Genomic Profiling to Optimize Precision‐Focused Cancer Management

A Year 2016 and Beyond Science‐to‐Best Practice Cancer Update and Scientific Exchange Meeting for the Asia‐Based Oncology,

Genomic, and Hematology Specialist

The Evidence‐Based Journey from Targets to Therapy

Welcome and Introduction

Professor Nir Peled, MD, PhD ‐ Program ChairHead, Thoracic Cancer Unit and Center for Precision Medicine

Davidoff Cancer CenterTel Aviv UniversityTel Aviv, Israel

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Presenter Disclosure

Advisor for and honorarium from AZ, BI, BMS, Lilly , MSD, Novartis, Pfizer, Roche

Audience Response System

Getting to Know You and Your Practice Patterns

What is your practice specialty within the field of oncology?

1) General medical oncology

2) Organ specific medical oncology

3) Both medical and radiation oncology

4) Para‐medical (bioinformatics/lab/scientist)

5) Onco‐pathology

Please Enter Your Response On Your Keypad

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How many years have you been in oncology practice?

1) Up to 3 years

2) 3‐5 years

3) 5‐10 years

4) 10‐20 years

5) 20 years or more




What percentage of your cancer patients do you treat with targeted therapy (i.e. precision‐focused cancer medicine)?

1) Less than 10%

2) 10% ‐ 20%

3) 20% ‐ 30%

4) 30% ‐ 50%

5) 50% ‐ 75%

6) 75% ‐ 100%




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In your overall clinical experience, what percentage of your cancer patients do you feel have an actionable, druggable mutation?

1) Less than 10%

2) 10% ‐ 20%

3) 20% ‐ 30%

4) 30% ‐ 50%

5) 50% ‐ 75%

6) 75% ‐ 100%




Your targeted cancer therapy is most often based on:

1) Immunohistochemistry

2) PCR‐based mutation detection

3) FISH

4) I am not sure




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In your view, the main advantage of Hybrid Capture‐Based, Next Generation Sequencing (HC‐NGS) over “standard” NGS is:

1) HC‐NGS requires less tissue

2) HC‐NGS is mainly good for common mutations

3) HC‐NGS is much faster

4) None of the above

5) I don’t know




8:10 AM –8:30 AM ‐Current and Evolving Technologies for Comprehensive Genomic Profiling in CancerDr. Brendan Pang , MBBS, FRCPath(UK)

8:30 AM – 8:50 AM ‐ Next‐Generation Sequencing Approaches for Understanding the Genetic Basis of Cancers for Personalized Medicine: A Review of Available Technologies and Methods

Professor Maria Li Lung, PhD

9:10 AM – 9:30 AM ‐ Treatment of Patients with Advanced NSCLC Based on Genomic Analysis of the Tumor Professor James CH Yang, MD, PhD

9:30 AM – 9:50 AM ‐ The Clinical Implications of Using Hybrid Capturing NGS in Lung CancerProfessor Nir Peled, MD, PhD, FCCP – Program Chair

10:10 AM – 10:30 AM ‐ The Role of Genomic Profiling to Optimize Clinical Outcomes in Patients with Breast Cancer

Professor Rebecca Dent, MD, FRCP

11:00 AM – 11:20 AM ‐ Comprehensive Genomic Profiling of Gynaecological Cancers to Optimize TherapyDr David SP Tan, BSc(Hons), MBBS(Hons)(London), MRCP(UK)(Medical Oncology), PhD(London)

11:30 AM – 11:50 AM ‐ Comprehensive Genomic Profiling for Gastrointestinal CancersDr. Wong Seng Weng, MBBS, MRCP(UK), FAMS (Medical Oncology)

Scientific Program –Morning Agenda

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1:00 PM – 2:40 PM Interactive Mini‐Roundtables with Faculty Moderators: Participants and Faculty Analyze and Discuss Clinical Cases in Cancer‐Focused Precision Medicine

1:00 PM – 1:25 PM Case Management Session: Applying NGS and Actionable Genomic Alterations to Patients with Lung Cancer: Professor Peled

1:25 PM – 1:50 PM Case Management Session: Applying NGS and Actionable Genomic Alterations to Patients with Breast Cancer: Professor Dent

1:50 PM – 2:15 PM Case Management Session: Applying NGS and Actionable Genomic Alterations to Patients with Tumor of Unknown Etiology: Professors Lung and Pang

2:15 PM – 2:40 PM Case Management Session: Applying NGS and Actionable Genomic Alterations to Patients with Lung Cancer: Professor Yang

Scientific Program Agenda –Afternoon Roundtable Sessions

Germline Variation Somatic Mutation Personalized Care

Precision Medicine: Science Serving Patients

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Cancer Genomics

Genetic subtypes of glioblastoma, gastric and other cancers identified

via TCGA research

2005

Hallmarks of Cancer published

2000 2010‐2014

• Advent of the “precision medicine” era

• But cancer’s biology is far more complex than we had imagined

Image Source: TCGA

The Cancer Genome Atlas (TCGA) launches

Cancer Genomics

Genomic Landscape of 5,000 Human Cancers

Source: MacConaill, L, et. al., J Mol Diagn 2014, 16: 660-672

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Common Cancers Now Collections of Rare Cancers

Catherine B. Meador et al. Clin Cancer Res 2014;20:2264-2275

EGFR

KRAS

Unknown

What Impact Does Molecular Information Have? Evolving Clinical Practice Through Disease Biology

Unknown

MET Splice SiteMET Amplification

KRAS

NRAS

ROS1 Fusions

RET Fusions

EGFR

ALK Fusions

HER2BRAF

PIK3CA AKT1MAP2K1

Molecular profiling has changed the classification of lung cancer

Today, there are many known genomic alterations that can drive

the development of cancer...

2004 2015

Modified and updated from Pao and Hutchinson (2012) Chipping away at the lung cancer genome. Nature Medicine 18(3):349‐51.

A decade ago, genomic alterations were important in only around

1/3 of NSCLC cases

NSCLC: Non‐small cell lung cancer

9

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Trastuzumab, Afatinib

Vemurafenib, Dabrafenib

Crizotinib, Ceritinib

Erlotinib, Afatinib

Cabozantinib

Trametinib

2015

Modified and updated from Pao and Hutchinson (2012) Chipping away at the lung cancer genome. Nature Medicine 18(3):349-51.

Crizotinib

Crizotinib

…and many new targeted therapy options to treat patients harboring these genomic alterations

Unknown


KRAS

NRAS

ROS1 Fusions

RET Fusions

EGFR

ALK Fusions

HER2BRAF

PIK3CA AKT1

MAP2K1

Cell 2011 144, 646‐674DOI: (10.1016/j.cell.2011.02.013)

Hallmarks of Cancer: Therapeutic Implications

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Comprehensive Genomic ProfilingUnderstanding the Diagnostic Difference

Number of Targeted Therapeutics is RisingKnowing Which Tests to Order is the Challenge

FBXW7ROS1 KRAS

RET

VEGF/VEGFR

AURKA

CDK4

CCND1ERBB3

DDR2

DNMT3A

GNAQ

BRCA1

BRAF

CDK6

AKT1

TSC1/2

METNOTCH1

TSC2

PIK3CANF1

FLT3

CDKN2A

PTEN

HER2

KDR

GATA3RAF1

IGF1R

ALK TNF

STK11

IGF/IGFR

FGFR1

MAP2K1Year

2005 2012 2015 2020

~15 approved drugs hitting ~10 targets

TodayComing Soon

~700 compounds targeting~150 targets in development

2025IDH1/2

Extrapolated from BioCentury Online Intelligence Database

Target Markers

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Current Testing ModelsMultiple Diagnostic Tests Exhaust Tissue and Resources

Single assays, «tissue is the issue» Comprehensive tumour analysis...

...and continuous monitoring

RNASequencing

DNASequencing

Blood DNA Sequencing

Imaging

8‐10 slides

Lung tissue biopsy

Enough tissue for only 2‐3 individual tests

Produces a single snapshot

8‐10 slides

Example: Lung cancer

Routine Single‐Marker Molecular TestThe Most Common Type of Molecular Testing

CATEGORY ONE

CATEGORY TWO

CATEGORY THREE

Routine single marker molecular tests such as IHC, PCR and FISH that have been used for decades and will continue to play an important role in cancer diagnosis

missedmissed

foundmissed

missed

FISH: fluorescence in situ hybridization; IHC: Immunohistochemistry; PCR: Polymerase chain reaction

12

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Multi‐Gene “Hot Spot” TestBroader Testing Focused On a Narrow Subset Of Genes

CATEGORY ONE

CATEGORY TWO

CATEGORY THREE

The hot spot NGS panels identify pre‐specified mutations occurring in very limited areas of genes of interest and fail to detect all classes of genomic alterations

missed foundmissed

missedfound

Hybrid CaptureNGS‐Based, Comprehensive Genomic ProfilingThe Most Comprehensive Genomic Test Available

CATEGORY ONE

CATEGORY TWO

CATEGORY THREE

Hybrid capture NGS‐based comprehensivegenomic profiling approach of testing all of the known clinically relevant cancer genes for all classes of alterations

foundfound

foundfound

found

Hybrid Capture NGS‐Based, Comprehensive Genomic Profiling

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The Rise of Targeted Therapy

Precision Medicine

• Cancers classified by molecular abnormalities and site of origin

• Exceptional success when treatment is matched to a driver mutation

20011998

First targeted drug: rituximab

Trastuzumabintroduced for HER2+ breast

cancer Imatinibintroduced

1997‐2016

100+ FDA‐approved targeted cancer drug

indications

1997

Image Sources: Slamon D, et al. Engl J Med 2001; 344:783‐792; NCI; FDA

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Timeline of Selected Major Discoveries in Lung Cancer Treatment

Source: Katerina Politi, and Roy S. Herbst Clin Cancer Res 2015;21:2213-2220

Precision Medicine

Photographs were taken:

A. Before initiation of vemurafenib

B. After 15 weeks of therapywith vemurafenib

C. At relapse, after 23 weeks of therapy.

Source: Wagle, N et al. Dissecting Therapeutic Resistance to RAF Inhibition in Melanoma by Tumor Genomic Profiling. JCO August 1, 2011 vol. 29 no. 22 3085‐3096

But precision medicine has brought new complexity – and

challenges

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The Range, Specificity, and Sensitivity of Genomic‐Focused Technologies Available for Identifying Molecular Drivers for Targeted Cancer Therapy

Hot Spot Panels, FISH, and Hybrid Capture‐Based Comprehensive Genomic Profiling—What is the Gold Standard? Why?

Dr. Brendan Pang , MBBS, FRCPath (UK)

Consultant, Department of Pathology Laboratory (Section) Director, Diagnostic Molecular Oncology Centre (DMOC) National University Hospital (NUH) Clinical Assistant Professor Clinician Tract, Department of Pathology Yong Loo Lin School of Medicine National

University Singapore (NUS) Singapore

I have received honorariums and/or speaker fees for consulting, speaking, and advisory boards from:

MSD, Roche, AstraZeneca


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Milestones of DNA Sequencing Technology

Watson and Crick

Source: www.esciencecentral.org

AB370A: sequence 96 samples simultaneously, 500 kb per day

1950s Discovery of DNA replication mechanism

1970s Invention of Sanger DNA sequencing

1987 Invention of automated DNA

sequencer

Next-Generation

Sequencing

Comprehensive Genomic Profiling

1869 Discovery of DNA

1920-50s Discovery of DNA structure

Overview of NGS Comprehensive Genomic Profiling

Hanahan D and Weinberg RA, Cell 144, 2011

1. Library preparation

2. Cluster generation

3. Sequencing

4. Reference mapping

5. Variant calling

6. Bioinformatics analysis

DNA sample preparation

EGFRINHIBITORS

Cyclin-dependentKinase inhibitors

TelomeraseInhibitors

Immune activatingAnti-CTLA4 mAb

Selective anti-inflammatory drugs

Inhibitors of HGF/c-Met

Inhibitors of VEGF signaling

PARPinhibitors

ProapoptoticBH3 mimetics

Aerobic glycolysisinhibitors

ActivatingInvasion&

metastasisi

Inducingangiogenesis

GenimeInstability&mutation

Resistingcell

death

Deregulatingcelluar

energetice

SustainingProliferative

signaling

Evadinggrowth

suppressors

AvoidingImmune

destruction

EnablingReplicativeimmortality

Tumor-Promoting

inflammation

NGS Comprehensive

Genomic Profiling

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Reference Mapping to Convert Raw Data to Meaningful DNA Sequence

Reference genome sequence

Sequencing results in a library of short DNA sequences

4. Reference mapping

5. Variant calling

Identify Abnormalities in the DNA Sequence (Variant Calling)

• Due to tumor heterogeneity, not all cancer cells contain every variant. Bioinformatics to identify true variants and separate from sequencing artifact.

• Variant annotation: identify variants that are clinically relevant.

Reference genome sequence

6. Bioinformatics analysis5. Variant calling

18

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Number of Targeted Therapeutics is RisingKnowing Which Tests to Order is the Challenge

FBXW7ROS1 KRAS

RET

VEGF/VEGFR

AURKA

CDK4

CCND1ERBB3

DDR2

DNMT3A

GNAQ

BRCA1

BRAF

CDK6

AKT1

TSC1/2

METNOTCH1

TSC2

PIK3CANF1

FLT3

CDKN2A

PTEN

HER2

KDR

GATA3RAF1

IGF1R

ALK TNF

STK11

IGF/IGFR

FGFR1

MAP2K1Year

2005 2012 2015 2020

~15 approved drugs hitting ~10 targets

TodayComing Soon

~700 compounds targeting~150 targets in development

2025IDH1/2

Extrapolated from BioCentury Online Intelligence Database

Target Markers

Current Testing ModelsMultiple Diagnostic Tests Exhaust Tissue and Resources

Single assays, «tissue is the issue» Comprehensive tumour analysis...

...and continuous monitoring

RNASequencing

DNASequencing

Blood DNA Sequencing

Imaging

8‐10 slides

Lung tissue biopsy

Enough tissue for only 2‐3 individual tests

Produces a single snapshot

8‐10 slides

Example: Lung cancer

19

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NCCN Guidelines for NSCLC Version 4.2016, p16

The NCCN NSCLC Guidelines Panel strongly endorses broader molecular profiling with the goal of identifying rare driver mutations for which effective drugs may already be available, or to appropriately counsel patients regarding the availability of clinical trials. Broad

molecular profiling is a key component of the improvement of care of patients with NSCLC.

Histologic Subtype Testing

Adapted from NCCN NSCLC v. 4.2016, summary slide NSCL‐16 "Systematic Therapy for Metastatic Disease“p29. Used with permission.

‐EGFRmutation testing (category 1)

‐ALK testing (category 1)

‐EGFR and ALK should be conducted as part of broad

molecular profiling

‐Consider EGFRmutation and ALK testing especially in never

smokers or small biopsy specimens, or mixed histology

‐EGFR and ALK should be conducted as part of broad

molecular profiling

Metastatic Disease:‐Establish histological

subtype with adequate tissue for molecular

testing, consider rebiopsyif appropriate)

‐Integrate palliative care (see guidelines)

‐Adenocarcinoma‐Large cell‐NSCLC NOS

‐Squamous Cell CA

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Sensitive EGFR Mutation Testing – Single Gene Tests

MethodAnalytical selectivity

Coverage of

mutationsKey Reference for Method Equipment TAT

Sanger DNA Sequencing coupled withmacro/micro‐dissection

5‐10%(~ 20% without macro‐

dissection). Macro‐dissection is highly recommended for samples with less than 50% tumour

>99% (this method can detect novel changes)

•Eberhard DA et al. J Clin Oncol; 26 (6): 983‐993 2008•Ellison G, et al. J Exp Clin Cancer Res; 6(29)132 2010•Molina‐Vila, M, et al Journal of Thoracic Oncology: 3 (11) 1224‐1235, 2008•Macrodissection: EGFR Mutation expert training: EGFR‐mutation.com (video)

DNA sequencer 2‐3 days

Fragment length analysis

~ 5% >99% of indelsonly

•Molina‐Vila, M, et al Journal of Thoracic Oncology: 3(11) 1224‐1235, 2008

Capillary electrophoresis/ DNA sequencer

1 day

PNA LNA Clamp ~ 1% 90‐95% (detects 29 target mutations)

•Nagai Y et al. Cancer Res; 65, 7276‐7282 2005•Miyazawa, H, et al. Cancer Science, 99(3), 595‐600 2008•Rosell, R, et al N Engl J Med;361:958‐67 2009

Real‐time PCR machine

~3 hours

Cycleave ~ 1% 90‐95% •Yatabe Y, et al. J Mol Diagn; 8: 335‐341 2006•http://www.takarabioeurope.com/cpt.html

Real‐time PCR machine

~1 day

Invader ~ 1% 90‐95% •Hall JG et al. Proc Natl Acad Sci U S A; 97: 8272‐8277 2000•Naoki K, et al. Int J Clin Oncol 2011 (preview)

PCR machine, Fluorescent reader

~1 day

Pyrosequencing 5‐10% 90‐95% •Takano, T et al. Journal of Clinical Oncology. 23(28):6829‐37, 2005 •Dufort, S, et al. Journal of Experimental & Clinical Cancer Research, 30:57 2011

Pyrosequencer 1 day

Issues with allele specific RT‐PCR

• Cobas seemed to

suggest an exon

19 Deletion in

sample

• Patient did not

respond as hoped

to first line TKI

• Sanger ‐Due to a

cluster of 6 SNPs

at the deletion

start point which

may have led to a

false positive

signal PCR

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Uncertain and/or false negative direct sequences benefit from verification by a more sensitive platform

Exon 20 insertion/deletion mutations are typically not sensitive to erlotinib, gefitinib, and afatinib

Chromosomal re‐arrangements of ALK are present in3% to 7% of NSCLC

• The resulting ALK

fusions, such as

EML4‐ALK, function

as potent

oncogenic drivers

and lead to a state

of oncogene

addiction

22

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ALK Fluorescence In Situ Hybridization

2p23ALK Dual Color, Break Apart FISH assay, Abbott Molecular

normal3’ 5’

Rearrangement positive ‐ split Rearrangement positive ‐ single 3’ ALK

Inversion with EML4‐ALK fusion

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ALK IHC for screening:Alectinibphase I/II study in JapanAF‐001JP

In contrast to the

earlier studies which

used ALK fluorescence

in situ hybridization

(FISH) only, patients

were identified as

ALK‐positive using ALK

immunohistochemistr

y (IHC), followed by

ALK FISH for

confirmation.

Paik et al, JTO 2011

Novocastra clone 5A4

Yi et al, JTO 2011

DAKO clone ALK1

Mino‐Kenudson et al., CCR 2010

Cell Signaling clone D5F3

An International Interpretation Study Using the ALK IHC Antibody D5F3 and a Sensitive Detection Kit Demonstrates High Concordance between ALK IHC and ALK FISH and between EvaluatorsWynes, Murry W. PhD*; Sholl, Lynette M. MD†; Dietel, Manfred MD‡; Schuuring, Ed PhD§; Tsao, Ming S. MD, FRCPC‖; Yatabe, Yasushi ME, PhD¶; Tubbs, Raymond R. DO#; Hirsch, Fred R. MD, PhD***††

Overall for the 100 evaluable cases the ALK IHC assay was highly sensitive (90%), specific (95%), and accurate relative (93%) to the ALK FISH results. Similar results were observed using a majority score.Journal of Thoracic Oncology:May 2014 - Volume 9 - Issue 5 - p 631–638

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48 yomale patient• 3.2 x 4.4 cm

spiculated mass in the R lower lobe of the lung

• Liver metastases

• Large necrotic lymph nodes in the right retrocrural, upper abdominal (pericoeliac, retrocaval and portocaval, paracaval), retroperitoneal and also mesenteric lymph nodes are seen, surrounding the portal confluence, celiac axis and left renal vein, and indenting the IVC.

G1202R mutation has been reported to confer resistance to alectinib

Alectinib

reportedly

efficacious in 4

crizotinib‐

resistant ALK

mutations

L1196M, F1174L,

R1275Q and

C1156Y

25

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Brigatinib has reduced susceptibility to ALK mutations compared with other first- and/or second-generation ALK TKIs in vitro.

Sen Zhang et al. Clin Cancer Res 2016;22:5527-5538

©2016 by American Association for Cancer Research

The Future – For a Single Patient…

We will test for many members of a molecular pathway

We will test for biomarkers associated with different drugs, to be given at different time points

This will require a different molecular diagnostic approach

TUMOR

TUMORRESISTANCE 1

TUMORRESISTANCE 2

(…) (…)

Drug 1

Drug 2

Drug 3

26

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Routine Single‐Marker Molecular TestThe Most Common Type of Molecular Testing

CATEGORY ONE

CATEGORY TWO

CATEGORY THREE

Routine single marker molecular tests such as IHC, PCR and FISH that have been used for decades and will continue to play an important role in cancer diagnosis

missedmissed

foundmissed

missed

FISH: fluorescence in situ hybridization; IHC: Immunohistochemistry; PCR: Polymerase chain reaction

Multi‐Gene “Hot Spot” TestBroader Testing Focused On a Narrow Subset Of Genes

CATEGORY ONE

CATEGORY TWO

CATEGORY THREE

The hot spot NGS panels identify pre‐specified mutations occurring in very limited areas of genes of interest and fail to detect all classes of genomic alterations

missed foundmissed

missedfound

27

Notes:

Notes:

Hybrid CaptureNGS‐Based, Comprehensive Genomic ProfilingThe Most Comprehensive Genomic Test Available

CATEGORY ONE

CATEGORY TWO

CATEGORY THREE

Hybrid capture NGS‐based comprehensivegenomic profiling approach of testing all of the known clinically relevant cancer genes for all classes of alterations

foundfound

foundfound

found

Hybrid Capture NGS‐Based, Comprehensive Genomic Profiling

Hybrid CaptureNGS‐Based, Comprehensive Genomic Profiling DeliveringActionable Insights From the First Page

Patient and ordering physician information

Targeted therapies and clinical trials that may be relevant based on genomic alterations

identified

Summary of results and genomic alterations

identified

28

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29

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High performance was achieved for both high‐level amplifications (copy number ≥ 8) and homozygous deletions when tumor purity was as low as 30%: sensitivity was 99% (91/92) with PPV > 99% (127/127).

Performance was reduced for lower CNAs (6–7 copies) and at lower sample purities (20–30%), with overall sensitivity >80%.

Our results demonstrate that an optimized NGS‐based test can accurately detect most clinically actionable CNAs in a broad spectrum of patient specimens.

These results also highlight the

scope for further improvements in this methodology, including the robust detection of heterozygous loss.

Copy Number Alterations (CNAs)‐ Foundation

30

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Durable Response to Crizotinib in a Patient withMET‐Amplified Carcinoma of Unknown Primary

59‐year‐old female

60‐pack‐year smoking history

New‐onset seizures

MRI identified 2 distinct masses; right frontal lobe of brain and left mid‐abdominalmass

Real‐time PCR demonstrated KRASmutation, FISH analysis negative for ALK rearrangement

Palma, N.A., et al (2014) Durable Response to Crizotinib in a MET-Amplified, KRAS-Mutated Carcinoma of Unknown Primary. Case Rep Oncol 7(2):503–8.

Patient Profile

Durable Response to Crizotinib in a Patient withMET‐Amplified Carcinoma of Unknown Primary

Adenocarcinoma of unknown primary with brain metastases

Disease progression after 4 cycles of carboplatin and docetaxel

FISH: Fluorescence in situ hybridization; MRI: Magnetic resonance imaging; PCR: Polymerase chain reaction


Diagnosis

Treatment Status

31

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Normalization of TumorMetabolic Activity Following MET Targeting with Crizotinib

Identification of genomic alterations in MET, CCND1, MYC, KRAS, TP53 and CARD11

Treatment with crizotinib was initiated

18F-FDG PET/CT: 18F-fluorodeoxyglucose positron emission tomography

Genomic position

Genomic profiling by NGS of resected brain specimenMET amplification

Lo

g2(

test

/ref

)

2.0

1.5

1.0

1 2

0.5

0.0

-0.5

-1.0

-1.5

3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 x

Co

py n

um

ber

0

2

4

6

8

10

12

14

16


Genomic Profiling and Subsequent Treatment

Normalization of TumorMetabolic Activity Following MET Targeting with Crizotinib

Complete normalization of tumor metabolic activity for > 19 months of crizotinib treatment

18F-FDG PET/CT: 18F-fluorodeoxyglucose positron emission tomography

18F‐FDG PET/CT fusion of the transaxial left mid‐abdominal mesenteric mass 1 month prior (*) and 3 months (**) after starting crizotinib

***

NGS comprehensive genomic profiling identified a MET amplification. The patient exhibited a sustained response to subsequent treatment

with a multi‐kinase inhibitor that targets MET, ROS1 and ALK


32

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Notes:

ActivatingInvasion&

metastasisiInducing

angiogenesis

GenimeInstability&mutation

Resistingcell

death

Deregulatingcelluar

energetice

SustainingProliferative

signaling

Evadinggrowth

suppressors

EnablingReplicativeimmortality

Tumor‐Promoting

inflammation

AvoidingImmune

destruction

Immune Checkpoint Therapy

Hallmarks of Cancer

Signaling Pathways and Intervention of Immune Checkpoints in Tumor Microenvironment

Source: thasso.com, accessed in August 2016Pardoll DM, Nature Reviews Cancer 12, 252-264 (April 2012)

Molecule Company Target

Ipilimumab BMS CTLA4

Tremelimumab AstraZeneca CTLA4

Nivolumab BMS PD‐1

Pembrolizumab Merck PD‐1

Atezolizumab Roche PD‐L1

Durvalumab AstraZeneca PD‐L1

Avelumab Merck/Pifzer PD‐L1

33

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MSI Status as Prognostic Indicator That Correlates to Higher TMB

• MSI is a condition of genetic hypermutability that is caused by a deficiency in DNA mismatch repair (MMR) in the tumor

• MSI is associated with better prognosis in multiple cancer types1‐3

Cancer Genome Atlas Network, Nature. 2012 Jul 18;487(7407):330-7.

1. Arzimanoglou II et al., Cancer. 15;82(10):1808-20 (1998)2. Zhu L et al., Mol. Clin. Oncol. 3, 699-705 (2015)3. Guastadisegni C et al., Eur. J. Cancer 46(15), 2788-2798 (2010)

Tumor Mutational Burden (TMB) and MSI are Biomarkers for Response to PD‐1/PD‐L1 Checkpoint Blockade

Le et al., NEJM, 2015

Snyder et al., NEJM, 2014

High TMB in Melanoma MSI‐High in Colorectal Cancer

34

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Notes:

TMB Measured for 315 CGP Test Genes Versus Whole Exome – TCGA Data

R²=0.9763

0

100

200

300

400

500

0 5,000 10,000 15,000

Mutationcount–

targetedtest

Mutationcount– wholeexome

1

10

100

1 10 100 1,000 10,000

Mutationcount–

targetedtest

Mutationcount– wholeexome

35 TCGA studies7,000 specimens

Cancer Res 2016;76(14 Suppl):Abstract nr 2629

Association of TMB With AtezolizumabEfficacy in 2L+ PD‐L1–Selected Patients From BIRCH and FIR

Kowanetz, M. et al. in Annual ESMO congress (Copenhagen, Denmark 2016). Poster #77P

35

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Next‐Generation Sequencing Approaches to Understanding the Genetic Basis of Cancers

for Personalized Medicine

Maria Li Lung, PhD

Department of Clinical Oncology, University of Hong Kong

Center for Nasopharyngeal Carcinoma Research

OncoSeek Limited, Hong Kong Science Park

Singapore Scientific Exchange Meeting on Cancer Genetics

December 15, 2016


Non‐paid consultant for OncoSeek working on CTCs

36

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Notes:

EGFR

KRAS

Unknown


Unknown


KRAS

NRAS

ROS1 Fusions

RET Fusions

EGFR

ALK Fusions

HER2BRAF

PIK3CA AKT1MAP2K1


Today, there are many known genomic alterations that can drive

the development of cancer...

2004 2015

Modified and updated from Pao and Hutchinson (2012) Chipping away at the lung cancer genome. Nature Medicine 18(3):349‐51.

A decade ago, genomic alterations were important in only around

1/3 of NSCLC cases

NSCLC: Non‐small cell lung cancer



Trastuzumab, Afatinib

Vemurafenib, Dabrafenib

Crizotinib, Ceritinib

Erlotinib, Afatinib

Cabozantinib

Trametinib

2015

Modified and updated from Pao and Hutchinson (2012) Chipping away at the lung cancer genome. Nature Medicine 18(3):349-51.

Crizotinib

Crizotinib

…and many new targeted therapy options to treat patients harboring these genomic alterations

Unknown


KRAS

NRAS

ROS1 Fusions

RET Fusions

EGFR

ALK Fusions

HER2BRAF

PIK3CA AKT1

MAP2K1

37

Notes:

Notes:

Applications of NGS

Critical Reviews in Oncology/Hematology 96 (2015) 463–474

NGS Description Advantages Disadvantages

Genomesequencing

Determines the sequence of most of the DNA from the individual’s genome

• Provides information on non‐coding regions and structural variants as well as coding regions

• Expensive and time consuming

• Data can be more difficult to interpret

• Challenges of what to do about incidental findings

Exome sequencing

Ex: germline CPGs somatic tumor mutations

Determines the sequence of the protein –coding DNA regions(exons)

• Faster and cheaper than genome sequencing • The majority of known pathological abnormalities occur in the exome

• Functional consequences of variants are more easily understood

• Misses variations in non‐coding regions and some structural variants

• Challenges of what to do about incidental findings

Targeted panels

Ex: NGS of CTCs

Determines the sequence ofspecific genes or parts of genes

• Usually cheaper than exome or genome sequencing, but this depends on the size of the gene panel

• Focused on particular regions of interest and so data interpretation is easier

• No concern regarding incidental findings as only the regions of interest are sequenced

• Can optimize the panel to capture problematic regions that are difficult to sequence using exomeor genome approaches

• Does not provide information on regionsoutside of the gene panel

Nasopharyngeal Carcinoma (NPC)

Cancer associated with genetic, dietary/environmental factors, and EBV infection

Common cancer in SE Asia, nicknamed the “Guangdong cancer”

Salted fish

Located in center of head with lymphatic spread

38

Notes:

Notes:

NPC differs from many other cancers, since patients are relatively young at diagnosis and may survive many years after treatment. QoL

issues important!Sources from: Chien & Chen, 2003 and Hong Kong Cancer Registry, 2009

Relative Frequency of Five Most Common Cancers in Males by Age Group in 2012

% ofAges 20‐44 #/yr all cancersNasopharynx 130 17 Colorectum 84 11Liver 69 9Lung 58 7.6Testis 50 6.5

% of Ages 45‐64 #/yr all cancersLung 894 17.9Colorectum 880 17.6Liver 654 13.1Nasopharynx 370 7.4Prostate 323 6.5

Tumor Development

Year 0 Year 5

Inherited Risk

DysplasiaCa in situ

Invasion Angiogenesis

Detection Threshold

Onset of metastasis

Diagnosis period

Treatment period

Invasion prevention/ intervention window

Time

Tu

mor

Siz

e

Normal Hyperplasia Carcinoma in situ

Invasion angiogenesis Metastasis

Copyright / illustrated by Panda

39

Notes:

Notes:

NPC Genetic Predisposition?

Age

Peak age: 45‐55 years

Early‐age onset cases: diagnosed with NPC at ≤ 20 years

Family clustering

5‐10% of NPC patients have a history of one or more affected family members

RR 12.8 for individuals with family history of NPC, compared to general population in endemic regions

Migrant studies

Offspring of migrants from endemic regions often show increased risk of NPC in low‐risk regions

Source: World Cancer Report 2008Zeng, Y. X., & Jia, W. H. (2002). Familial nasopharyngeal carcinoma. Sem Cancer BiolNg WT et al. (2005). Screening for family members of patients with nasopharyngeal carcinoma. IJC

Genetic Susceptibility

Family history

positive NPC

Early age onset NPC

FH+67 individuals from 56 families; 9 families with more than one affected individual sequenced, Southern Chinese

EAO39 NPC patients who have been diagnosed with NPC at or younger than 20, Southern Chinese4 cases have FH+ NPC

NPC Genetic Susceptibility

Sporadic NPC

Non‐cancer controls

Sporadic59 NPC patients who do not have family history

of NPC, Southern Chinese

Control cohorts895 Southern Chinese mainly from HK

Exome sequencing was performed using Illumina HiSeq (TruSeq capture)

Study Cohorts in Discovery Stage

Hypothesis: Important genes associated with NPC genetic susceptibility may be uncovered in EAO cases and FH+ cases because NPC occurs earlier in such patients compared to sporadic cases

40

Notes:

Notes:

Top CPG: Macrophage‐Stimulating 1 Receptor (MST1R)

• MST1R = RON. Maps to chr 3p21.3. Encodes a cell surface receptor with tyrosine kinase activity (Ronsin et al. Oncogene, 1993)

• Expressed in the tissue‐resident macrophages and functions to maintain inflammation homeostasis (Correll et al. J Leukoc Biol, 2004)

• Ligand: Macrophage‐Stimulating Receptor (MSP), encoded by MST1, also located in chromosome 3p21.3 (Wang et al. Science, 1994)

• SEMA domain harbors ligand‐binding pocket for MSP

• Two transcripts of MST1R initiated by 2 promoters, 2 CpG islands suggested to be molecular switch for expression of two transcripts, short isoform associated with aggressive tumor

• The MSP‐MST1R signaling has been implicated in several tumorigenic processes including cell proliferation, survival, migration, invasion, and angiogenesis (Yao et al. Nat Rev Cancer, 2013)

• Expressed in the ciliated epithelial cells in the nasal cavity. Activation of MST1R increases ciliary beat frequency, which moves the fluid over the surface of the epithelial cells and prevents chronic infection in the nasal cavity (Sakamoto et al. J Clin Invest ,1997)

MST1RDeleterious Variants in NPC

In total, we identified 11 rare deleterious variants (10 missense and 1 frameshift deletion) in NPC cases, accounting for 17.8% EAO cases, 7.1% FH+ cases and 5.1% sporadic cases

Dai et al, PNAS 113: 3317‐22, 2016

41

Notes:

Notes:

Somatic Landscape StudiesDiscovery WES specimens: 51 primary, 8 recurrent, 3 LN tumors

Validation targeted gene sequencing specimens: 73 primary tumors

Lymph node

metastaticSource: Cancer Research UK

T1 T2 T3 T4

Identify driver genes/pathways

Whole exome sequencing

Targeted resequencing

DNA methylome profiling

Transcriptome profiling

Prognosis and diagnosis

Patient stratification

New therapy

Landscape of genetic and epigenetic alterations

Explore new therapeutic targets

Chip‐seq analysis

Molecular basis of tumorigenesis

Mutation Landscape

Zheng et al, PNAS 2016

42

Notes:

Notes:

TP53Mutations in NPC

TP53 is the most frequently mutated gene in our cohort (9/124, 7.3%), as well as in the Singapore WES study (10/117, 8.5%, only consider somatic SNPs and INDELs)

Almost all somatic mutations fall into the DNA binding domain of TP53

Immunohistochemistry staining of p53 in three tumor samples with TP53missense mutations

missensestopgainsplicingframeshift INDELnonframeshift INDEL


Mutations of NF‐κBRegulators

Verification of NFKBIA somatic INDELs

missensestopgainsplicingframeshift INDELnonframeshift INDEL


43

Notes:

Notes:

Primary Tumor Cancer SpreadingCirculation

Circulating tumor cells “seeds” for cancer spread

What are Circulating Tumor cells and Why are CTCs So Important?

Alix‐Panabieres, C. and Pantel, K. Cancer Discov., 2016

Clinical Application of CTCs and ctDNAas Liquid Biopsies

44

Notes:

Notes:

Challenge for Isolation and Identification of CTCs in Blood

Just like finding you amongst 7.4 billion people!

Software analysis

Immunostaining‐CTC (e.g. CK)‐WBC (e.g. CD45)‐DNA stain

CTC Test Details

Image capture

Enrichment1

2

34

5 Reporting

45

Notes:

Notes:

CTC levels in several human cancers

NPC 42 (15QE5026)

Merged

20 µm

CK+ CD45‐DAPI

Representative CTC images

New diagnosisStaging and

baseline blood test

2‐3 weeks

Cycle I Chemo

Blood test

Cycle II Chemo

Blood test

Cycle III Chemo

Blood test

3 weeks 3weeks 3weeks

Cycle V Chemo

Blood test

Cycle IV Chemo

Blood test

3 weeks

Cycle VI Chemo

Blood test

3weeks

CTC1 at diagnosis: Baseline

CTC2 after week 6: early predictive biomarkers for

chemoRT response

CTC3 after week 9: Correlate with chemo interim

response

CTC4 at end of CT: Biomarker for Chemo final responseBoth to be done at Week 18 ‐ 20

Four Serial Time‐Point Schedule for CTC Analysis of Metastatic Stage IVC NPC

1PET

7 10

2PET

13

3PET

160

Palliative 1st line chemotherapyMedian survival ~ 11 monthsCommon chemotherapy regimens include:cisplatin/5FU, gemcitabine/cisplatin (or carboplatin) [capecitabine]

First line of treatment

46

Notes:

Notes:

CR: No significant soft tissue or uptake in nasopharynx, and remained same on all scans.

PET1 PET2 PET3 PET1 PET2 PET1 PET2

Similar size and metabolic activity with no new lesions

Reduction in size and metabolic activity of

indexed lesions

47

Notes:

Notes:

Why is Comprehensive Genomic Profiling So Important?

0

5

10

15

20

25

30

35%

of

pat

ien

tsPatients eligible for trastuzumab: using current standard testing

= rearrangements

= base substitutions

= insertions/deletions

= amplifications

ERBB2mutations

Data source: Foundation Medicine database

0

5

10

15

20

25

30

35

% o

f p

atie

nts

Patients eligible for trastuzumab: using a test for all solid tumor types

= rearrangements



= amplifications

ERBB2mutations


Why is Comprehensive Genomic Profiling So Important?

48

Notes:

Notes:

Comprehensive Genomic Profiling Can Identify Mutations that Would Have Been Missed by Standard Tests

0

5

10

15

20

25

30

35%

of

pat

ien

tsPatients eligible for trastuzumab: using a comprehensive profiling test

= rearrangements



= amplifications

ERBB2mutations


pre

NGS Study: Target Capture of 1373 Genes

Adapted from http://www.nimblegen.com/products/seqcap/ez/choice/index.html

49

Notes:

Notes:

Spike‐in DNA from Cancer Cell Line to Normal Individual for Evaluation of NGS Study by Target Capture

Only the protein‐altered somatic mutations were examined. We identified 102 protein‐altered mutations in KYSE270.

Sample summary

RC2202: blood sample from Red Cross

KYSE270: cell line KYSE270

10: RC2202 with 10% KYSE270

5: RC2202 with 5% KYSE270

2.5: RC2202 with 2.5% KYSE270

1.25: RC2202 with 1.25% KYSE270

Example: all three TP53 mutations can be identified in 10% and 5% spiked‐in

samples, but not in 2.5% and 1.25% samples.

Bioinformatics analysis done by Wei Dai

High specificity of protein‐altered somatic mutations with low false discovery rate.

0

500

1000

1500

2000

2500

KYSE270 10 5 2.5 1.25

TotalM

utations Compare to

RC2202

Compare to RC2202 KYSE270 KYSE270

(10%)

KYSE270

(5%)

KYSE270

(2.5%)

KYSE270

(1.25%)

Sensitivity reference 0.6078 0.2843 0.0686 0.0490

False discovery rate (FDR) reference 0.0606 0.0938 0.4615 0.5455

Positive prediction value

(PPV)reference 0.9394 0.9063 0.5385 0.4545

Preliminary data:

In ESCC13T, we identified 142 protein‐alteredmutations including 129 missense, 5 frameshiftinsertions, 4 splicing, 3 stopgain and 1 non‐frameshift deletion.

Identification of Somatic Mutations in ESCC CTC Sample

50

Notes:

Notes:

Acknowledgements

• Basic AoE lab team: J Ko, W Dai, H Zheng, A Cheung, B Wong

• Center for NPC Research Tissue Bank• AoE Clinical team: R Ngan, WT Ng, D Kwong, V Lee, KO Lam, CC Yau, S Tung

• AoE Imaging team: PL Khong, V Vardhanabhuti

• PRC collaborators: MF Ji (Zhongshan), J Pan (Fujian), X Peng (Shantou), ZF Zhang (Guangxi)

• OncoSeek: S Lam, V Wong

• AoE grant support from the Research Grants Council

• HK Health and Medical Bureau: HMRF grant

• HK Cancer Fund• OncoSeek, Ltd

CHALLENGES and QUESTIONS

Interactive Dialogue Session with Faculty‐ Facilitated Analysis and Discussion Focused on NGS Technologies

for Genomics‐Driven Cancer Medicine

51

Notes:

Notes:

Based on the growing number and combination of genomic alterations that are potentially actionable across a broad spectrum of tumor subtypes, hybrid capture NGS comprehensive genomic profiling should be used routinely, in preference of other strategies, as the primary methodology for precision‐focused tumor assessment and targeted treatment:

1) Strongly agree

2) Agree

3) Moderately agree

4) Agree somewhat

5) Disagree



Challenges and Questions

Based on my experience, laboratories that provide hybrid capture NGS comprehensive genomic profiling for cancer produce results of similar quality, i.e. they provide the same spectrum and level of coverage for genomic alterations, they have the same false‐negativity and false positivity rates, and they use technologies that are equally validated with respect to their value in aligning molecular targets with targeted therapy and resulting clinical outcomes:

1) Agree

2) Tend to agree

3) Disagree

4) Tend to disagree




52

Notes:

Notes:

James Chih-Hsin Yang M.D., Ph.D.

楊志新教授Professor and Director, Graduate Institute of Oncology, NTU

台灣大學醫學院腫瘤醫學研究所所長Director, Department of Oncology, National Taiwan University Hospital

台大醫院腫瘤醫學部主任

Treatment of Advanced NSCLC Based onGenomic Analysis of the Tumor

James Chih‐Hsin Yang received honorarium for speech or participated in compensated advisory board of Boehringer Ingelheim, Eli Lilly, Bayer, Roche/Genentech/Chugai, Astellas, MSD, Merck Serono, Pfizer, Novartis, Clovis Oncology, Celgene, Merrimack, Yuhan Pharmaceuticals, BMS, Ono Pharmaceutical, Daiichi Sankyo and AstraZeneca


53

Notes:

Notes:

Advanced NSCLC Treatment Evolutions

Chemotherapy 1995 (mOS 6-12 months)

Platinum

Vinorelbine

Paclitaxel

Gemcitabine

Docetaxel

Irinotecan

S1

Pemetrexed

Targeted therapy 2002 (mOS 2-4 years)

Gefitinib #

Erlotinib #

Bevacizumab

Crizotinib #

Afatinib #

Ceritinib #

Alectinib #

Osimertinib #

Necitumumab

Ramucirumab

Nintendanib

Immunotherapy 2015

Nivolumab

Pembrolizumab

Histology Molecular driver profile Microenvironment

Red: only in non SCC# : driver mutation presencemOS: median overall survival

IDEAL: Objective Tumour Response Rates

Dose evaluation study for gefitinib in chemotherapy treated NSCLCNSCLC: Chemotherapy failure, no biomarker selection

Fukuoka M et al. JCO 2003

54

Notes:

Notes:

18

19

21

20

C-helix

P-loop

A-loop

Deletions 46%

L858R (39%)

Duplications/insertions (9%)N-lobe

C-lobe

Transmembraneregion

Extracellular domain

Regulatorydomain

ATP binding cleft

TKdomain

Distribution of Mutations in the TK domain of EGFR: Meta‐Analysis of Five Studies (n=1256)

Gefitinib Carboplatin / paclitaxel

EGFR M+ odds ratio (95% CI) = 2.75(1.65, 4.60), p=0.0001

EGFR M- odds ratio (95% CI) = 0.04(0.01, 0.27), p=0.0013

Overallresponserate (%)

(n=132) (n=129) (n=91) (n=85)

Odds ratio >1 implies greater chance of response on gefitinib

71.2%

47.3%

1.1%

23.5%

Iressa Pan‐Asia Survival Study (IPASS): Analysis based on EGFR mutations

55

Notes:

Notes:

PFS in EGFRMutation‐Positive and Wild‐Type Patients (IPASS)

EGFR mutation-positive EGFR wild-type

Probab

ility of PFS

1.0

0.8

0.6

0.4

0.2

0

Probab

ility of PFS

1.0

0.8

0.6

0.4

0.2

00 4 8 12 16 20 24 0 4 8 12 16 20 24

Months Months

132 108 71 31 11 3 0129 103 37 7 2 1 0

At risk:GefitinibC/P

91 21 4 2 1 0 085 58 14 1 0 0 0

Gefitinib (n=132)Carboplatin/paclitaxel (n=129)

HR (95% CI) = 0.48 (0.36, 0.64)p<0.0001

Gefitinib (n=91)Carboplatin/paclitaxel (n=85)

HR (95% CI) = 2.85 (2.05, 3.98)p<0.0001

Mok et. al. NEJM 2009

Treatment by subgroup interaction test p<0.0001

First‐line EGFR‐TKIs in EGFRMutation‐Positive: Summary

EGFR‐TKIMedian PFS

EGFR‐TKI vs Chemotherapy

IPASS[a] Gefitinib 9.6 vs 6.3 months (HR=0.48)

NEJ002[b] Gefitinib 10.8 vs 5.4 months (HR=0.30)

WJTOG3405[c] Gefitinib 9.2 vs 6.3 months (HR=0.49)

First‐SIGNAL[d] Gefitinib 8.4 vs 6.7 months (HR=0.61)

EURTAC[e] Erlotinib 9.7 vs 5.2 months (HR=0.37)

OPTIMAL[f] Erlotinib 13.1 vs 4.6 months (HR=0.16)

ENSURE[g] Erlotinib 11.0 vs 5.5 months (HR=0.33)

LUX‐Lung 3[h] Afatinib 11.1 vs 6.9 months (HR=0.58)

LUX‐Lung 6[i] Afatinib 11.0 vs 5.6 months (HR=0.28)

a. Mok T, et al. N Engl J Med. 2009;361:947‐957. b. Maemondo M, et al. N Engl J Med. 2010;362(25):2380‐2388.c. Mitsudomi T, et al. Lancet Oncol. 2010;11(2):121–128. d. Han JY, et al. J Clin Oncol. 2012;30(10):1122‐1128.e. Rosell R, et al. Lancet Oncol. 2012;13:239‐246. f. Zhou C, et al. Lancet Oncol. 2011;12:735‐742.g. Wu YL, et al. ELCC 2014. Oral Presentation 91O. h. Sequist LV, et al. J Clin Oncol. 2013;31(27):3327‐3334.i. Wu YL, et al. Lancet Oncol. 2014;15(2):213‐222.

56

Notes:

Notes:

Evidence to treat EGFRm+ NSCLC

with 1st line EGFR TKI (Gefitinib, Erlotinib, Afatinib )

compared to standard pt‐doublet

1. Higher PFS 2. Higher RR

3. Better HRQoL

Resistance Mechanisms in EGFR Mutant NSCLC

EGFR T790M

MET

Amplification

HGF

Production

57

Notes:

Notes:

AURA Study: Osimertinib (AZD9291) EGFR Mutant Specific Inhibitor

EscalationNot preselected by T790M status

ExpansionEnrollment by local testing

followed by central laboratory confirmation* of T790M status or by

central laboratory testing alone

*cobas® EGFR Mutation Test (Roche Molecular Systems)

Phase I, open‐label, multicenter study of AZD9291 administered once daily in Asian and Western patients with advanced NSCLC who have documented radiological progression while on prior

therapy with an EGFR‐TKI (AURA; NCT01802632)

Objectives

Primary: safety, tolerability and efficacy (objective response rate)

Secondary include: define maximum tolerated dose, pharmacokinetics

Extension

Jänne PA et al. ELCC 2015; abstract LBA3

Tumour Response to Osimertinib Treatment

AURA Ph I data cut-off 4 January 2016; population: evaluable for response set; assessment: investigator assessed; AURA pooled Ph II data cut-off 1 November 2015; population: evaluable for response set; assessment: BICR.*Represents imputed values: if it is known that the patient has died, has new lesions or progression of non-target lesions, has withdrawn due to disease progression, and has no evaluable target lesion (before or at progression) assessments, best change will be imputed as 20%; †Complete response, partial response, stable disease ≥6 weeks.

Tumor Response AURA Ph I (80 mg) n=61

AURA pooled Ph II (80 mg) n=397

Confirmed ORR 71% (95% CI: 57, 82) 66% (95% CI: 61, 71)

Disease control rate† 93% (95% CI: 84, 98) 91% (95% CI: 88, 94)

Best objective response Complete responsePartial responseStable disease ≥6 weeksProgressive disease

142142

62569925

–100

–80

–40

–60

–20

0

20

40

60

80

Complete responsePartial responseStable diseaseProgressive diseaseNot evaluable

Best

per

cent

age

chan

ge fr

om b

asel

ine

in

targ

et le

sion

siz

e (%

)

*********

100

–100

–80

–60

–40

0

20

40

80

–20

100

Best

per

cent

age

chan

ge fr

om b

asel

ine

in

targ

et le

sion

siz

e (%

)

Complete responsePartial responseStable diseaseProgressive diseaseNot evaluable

AURA Ph I AURA pooled Ph II

Proprietary and confidential AstraZeneca document – for internal use only.Yang JCH, et al. ELCC 2016; Abstract LBA2_PR.

58

Notes:

Notes:

Duration of Response With Osimertinib

AURA Ph I

AURA Ph I data cut-off 4 January 2016; population: evaluable for response set; assessment: investigator assessed; AURA pooled Ph II data cut-off 1 November 2015; population: evaluable for response set; assessment: BICR.Tick marks on the Kaplan-Meier plot denote censored observations *Duration of response is the time from first documentation of response until date of progression or death or last evaluable RECIST assessment for patients who do not progress.†Calculated using the Kaplan-Meier technique

Duration of Response AURA Ph I (80 mg) n=43

AURA pooled Ph II (80 mg) n=262

Median DoR*, months (95% CI) 9.6 (7.7, 15.6) 12.5 (11.1, NC)

Maximum DoR, months 26.3 ongoing 15.3 ongoing

Remaining in response†, % (95% CI)12 months18 months24 months

44 (29, 58)32 (19, 46)20 (8, 35)

53 (46, 59)NCNC

0Number of patients at risk:

Osimertinib 80 mg

Prob

abilit

y of

resp

onse

Month

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 3 6 9 12 15 18

43 40 36 22 18 16

21 24 27

11 5 3

Prob

abilit

y of

resp

onse

Number of patients at risk:Osimertinib 80 mg

Month262 240 185 142 69 4 0

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

0 3 6 9 12 15 18 21 24 27

1.0 1.0

0.0

AURA pooled Ph II

Proprietary and confidential AstraZeneca document – for internal use only.

Yang JCH, et al. ELCC 2016; Abstract LBA2_PR.Yang JCH, et al. ELCC 2016; Abstract LBA2_PR.

EML4

EML4–ALK variant 1

HELP1 496 981

WDBasic

1 496 1059

1 1058 1620

TM

KinaseALK

Initially reported in 2007 as a result of an inversion in chromosome 2p, which results in the fusion of the N-terminal portion of the echinoderm microtubule-associated protein-like 4 (EML4) with the kinase domain of ALK

Soda et al., Nature 2007; 448:561-567

Discovery of the EML4‐ALK Fusion in NSCLC

59

Notes:

Notes:

Profile 1014 : Treatment Naïve ALK+ NSCLCCrizotinib Superior to Pemetrexed‐based Chemotherapy in Prolonging PFSa

Mok TS, et al. ASCO 2011

Tyrosine Kinase Inhibitors Activity Against VariousALK or ROS1 Fusion Kinases

60

Notes:

Notes:

Study Design (NCT01945021)

Phase II Study of Crizotinib in East Asian Patients With ROS1‐Positive Advanced Non‐Small Cell Lung Cancer

Goto K. et al. ASCO 2016 abstract 9022

IRR-assessed Best Percent Change <br />from Baseline in Target Lesion Size*

Phase II Study of Crizotinib in East Asian Patients With ROS1‐positive Advanced Non‐Small Cell Lung Cancer

Goto K. et al. ASCO 2016 abstract 9022

61

Notes:

Notes:

Efficacy and Safety of Crizotinib in Patients with Advanced MET‐Amplified NSCLC

Best percent change from baseline in target tumor lesionsa by patient

Camidge DR et al. ASCO 2014 abstract 8001

NSCLCcMET Skipping Exon 14 Mutation

Nele Van Der Steen et al. JTO 2016;11(9):1423-1432

62

Notes:

Notes:

NSCLCcMET Skipping Exon 14 Mutation

Nele Van Der Steen et al. JTO 2016;11(9):1423-1432

Actionable Targets in Lung Adenocarcinomas

Unknown75%

1999

2005-2016

EGFR

2004

Unknown60%

Modified from Kris M et al. IASLC 2012 Targeted Therapies Conference

SelumetinibTrametinib

GefitinibErlotinibAfatinib, DacomitinibOsimertinib, OlmutinibEGF816, ASP8273

Crizotinib, Ceritinib, Alectinib, BrigatinibLorlatinib

NRAS

CrizotinibCeritinib, Lorlatinib

Selumetinib?

Afatinib?Dacomitinib?

INC280MSC2156119jLY2801653Crizotinib

Dabrafenib, VemurafenibRegorafenib, Selumetinib, Trametinib

MK2206?BKM120?

HSP90 client oncoproteinAUY922PD1/PD-L1 expression Pembrolizumab, Nivolumab, Ateolizumab, Durvalumab, Avelumab etc. AntiangiogenesisBevacizumab, NintedanibRamucimumab

63

Notes:

Notes:

Patients with Driver MutationsCurrent Challenges

Detection of driver mutations: NGS

Detection and quantitation of T790M: plasma test

Selection of ALK inhibitors: ALK fusion mutation types

CNS metastasis

Poor performance patients

Selecting patients for combination therapy (bevacizumab, chemotherapy other targeted therapy)

Nivolumab2nd Line

Squamous cell carcinoma CheckMate17Nivolumab vs. Docetaxel 2nd line

Adenocarcinoma CheckMate57Nivolumab vs. Docetaxel 2nd line

64

Notes:

Notes:

Pembrolizumab1st, 2nd and Further Lines

Keynote 001 Keynote 010: pembro vs doc as 2nd line

Key End Points

Primary: PFS (RECIST v1.1 per blinded, independent central review)

Secondary: OS, ORR, safety

Exploratory: DOR

KEYNOTE‐024 Study Design (NCT02142738)

Key Eligibility Criteria

• Untreated stage IV NSCLC

• PD-L1 TPS ≥50%

• ECOG PS 0-1

• No activating EGFR mutation or ALK translocation

• No untreated brain metastases

• No active autoimmune disease requiring systemic therapy

Pembrolizumab 200 mg IV Q3W

(2 years)

R (1:1)N = 305

PDa Pembrolizumab 200 mg Q3W for 2 years

Platinum-Doublet Chemotherapy

(4-6 cycles)

aTo be eligible for crossover, progressive disease (PD) had to be confirmed by blinded, independent central radiology review and all safety criteria had to be met.

Reck M. et al. NEJM 2016:375(19);1823‐1833

65

Notes:

Notes:

Progression‐Free Survival

Assessed per RECIST v1.1 by blinded, independent central review.Data cut-off: May 9, 2016.

Events, n

Median, mo

HR (95% CI)

P

Pembro 73 10.3 0.50 (0.37-0.68)

<0.001Chemo 116 6.0

62%50%

0 3 6 9 12 15 180

10

2030

4050

6070

80

90

100

Time, months

PF

S,%

No. at risk

154 104 89 44 22 3 1151 99 70 18 9 1 0

48%15%

Reck M. et al. NEJM 2016:375(19);1823‐1833

Overall Survival

Data cut-off: May 9, 2016.

80%72%

0 3 6 9 12 15 18 210

10

20

30

40

50

6070

8090

100

Time, months

OS

,%

No. at risk

154 136 121 82 39 11 0151 123 106 64 34 7 0

21

70%54%

Events, n

Median, mo

HR (95% CI)

P

Pembro 44 NR 0.60 (0.41-0.89)

0.005Chemo 64 NR

DMC recommended stopping the trial because of superior efficacy observed with pembrolizumab

Reck M. et al. NEJM 2016:375(19);1823‐1833

66

Notes:

Notes:

Distribution of TMB Across All LC Cases

Comparison of Time on Anti‐PD‐1/PD‐L1 Therapy vs. TMB

Spigel DR et al. ASCO 2016

67

Notes:

Notes:

Comparison of Time on Anti‐PD‐1/PD‐L1 Therapy vs. TMB


Slide 6


68

Notes:

Notes:

2016 Oct UpdatedTreatment Paradigm

Squamous cell carcinoma(non‐adenocarcinoma)

Adenocarcinoma(Non‐SCC)

Small cell Lung cancer

platinum + gem/taxane/vnr

+necitumumab

nivolumab, atezolizumabor pembrolizumab(PDL1+)

docetaxelafatiniberlotinib? +ramucimumab

or Nintedanib(fast PD)

Molecular diagnosisDriver mut‐Or no TT* Driver mut+

platinum + pemor paclitaxel/car/bev

pem maintenance

nivolumab, atezolizumabor pembrolizumab(PDL1+)

EGFR mut

* K‐ras, N‐ras, HER2, EGFRexon20 ins, etc.

other not used agents or clinical trials

afatinib, erlotinib,gefitinib +bevacizumab

platinum + pem+/maintor paclitaxel/car/bev

ALK fusion

Other drivers#

#cMET exon14 skip, RET fusion, ROS1 fusion, TRK fusion etc.

crizotinib, alectinib

T790M+

osimertinib

T790M‐

Docetaxel +ramucimumabor Nintedanib(fast PD)

ceritinibalectinib

Corresponding targeted therapy, chemotherapy, immunotherapy

T790M‐

Pembrolizumab

PD L1>50%?

The Clinical Implications of Using Hybrid Capturing NGS in Lung Cancer

The Journey from Genomic Alterations to Optimizing Targeted Therapy at the Front Line of Oncology Practice

Professor Nir Peled, MD, PhD ‐ Program ChairHead, Thoracic Cancer Unit and Center for Precision Medicine

Davidoff Cancer CenterTel Aviv UniversityTel Aviv, Israel

69

Notes:

Notes:

NSCLC ‐ Survival Curves

Schiller et al. NEJM; 2002

Kris, M; 2014

Only ~ 20% of NSCLC Have A Driver Mutation

Most Patients Still Have Poor Outcome

Broadcasting News

1st-line combination

2nd line

Maintenance treatment

1st-line or unspecified setting single agent

1970 1980 1990 2000

Erlotinib2004

Docetaxel1999

Gefitinib†

2003

2010

Pemetrexed‡

2004

Erlotinib2010

Pemetrexed‡

2009

Crizotinib§2011 (US)/2012 (EU)

Erlotinib**2013Median OS, months

12+

~8–10~6

~2–4

13+

Carboplatin*1989

Gemcitabine1996

Vinorelbine1994

Docetaxel2002

Bevacizumab‡

2006

Pemetrexed‡

2008

Paclitaxel1998

Nab‐Paclitaxel2012

Cisplatin*1978

FDA Approval Dates for NSCLC

*Not approved in NSCLC, but commonly used; †Restricted to patients participating in a clinical trial or continuing to benefit from treatment already initiated; ‡Non‐squamous NSCLC only; §ALK‐positive NSCLC only; **EGFR exon 19 deletions or exon 21 (L858R) substitution mutations only; #Afatinib is approved for the treatment of patients with activating EGFRmutations but only PFS data have been published (May 2014).

U.S. Food and Drug Administration. Available at www.fda.gov. Accessed September 2014; European Medicines Agency. Available at http://www.ema.europa.eu. Accessed September 2014; NCCN Guidelines. Non‐small cell lung cancer. v3.2014.

Afatinib**,#

2013

Nivolumab 2015

Zykadia2014

Pembrolizumab 2015

AZD9291 2015

Alectinib2015

Atezolizumab 2016

70

Notes:

Notes:

Modified from Steven O'Day

Stratification for EGFR, ALK and histology

EGFRMut+EGFRWT

non‐squamous

EGFR TKI1+2 L

Platinum doublet + bevacizumab

ALK+

ALK TKI1+2 L

Crizotinib for

ROS1

Therapy Algorithm NSCLC 2016

EGFRWT squamous

Platinum‐based doublet

PD1 BlockadePD1 Blockade

71

Notes:

Notes:

KEYNOTE‐024: Pembrolizumab vs Platinum‐Based Chemotherapy as First‐Line Therapy for Advanced NSCLC With a PD‐L1 (IHC) ≥50%

Martin Reck, Delvys Rodríguez‐Abreu, Andrew G. Robinson, Rina Hui, Tibor Csőszi, Andrea Fülöp, Maya Gottfried,Nir Peled, Ali Tafreshi, Sinead Cuffe,Mary O’Brien, Suman Rao, Katsuyuki Hotta, Melanie A. Leiby, Gregory M. Lubiniecki, Yue Shentu, Reshma Rangwala, and Julie R. Brahmer, on behalf KEYNOTE‐024

PDL1≥50% in 30% of NSCLC patients

20% (EGFR/ALK) + 30% (PDL1++) = 50%!!

NEJM 2016

2017th Treatment Algorithm in Advanced NSCLC

Non‐squamous cellNon‐squamous cell

Locally Advanced or Metastatic NSCLCLocally Advanced or Metastatic NSCLC

Any histologyAny histology

EGFR PositiveEGFR

PositiveALK/ROS positiveALK/ROS positive

EGFR inhibitor

ALK/ROS inhibitor

Platinum Doublet(Excluding Pemetrexed in Squamous)


Response

PD‐L1 ≥ 50% TPSPD‐L1 ≥ 50% TPSPD‐L1 < 50% TPSPD‐L1 < 50% TPS

TESTING: PD‐L1 EGFR, ALK, histologyTESTING: PD‐L1 EGFR, ALK, histology

PD‐L1 (+)Driver MutationDriver Mutation

Progression Progression

*Maintenance Pemetrexed (NSQ)

PD‐L1 ≥1% TPSPD‐L1 UnknwonPD‐L1 ≥1% TPSPD‐L1 Unknwon

Progression

Pembrolizumab

PD‐L1PD‐L1

PDL1 Therapy

72

Notes:

Notes:

Beyond EGFR, ALK & ROS1 (NCCN)

Journal of Thoracic Oncology 2016 11, 613‐638. DOI: (10.1016/j.jtho.2016.03.012)

73

Notes:

Notes:

What Do We Do Today?

H&E • ADC

EGFR • Negative

ALK • Negative

PDL1

ROS1; CMET; RET

Other Drivers?

What should we add?

Example:Complete Response to Crizotinib in a 63 y/o Woman with a MET Amplification and MET Exon 14 Splice Site Mutation, DetectedVia FMI

74

Notes:

Notes:

Current Main Challenges

Diagnostic challenges:

Sample size & Turn around time

PDL1 IHC implementation

EGFR/ALK/ROS1 performance

CMET/RET/BRAF or Multiplex approach

Therapeutic challenges:

Patient selection

Drug availability & Reimbursement

The POWER to PREDICT

IPASS (EGFR; NEJM 2009) PROFILE 1014 (ALK; NEJM 2014)

KEYNOTE 024 (PDL1; NEJM 2016)

75

Notes:

Notes:

Case Presentation (6/2011)

43‐year‐old never smoker caucasian male

Shortness of breath

Pleural effusion and tamponade

Pleurocentesis with clinical relief

Cytology: Cancerous cells

Most probably – Adenocarcinoma

No further cells are available for analysis

CT/PET – RLL + pleural disease only

Case Presentation Continued

Histology: TTF1(+); p63(‐) Adenocarcinoma

EGFR (cobas®) – Negative

ALK FISH (abbott) – Negative

Cisplatin/Pemetrexed/Bevacizumab X 4 PD

76

Notes:

Notes:

A_Pre A_4 weeks A_4 months

B_Pre B_4 weeks B_4 months

Journal of Thoracic Oncology. 7(9):e14-e16, 2012

Case Continued (February/2013)

Crizotinib 250 mg BID

Mild Ataxia

CT/PET – Normal

Brain MRI

77

Notes:

Notes:

JTO 2013 (8): e112

Crizotinib250 mg X2

Post WBRT

Crizotinib

500 mg X1

78

Notes:

Notes:

Brain Response to Ceritinib

•Diagnosed: June 2011 Aug 2016

•Ceritinib since 4.2014

Peled et al; J Thoracic Oncology 2012

Peled et al; The Oncologist 2015

Peled et al; Journal of Clinical Neuroscience 2016

79

Notes:

Notes:

Nivolumab in Non‐SqNSCLC 2nd Line Checkmate 057

mOS (mos)Nivo 17.7Doc 9.0






≥1% PD-L1 expression level

Time (mos)

100

90

80

70

60

50

40

30

10

0

20

3024211815129630 27

OS

(%)

NivoDoc

HR (95% CI) = 0.58 (0.43, 0.79)


100

90

80

70

60

50

40

30

10

0

20

3024211815129630 27Time (mos)

HR (95% CI) = 0.43 (0.30, 0.62)


100

90

80

70

60

50

40

30

10

0

20

3024211815129630 27Time (mos)

HR (95% CI) = 0.40 (0.27, 0.58)

<1% PD-L1 expression level100

90

80

70

60

50

40

30

10

0

20

3024211815129630 27Time (mos)

OS

(%)

NivoDoc


90

80

70

60

50

40

30

10

0

20

3024211815129630 27Time (mos)


90

80

70

60

50

40

30

10

0

20

3024211815129630 27Time (mos)

HR (95% CI) = 0.87 (0.63, 1.19) HR (95% CI) = 0.96 (0.73, 1.27) HR (95% CI) = 0.96 (0.74, 1.25)

157

"Copyright permission has been obtained for this figure. From The New England Journal of Medicine, Borghaei H, et al., Nivolumab versus Docetaxel in Advanced Nonsquamous Non–Small-Cell Lung Cancer [Epub ahead of print; DOI: 10.1056/NEJMoa1507643]. Copyright © 2015 Massachusetts Medical Society. Reprinted with permission from Massachusetts Medical Society."

POPLAR ‐ OS According to PD‐L1 Expression Level

80

Notes:

Notes:

Subgroups Analysis of Progression Free Survival

Wake Up Call!

An URGENT need for UPFRONT PDL1 staining

EGFR/ALK positives do not benefit from I‐O

Do ROS1 / RET / MET benefit from I‐O ?

Do we catch all patients with a driver mutation?

81

Notes:

Notes:

Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA): a multicentre, open‐label,

proof‐of‐concept, randomised, controlled phase 2 trial

Le Tourneau, C., Delord, JP., Gonçalves, A., et al. (2015) Lancet Oncol 16(13):1324‐34. http://www.ncbi.nlm.nih.gov/pubmed/26342236

40% of Patients Refractory Solid Tumors with ≥ 1 Genomic Alteration Could be Molecularly Targeted

Objective: Compare the PFS of patients with recurrent/ metastatic solid tumors refractory to standard care treated with MP‐directed or physician‐directed therapyMethods: • Open‐label, randomised, controlled phase 2 study (n = 195): experimental group (n = 99), control group (n = 96)

• MP by NGS (AmpliSeq cancer panel on an Ion Torrent/PGM system, Life Technologies, Carlsbad, CA, USA; appendix 2, Cytoscan HD (Affymetrix, Santa Clara, CA, USA); hormone receptors by IHC

• Patients with genomic alterations in hormone receptor, PI3K/AKT/mTOR or RAF/MEK pathways were included

Results: • 293 (40%) patients had at least 1 genomic alteration matching one of 10 available targeted regimens

Le Tourneau, C., et al. (2015). Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA): a multicentre, open‐label, proof‐of‐concept, randomised, controlled phase 2 trial. Lancet Oncol 16(13):1324‐34.

Age (years) 61 (54‐69) 63 (54‐69)

Sex

Female 60 (61%) 69 (72%)

Male 39 (39%) 27 (28%)

Previous lines of treatment 3 (2‐5) 3 (2‐5)

Molecular pathway targeted

Hormone receptor pathway

40 (40%) 42 (44%)

PI3K/AKT/mTOR pathway 46 (46%) 43 (45%)

RAF/MEK pathway 13 (13%) 11 (11%)

MP: Molecular profiling; NGS: Next‐generation sequencing; PFS: Progression‐free survival

Baseline patient characteristics

MP‐directed therapy (n= 99)

Physician‐directed therapy (n= 96)

82

Notes:

Notes:

No PFS Improvement Following Off‐label Matched Therapyin Patients with Metastatic Solid Tumors

Results: • Median follow‐up at time of primary analysis of PFS in both groups was 11.3 months

• Similar median progression‐free survival (p = 0.41) in:• Experimental group: 2.3 months (95% CI 1.7‐3.8)

• Control group: 2.0 months (95% CI 1.8‐2.1)• In both groups grade 3‐4 adverse events were observed (p = 0.30)

Conclusions: Use of targeted therapy outside indications of agents does not improve progression‐free survival compared with treatment at physician’s choice in heavily pre‐treated cancer patients

Le Tourneau, C., et al. (2015). Molecularly targeted therapy based on tumour molecular profiling versus conventional therapy for advanced cancer (SHIVA): a multicentre, open‐label, proof‐of‐concept, randomised, controlled phase 2 trial. Lancet Oncol 16(13):1324‐34.

MP: Molecular profiling; NGS: Next‐generation sequencing; PFS: Progression‐free survival

Progression‐free survival

HR 0.88 (95% CI 0.65‐1.19); p = 0.41

Molecularly targeted agentTreatment of physician’s choice

PFS (%)

Time (months)No. at risk

Molecularly targeted agent

Treatment at physician’s choice

0 62 4 8 10 120

20

80

40

60

100

99 62 20 10 5 2 0

95*

50 19 12 8 1 0*One patient was not followed‐up so is not shown here

Using multiplexed assays of oncogenic drivers in lung cancers to select targeted drugs

83

Notes:

Notes:

A Genomic Alteration was Identified in 64% of Patients with Lung Adenocarcinoma

Objectives: • Determine the frequency of genomic alterations (oncogenic drivers) in patients with lung adenocarcinomas

• Assess survival following a treatment strategy to target the identified drivers

Patients and methods: • Tumors from 1007 patients were tested for at least 1 gene, and from 733 patients for 10 genes (full genotyping)• MP by matrix‐assisted laser desorption/ionization time‐of‐flight mass spectrometry (Sequenom, Arizona Research Laboratories); multiplexed single‐nucleotide extension sequencing (SNaPshot, Applied Biosystem), or Sanger sequencing with peptide nucleic acid probes, as well as sizing electrophoresis• Selected, molecularly‐matched targeted therapies were initiated where genomic alterations were identified

Results: • Genomic alterations were identified in 466 of 733 (64%) patients with full genotyping performed• 44% of individuals with genomic alterations detected received a matched therapy

MP: Molecular profilingKris M.G., et al. (2014). Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs. JAMA 311(19):1998‐2006.

Patients with Lung Adenocarcinomas Receiving Matched Therapy Lived Longer

Results: • Median survival of the 938 patients with adequate data was 2.7 years (95% CI, 2.4–2.9)

• A higher median survival was observed in patients with a genomic alteration receiving a targeted therapy (3.5 years (IQR 1.96‐7.70), n = 260; p = 0.006)compared with patients with a genomic alteration but not receiving a targeted therapy (2.4 years (IQR 0.88‐6.20), n = 318)

Conclusions:• Patients with lung adenocarcinoma receiving molecular targeted therapy lived longer

• Molecular profiling may be clinically beneficial

Median survival (95% CI)

Kris M.G., et al. (2014). Using Multiplexed Assays of Oncogenic Drivers in Lung Cancers to Select Targeted Drugs. JAMA 311(19):1998‐2006.

1 2 3 4 5

Years

Survival probab

ility

0.2

0.4

0.6

0.8

1.0

00

No targeted therapy

Targeted therapy

No driver

Log‐rank p < 0.001

318 205 110 64 43 20

260 225 143 72 36 23

360 250 122 59 36 23

No. at riskPatients with oncogenic driver

No targeted therapy

Targeted therapy

No driver

IQR: Interquartile range

84

Notes:

Notes:

Identifying ALKRearrangements That are Not Detected by FISH with Targeted Next Generation Sequencing of Lung Carcinoma

Data analysis

MethodsGenomic profiling of 1,070 lung carcinomas was performed on DNA extracted from formalin fixed, paraffin embedded specimens, from either primary tumors or metastatic sites

47 patients with lung adenocarcinomas were identified whose tumors harbored no evidence of a genomic alteration via extensive, focused non‐NGS testing.

Ali, S., et al. (2014) Identifying ALK rearrangements that are not detected by FISH with targeted next generation sequencing of lung carcinoma. J Clin Oncol 32:5s, 2014 (suppl; abstr 8049).

ResultsHybrid Capture NGS‐Based, Comprehensive Genomic Profiling identified 47 ALKrearrangements (4.4% of cases) in 1070 advanced lung cancer cases

Of the 28 ALK rearranged specimens also tested by ALK FISH, 9 (32%) were negative, and 19 were positive

Identifying ALKRearrangements That are Not Detected by FISH with Targeted Next Generation Sequencing of Lung Carcinoma

Subsequent treatments

Conclusion‐ Targeted NGS may be more sensitive for the detection of ALK rearrangements than FISH. ‐ In light of the responsiveness of ALK NGS+/FISH tumors to crizotinib, the use of FISH as the gold standard for ALK detection in LC warrants prospective study

Treatment status‐ 22 patients were treated with crizotinib and had response data available‐ 19 responded by investigator assessmentOf the 9 cases negative by FISH:‐ 5 patients responded to crizotinib‐ 2 patients did not‐ The response data for the remaining 2 patients is unavailable

Hybrid Capture NGS‐Based, Comprehensive Genomic Profiling revealed ~32% of ALK fusions that are being MISSED by FISH

Ali, S., et al. (2014) Identifying ALK rearrangements that are not detected by FISH with targeted next generation sequencing of lung carcinoma. J ClinOncol 32:5s, 2014 (suppl; abstr 8049).

85

Notes:

Notes:

The Clinical Utility of NGS in Lung Cancer1N Peled,2A Dvir,2Gutman-Li Soussan,1FlexD,1E Dudnik,†1M Ilouze,†1AB Rozenblum

Evaluate the impact of hybrid NGS on AIM:treatment strategy in NSCLC

In PressJournal of Thoracic Oncology;

Methods ‐ Two

Commercial

Profiling Tests

1. Hybrid capture‐based NGS of solid tissue (Foundation‐

One, n=82/101)2. NGS of circulating cell‐free

DNA (Guardant360, n=19/101)

Study Population

The studied population is a focused group of patients ‐ the majority was negative on standard molecular testing

Age at Diagnosis (Years) 63 (Median), range: 20-84

Gender

M 46.5% (n=47) F 53.5% (n=54)

Cigarette Smoking Status Never 44.55% (n=45) Ever, Average Pack Years 52.48% (n=53), 38PY Not-Available 2.97% (n=3)

Histopathology

Adenocarcinoma 85.1% (n=86)

Other 14.9% (n=15)

Type of NGS Test Performed Solid Tissue (FoundationOne) 81.2% (n=82) Blood Circulating Cell-Free DNA (Guardant360) 18.8% (n=19)

Standard Testing Results EGFR % Negative or Inconclusive 85.2% (n=86) ALK

% Negative or Inconclusive 71.3% (n=72)

NGS Performance Timing Pre 1st Treatment Line 50.5% (n=51)

Post 1st Treatment Line 49.5% (n=50)

86

Notes:

Notes:

Seventeen patients were diagnosed with an EGFR/ALK alternation after previous negative/false approved standard molecular testing; Fifteen were treated with a targeted agent

Treatment Change 33% n=5/15 43% n=37/86

Driver No. of pts %

EGFR 11 29.7%

ALK 5 13.5%

RET 5 13.5%

2ERBB 5 13.5%

*MET 5 13.5%

ROS1 2 5.4%

BRAF 1 2.7%

KRAS 1 2.7%

NTRK1** 1 2.7%

NF1 1 2.7%

Previously TestedUpfront NGS

Driver No. of pts %

EGFR 3 60%

ALK 2 40%

Treatment Change

Response to Targeted Therapy

ORR: 64%

87

Notes:

Notes:

Duration of Treatment

Response to PD1 Therapy by Mutation Status

88

Notes:

Notes:

High Mutational Burden Predicts Response to Pembrolizumab in NSCLC

High Mutation Burden ≥200

Low Mutation Burden >200

Rizvi et al. 2015

Slide 3

89

Notes:

Notes:

Future Treatment Algorithm in Advanced NSCLC

Non‐squamous cellNon‐squamous cell

Locally Advanced or Metastatic NSCLCLocally Advanced or Metastatic NSCLC

Any histologyAny histology

EGFR PositiveEGFR

PositiveALK

positiveALK

positive

EGFR inhibitorEGFR

inhibitorALK

inhibitorALK

inhibitor



ResponseResponse

PD‐L1 ≥ 50% TPSPD‐L1 ≥ 50% TPSPD‐L1 < 50% TPSPD‐L1 < 50% TPS

TESTING: PD‐L1 EGFR, ALK, histologyTESTING: PD‐L1 EGFR, ALK, histology

PD‐L1 (+)Driver MutationDriver Mutation

Progression Progression Progression Progression

*Maintenance Pemetrexed (NSQ)*Maintenance

Pemetrexed (NSQ)

PD‐L1 ≥1% TPSPD‐L1 UnknwonPD‐L1 ≥1% TPSPD‐L1 Unknwon

Progression Progression

Pembrolizumab Pembrolizumab

PD‐L1PD‐L1

PDL1 TherapyPDL1 Therapy

Take Home Message

THANK YOU

/

90

Notes:

Notes:


Interactive Dialogue Session with Faculty‐Facilitated Analysis and Discussion Focused on NGS Technologies to Optimize Assessment and Targeted Therapy for

Patients with Lung Cancer

The multiplicity of potential driver mutations and associated genomic alterations that are being identified in NSCLS — including those whose targeting has been validated to improve clinical outcomes — are of such diversity and established clinical importance that hybrid capture‐based NGS comprehensive genomic profiling:

1) Should be utilized as the initial pathogenomic strategy in all patients with an established diagnosis of NSCLC

2) Should be utilized as the initial pathogenomic strategy in most patients with an established diagnosis of NSCLC

3) Should be utilized as the initial pathogenomic strategy in some patients with an established diagnosis of NSCLC

4) Should be utilized as a pathogenomic strategy in most patients with an established diagnosis of NSCLC, but only after hot spot panels have been employed




91

Notes:

Notes:

The growing body of evidence suggesting responsiveness in NSCLC to PD‐1 checkpoint inhibitors based on mutational load supports the use of hybrid capture‐based NGS comprehensive genomic profiling in almost all patients in NSCLC:

1) Strongly agree

2) Agree

3) Moderately agree

4) Agree somewhat

5) Disagree




The Role of Genomic Profiling to Optimize Clinical Outcomes in Patients

with Breast Cancer

Rebecca Dent, MD, FRCP (Canada)Senior Consultant, National Cancer Center Singapore

Associate Prof Duke‐NUS

92

Notes:

Notes:

I have received travel grants, honorariums and/or speaker fees from:

AstraZeneca, Celgene, Eisai, Genentech, Merck, Novartis, Pfizer, Roche


New Technologies

93

Notes:

Notes:

The Microenvironment

TCGA:The Cancer Genome Atlas

94

Notes:

Notes:

Heterogeneity

Tumor Evolution

Yates Nature Genetics 2012

95

Notes:

Notes:

Molecular Portraits of Breast Cancer

• Low HER2 cluster expression

• Low ER (and related genes) expression

Usually “triple negative”

• High basal cluster

– basal CK (5, 6, 14, 17)

– EGFR, c-kit

– others…

• Very proliferative

• Often p53 mutant

• Evidence of genomic instability

HER2 cluster

Basal gene cluster

Luminal (hormone receptor-related) cluster

Proliferation cluster

Basal- like Group

Perou C , Sorlie T et al. Nature 2000

METABRIC Validation

Ali Genome Biol 2014

Carlos Caldas from Cambridge group has given us 10 subtypes of breast cancer using over 10,000 samples

Evolution of increasing complexity ‐ but what is driving individual cancer

96

Notes:

Notes:

17%

35%48%

<1%

Hormone Receptor-Positive

HER2-E (n=26)

Lum A (n=54)

Lum B (n=75)

Basal (n=1)

Claudin-Low (n=0)

Normal-like (n=0)

51%

24%

4%

12%

3%6%

Hormone Receptor-Negative

HER2-E (n=56)

Lum A (n=26)

Lum B (n=5)

Basal (n=13)

Claudin-Low (n=3)

Normal-like (n=6)

31%

30%

30%

5%

2%

HER2+ tumors

HER2-E (n=82)

Lum A (n=80)

Lum B (n=80)

Basal (n=14)

Claudin-Low (n=3)

Normal-like (n=6)

Intrinsic Subtypes by Hormone Receptor

Carey, JCO 2015

NOAH: Response and Outcome Chemo/Trastuzumab vs Chemo alone

Perez et al, JCO 2014; Prat et al, CCR 2014

N9831/B31: Impact of H added to chemo

Subtype pCR 3y EFS

(all are cHER2+) ‐ H + H ‐ H + H

HER2‐Enriched (n=63) 28% 53% 61% 79%

Not HER2‐E (n=51) 18% 34% 48% 50%

NOAH: Impact of H by subtype

Small, hypothesis‐generating.Suggests that addition of HER2‐targeting especially important in HER2‐E subtype

97

Notes:

Notes:

pCR by Intrinsic Subtype

Other subtypes:3 Claudin‐low (0 pCR)14 basal‐like (36% pCR)Excluded “normal” (n=6)

70%

80%

71%

52%

34%37%

38%

9%

36%40% 41%

22%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

Overall THL TH TL

HER2E (n=82)

LumA (n=80)

LumB (n=80)

P=0.04

Carey, JCO 2015

This may be why effect larger in HR-than HR+

Note ~ 70% pCRrate with 12 weeks TH (APT regimen) in HER2-E

N9831: immune signature associated with RFS only in H-treated cohorts

Perez EA et al. JCO 2015; Loi S et al, Ann Oncol 2013

Immune Signatures / TIL and Prognosis

FinHER: Tumorinfiltrating lymphocytes associated with greater

benefit of H and prognosis

98

Notes:

Notes:

How do we identify patients who will respond within a molecular subgroup?

Ligand‐dependent Transcription

ER

ERE

ERER

Target‐Gene

MEK

MAPK

SOS

RAS

RAF

P

ER

Proliferation Cell SurvivalInvasion

P

PP

P

P

Adapted from Johnston S. CCR. 2005;11:889S‐899S.

Growth Factor

Estrogen/Tamoxifen

Ligand‐independent Transcription

EGFR/HER2

IGFR FGFR MET

Scr

Cyclin D

E2F

p16INK4A

Stat3

p21cip1

CDK4/6

P P

PP

P P

PP

PI3‐K

Akt

mTORC2

mTORC1

PI3K AKT mTOR Pathway

99

Notes:

Notes:

Median PFS (central)EXE + EVEROL: 11.0 moEXE + placebo: 4.1 mo

HR = 0.38 (95% CI: 0.31–0.48)Log-rank P value: < 0.0001

0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 102 108

0

20

40

60

80

100

Probab

ility of Event, %

Time, weeks

BOLERO-2

Baselga J et al, N Engl J Med 2011 366; 520-529Piccart M, et al. ASCO 2012; # 559.

84% prior endocrine response

EVE.PIK3CA.WT

EVE.PIK3CA.Alt

Study Arm

PIK3CA HR (95%CI)

EVE WT 0.36 (0.22 - 0.57)PBO WT

EVE Alt 0.44 (0.27 - 0.70)PBO Alt

0 100 200 300 400 500 600 700

0.0

0.2

0.4

0.6

0.8

1.0

Time, days

Probab

ility of PFS

Hortobagyi et al ASCO 2013 & 2014, Hortobagyi et al JCO. 2015 (in press)

Subgroup Definition

WT No alteration in any gene

Single Alteration in 1 gene only

Multiple Alterations in2 or more genes

Analysis of the following 4 genes: PIK3CA, PTEN, FGFR1/2, CCND1

Subgroup N HR* (95%CI)

EVE: WT27%

0.24 (0.11 - 0.54)PBO: WT

EVE: Single49%

0.26 (0.16 - 0.43)PBO: Single

EVE: multiple24%

0.78 (0.39 - 1.54) PBO: multiple

Everolimus benefit maintained in patients regardless of gene alterations in

PIK3CA

Patients with ≤1 genetic alteration in derive greater PFS benefit with EVE

PBO.PIK3CA.WT PBO.PIK3CA.Alt

100

Notes:

Notes:

4 main subtypes

Luminal AR (16‐23%)

Mesenchymal (18‐28%)

Basal immune suppressed (25‐30%)

Basal immune activated (29‐31%)

Burstein et al, CCR 2014

Triple Negative Breast Cancer MD Anderson and Baylor Collaboration

(DNA profiling and RNA Seq)

101

Notes:

Notes:

201

% o

f br

east

canc

ers

0

5

10

15

20

25

30

“Druggable” Genomic Alterations

Adapted from F. Andre

Rationale for Multi‐Gene Testing

Identify driver mutation(s) that promote survival or proliferation

Individualize treatment with targeted drugs that inhibit those key molecular pathways

Improve efficiency of screening for clinical trials with targeted drugs

102

Notes:

Notes:

Phase II GDC‐0032 + Fulvestrant

Dickler M, et al. ASCO 2016. Abstract P520.

ORR= 38.5% (PIK3CAmt) vs 10.5% (PIK3CAwt)

Identified in metastatic ER+ breast cancers after anti‐estrogen treatment

Rare in primary tumours, enriched in metastases Produce ligand‐independent activation of ER Polyclonal ESR1mutations may be detected in circulation;

produce resistance to AIs but not fulvestrant

Toy W et al Nature 2013Robinson DR et al Nature 2013Merenbakh‐Lamin K et al Cancer Res 2013

ESR1 Gene Mutations

103

Notes:

Notes:

Joseph JD et al. eLife 2016

Activity in ESR1mt Preclinical Models

Oral SERDs in Development

ARN-810/GDC-810RAD1901AZD9496SRN-927LSZ102

ERBB2mutation ~2% of non‐HER2 amplified breast cancers

May be enriched in lobular and metastatic breast cancers

Cell lines resistant to reversible HER2 TKI, sensitive to irreversible HER2 TKI

Bose R et al Cancer Discovery 2013. 3(2):1-14. Ross J et al CCR 2013. 19(10); 2668–76

ERBB2Mutation as an Oncogenic Driver in HER2 Non‐Amplified ER+ Breast Cancers

104

Notes:

Notes:

Neratinib in ERBB2‐Mutant, Non‐Amplified Breast Cancer

Ma CX et al ASCO 2016 Abstract 516

Washington University Phase II SUMMIT Basket Trial

Hyman DM et al SABCS 2015 Abstract PD5-05

AZD5363 (AKT inhibitor) Monotherapy in AKT1 E17K Mutant, ER+ Breast Cancer

Hyman DM, Smyth L et al AACR-EORTC-NCI Meeting 2015

105

Notes:

Notes:

15 3874

107

168

234

314370

449

531

619

722

795

0

100

200

300

400

500

600

700

800

900

Cumulative Accrual Projected Cumulative Accrual

High Level of Enthusiasm

NCI‐MATCH

Princess Margaret IMPACT/COMPACT

SHIVA Trial

Le Tourneau C et al Lancet Oncology 2015: 16:1324-34

106

Notes:

Notes:

423 patients signed

CGH arrays:288 patients

Biopsy of metastasis:403 patients

Targetablealterations in195 patients

27%Treatmentdriven by

genomics in 52 patients

+ 4 patients ERBB2 ampCGH array

13%

SAFIR‐01 Trial

Andre F et al Lancet Oncology 2014; 15(3):267-74

Mutation in Potentially Actionable Gene

Underwent Genomic TestingN = 2000

Genotype‐matched trial after genomic testing?

No (1211)

Genotype‐SelectedTrial N = 54

Genotype‐RelevantTrial N = 29

Yes (789)

No (706)Yes (83)

MD Anderson Institutional Profiling

54/2000 (3%) of pts who underwent genomic testing received genotype‐selected treatment

Meric-Bernstam F et al JCO 2015

107

Notes:

Notes:

NCI‐MATCH: Preliminary Phase

Activated 08/12/15; paused 11/11/15: 92 days

Patient cases registered for screening 795

Cases with samples submitted 739

Cases where labs were able to complete tumor testing

64587%

(N=739)

Cases with mutation matching 1 of 10 available treatment arms

569%

(N=645)

Patients matching specific eligibility criteria for, and assigned to, a treatment arm

335%

(N=645)

Patients who entered 7 of 10 available treatment arms

162.5%

(N=645)

Conley BA et al AACR 2016 Abstract CT101

32% 61%**

*Overall Response Rate p-value = 0.04**Any Reduction in Target Lesions p-value <0.0001

RECIST v1.1 ORR 20%*

Un‐matched Matched

RECIST v1.1 ORR 11%

Princess Margaret IMPACT/COMPACT Trials by Genotype‐Matching

Stockley TL et al Genome Medicine 2016; 8:109

108

Notes:

Notes:

Vall d’Hebron Breast Cancer Profiling

Oliveira M et al SABCS 2015 Abstract P2-08-13

N=280 patients with multi-gene panel results

N=127 (45%) no actionable

mutation(s)

N=153 (55%) ≥1 actionable

mutation(s)

N=62 (22%) genotype-directed

trials

Circulating Free DNA (cfDNA)

Opportunities

• Greater sensitivity of ddPCR & NGS cfDNA testing methods

• Alternative to metastatic biopsy for genomic characterization

• Detection of treatment‐emergent & polyclonal mutations

• Monitoring of treatment response

Challenges

• Assay standardization

• Optimal cut‐offs for clinical decision‐making

• Discordance with tissue‐based testing results

109

Notes:

Notes:

Development of MBC Precision Medicine

Arnedos, M. et al. (2015) Precision medicine for metastatic breast cancer—limitations and solutionsNat. Rev. Clin. Oncol. doi:10.1038/nrclinonc.2015.123

218

Take Home Messages

Driver mutations can be identified that are relevant for clinical trials with promising new investigational drugs

Likelihood of treatment‐matching following multi‐gene testing beyond these “druggable” driver mutations is low

Further evidence is needed before multi‐gene testing can be recommended in routine clinical practice

110

Notes:

Notes:

AR‐Driven Biology in TNBC Using a Gene Expression Profiling Assay

CBR16

PREDICT AR

AR IHC

YesNo

Not treated

Positive<1%≥ 1%

Data Cut‐off 01 July 2015

Parker, et al ASCO 2015

AR IHC PREDICT ARCBR16

Negative

• Hierarchical clustering according to biology

• Responders clustered within a recognized and distinct pattern that includes AR1‐5

– 521 genes significantly different in responders at 1% false discovery rate

• A diagnostic test was created and validated

Overall Survival by PREDICT AR Status

5662

5355

4946

4537

4227

4024

3213

156

116

32

Data cutoff 1Jul2015ITT = intent to treat; mOS = median survival; CI = confidence interval; .

Patients at riskPREDICT AR+PREDICT AR−

0

80

40

20

n = 118

PREDICT AR−mOS 32.3 weeks(95% CI: 20.7, 48.3)

PREDICT AR+mOS 75.6 weeks(95% CI: 51.6, 91.4)

0 8 16 24 33 41 49 61 64

Weeks

100

60

Ove

rall

Su

rviv

al (

%)

85

ITT Population

NCT01889238

PREDICT AR+ mOS 18.0 monthsPREDICT AR – mOS 7.5 months

111

Notes:

Notes:

ENDEAR: A Phase 3 Randomized, Placebo Controlled 3‐Armed Study

N = 780 patients with advanced, diagnostic‐positive TNBC who received either 0 or 1 prior line of systemic therapy for advanced disease (locally advanced or metastatic) will be randomized.

Acknowledgements

• Fabrice Andre

• Phil Bedard

• Andre Goncalves

• Paul Mainwaring

• Tira Tan

112

Notes:

Notes:



Patients with Breast Cancer

Based on our evolving understanding of TNBC subtypes —including hypothesis related to polymerase inhibitors for BRCA‐mutated TNBC, antiandrogens for androgen receptor (AR)‐positive TNBC, fibroblast growth factor receptor (FGFR) inhibitors for TNBC harboring FGFR amplifications and so on — current treatment of TNBC based on molecular subsets and mutations, hybrid capture NGS comprehensive genomic profiling should be used routinely, in preference of other strategies, as a primary methodology for precision‐focused tumor assessment and targeted treatment in this patient population:

1) Strongly agree

2) Agree

3) Moderately agree

4) Agree somewhat

5) Disagree




113

Notes:

Notes:

Given the preliminary studies recently presented at the SABC looking at immune checkpoint inhibition in TNBC, there us a rationale for looking at mutational loads using of hybrid capture‐based NGS comprehensive genomic profiling in this patient population:

1) Strongly agree

2) Agree

3) Moderately agree

4) Agree somewhat

5) Too early to form an opinions




Comprehensive Genomic Profiling of Gynaecological Cancers to Optimize Therapy

A Science‐to‐Practice Update

Dr David SP TanBSc(Hons), MBBS(Hons)(London), PG Dip(Oncology), MRCP(UK)(Medical Oncology),

PhD(London), FRCP(Edin)Consultant Medical Oncologist :: National University Cancer Institute, Singapore :: National

University Hospital

114

Notes:

Notes:


Employment or Leadership Position: None

Consultant/Advisory Role: Astra Zeneca, Roche, D3 Singapore Stock Ownership: None

Honoraria: Astra Zeneca, Roche

Research Funding: Astra Zeneca, KaryopharmTherapeutics, National Medical Research Council (NMRC) Singapore, National University Hospital Cancer Institute Singapore (NCIS) Endowment fund, NCIS Centre Grant Expert Testimony: None Other Remuneration: Merck

Understanding the Complexity of Ovarian Cancers

115

Notes:

Notes:

Histological Subtypes of Epithelial Ovarian Cancer

Serous 75%High grade 80‐90%Low grade 10‐20%

Endometrioid 10%

Clear cell 10‐25%

Mucinous 5%

Different Subtypes = Different Outcomes

Ovarian Cancer

Chan et al Gynae Onc 2008

Stage I Stage III

Stage II Stage IV

116

Notes:

Notes:

Prat J Ann Oncol 2012

Ovarian Cancer

Different subtypes = Different Origins = Different Molecular Abnormalities

Mutations in Endometrial Cancers

Zhao et al. PNAS 2013Liang et al Genome Research 2012McConechy et al J Pathol 2012

Serous Endometrial Cancers (UPSC) CNAs

117

Notes:

Notes:

Mutations in Cervical Cancer

Ojesina et al Nature 2013

Ovarian Cancer: Evidence for Intratumoral Heterogeneity

Side population (SP) cells in ascites SP cellsNon ‐SP cells

Hu et al BJC 2010

SP cells

Non‐SP cells

118

Notes:

Notes:

Gynaecological Cancers AreHistologically, Molecularly, Intratumorally Heterogeneous:

Multiple Disease Entities

Therapeutic approaches need to start taking these issues into consideration

Targeting the Key Hallmarks of Cancer

Hanahan D & Weinberg RA (2011) Cell.

119

Notes:

Notes:

Targeting Homologous Recombination Repair Deficiency in Ovarian Cancer

Germline BRCA1/2Mutations: A Case of MultifactedEvolving Actionability in Ovarian Cancer

Associated with increased risk of breast and ovarian cancer

Fear of “genetic stigma” still a significant hindrance to uptake of testing in Asia

Concerns re insurance coverage in countries without nationalised health care system

BUT prognostic and therapeutic implications for patients

120

Notes:

Notes:

Chemotherapy Response in BMOC

Tan and Kaye 2015 ASCO Educational Book

BRCA+ vs Non-hereditary: Median OS 8.4 vs 2.9 years

HR = 0.3

BRCA mutants with ovarian cancer

Improved Responses and Increased Survival for BRCA1/2‐Mutant vs Non‐Hereditary EOC

Excellent responses to chemotherapy

Improved survival compared to non‐BRCA mutants

1 Tan et al JCO 20082 Bolton et al JAMA 20123 Sun et al PLoS One 2014

121

Notes:

Notes:

BRCA1/BRCA2 failure

Chromosomal instability

Cell death

Impaired HR repair

Alternative error prone repair

DNA replication fork arrest and collapse

HR‐based repair

Normal BRCA1/BRCA2

Chromosome stability

Cell survival

RAD51

Impaired HR Repair (BRCAness) and Platinum/PARP Inhibitor Sensitivity

HR, homologous recombination; DSB, double‐strand breakFarmer H et al. Nature 2005;434:917–921; Bryant HE et al. Nature 2005;434:913–917

H2AX

DSB

Alkylating agents (Platinum)

Genotoxic stress (Radiation)

PARP inhibitor

Phase I trial confirms excellent tolerance and expansion in 50 BRCA patients showed 46% response.

“this is nothing like chemotherapy

Fong P et al. N Engl J Med, 2009; 361, 123‐134;Fong P et al. J Clin Oncol, 2010; 28, 2512‐2519

Pre-clinical Early Clinical Trials(Phase I, incl. IB)

Randomised Clinical Trials (Phase II and III)

Randomised trial (maintenance therapy) showed marked PFS benefit particularly in BMOC

Farmer et al, Nature 2005 Ledermann et al, NEJM 2012 366 1382‐92Ledermann et al Lancet Oncology 2014

PARP : poly(ADP) ribose polymerase

Exquisite preclinical

efficacy of PARPi

PARP Inhibitors for BRCA1/2 Mutant Patients

2005 2015

122

Notes:

Notes:

Olaparib Monotherapy for BRCA1/2Mutant OC – The Route to Registration in the USA

• From the ongoing pooled analysis of almost 300 patients, data on subgroup of 137 patients who received ≥ 3 lines of chemo presented to FDA for accelerated approval.– response rate 34%; response duration 7.9m.

Note: approval does not distinguish between platinum‐sensitive and platinum resistant BMOC

Study 42: Matulonis et al, SGO 2015

Plat sens 35/74 47% resp

Plat resi 31/115 27% resp

Other PARP Inhibitors in Clinical Trials

AGO14699 (Rucaparib) Clovis/Pfizer IV/oral

MK 4827 (Niraparib) Merck Oral

ABT 888 (Veliparib) Abbott Oral

INO‐1001 Inotek IV

GP1201 Eisai Oral

CEP 9722 Cephalon Oral

BMN 673 (700x more active than olaparibin vitro)

BioMarin Oral

Iniparib (BSI‐201) is NOT a PARP inhibitor

123

Notes:

Notes:

HR DNA REPAIR PATHWAY

HR Repair: Not Just BRCA1/2

Levine et al 2013 TCGA

HRD Defects in High Grade Serous Ovarian Cancers

~50% of HGSOC have HRD related genetic aberrations

124

Notes:

Notes:

Pennington et al. Clin Cancer Res 2014;20:764‐775

115 of 367 (31.3%) EOC pts had deleterious mutations in 13 homologous recombination genes:

Germline homologous recombination mutations included 49 (13.4%) in BRCA1, 17 (4.6%) in BRCA2, and 22 (6%) in other homologous recombination genes, including BARD1, BRIP1, CHEK1, CHEK2, FAM175A, NBN, PALB2, RAD51C, and RAD51D.

Mutations in HR Genes and Platinum Response in EOC

BRCA1/2 Deficiency is Not Restricted to Ovarian and Breast Cancer

• Percentage of tumours showing loss of BRCA1 or BRCA2 (copy number) in some different tumour types

http://cancer.sanger.ac.uk/cosmic/gene/analysis?ln=BRCA1#dist Accessed 03/07/14;http://cancer.sanger.ac.uk/cosmic/gene/analysis?ln=BRCA2#dist Accessed 03/07/14

72.9

31.8

16.7

14.1

13

7.2 5.3

Loss of BRCA1

Ovary

Breast

Endometrium

Lung

Large intestine

CNS

Kidney

56.7

53.9

38.5

28.8

24.6

12.410.6 3.3

Loss of BRCA2

Lung

Ovary

Breast

CNS

Pancreas

Kidney

Endometrium

Large intestine

Tumours with BRCA defects represent potential targets for PARP inhibitors. extend use of PARP inhibitors to other tumour types with BRCAness phenotype

Abbreviation: CNS, central nervous system

125

Notes:

Notes:

Apart From Somatic/ Germline Mutation Testing for Individual HR genes, How Else Can We Identify HR Deficient Tumours?

BRCAmut

BRCA-like

Chromosome No.

Biomarker Negative

Hypothesis 1: Ovarian cancer patients with high genomic LOH suggesting BRCA-like signature will respond to rucaparib.

Hypothesis 2: Ovarian cancer patients who are “Biomarker Negative” (ie, with low genomic LOH) will not respond to rucaparib.

250

NGS=next-generation sequencing; mut=mutation; wt=wild type.

HRD Causes Genome‐Wide Loss of Heterozygosity that can be Measured by Comprehensive Genomic Profiling Based on NGS

BRCAwt

McNeish et al ASCO 2015

ARIEL 2 Study

126

Notes:

Notes:

Primary Efficacy Analysis: PFS in BRCAmut and BRCA‐like versus Biomarker Negative Patients

HRD SubgroupMedian PFS, mo (90% CI)

BRCAmut 9.4 (7.3, Not Reached)

BRCA‐like 7.1 (3.7, 10.8)

BiomarkerNegative

3.7 (3.5, 5.5)

SubgroupComparison

Hazard Ratio (90% CI)

BRCAmut vsBiomarkerNegative

0.47 (0.35, 0.64)

BRCA‐like vsBiomarkerNegative

0.61 (0.41, 0.92)

Progression-free survival by HRD molecular subgroup

BRCAmut

BRCA-likeBiomarker Negative

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1.00.90.80.70.60.50.40.30.20.1

0

Time (months)

PF

S

CI=confidence interval.

McNeish et al ASCO 2015

NOVA Trial: Niraparib Maintenance in High‐Grade Serious Ovarian Cancer

127

Notes:

Notes:

NOVA Trial: Niraparib Maintenance in High‐Grade Serious Ovarian Cancer

The Myriad HRD Test

128

Notes:

Notes:

NOVA Trial: PFS in non‐gBRCAmut Subgroups

Key Practical Issues When Using PARP Inhibitors for the Treatment of BRCAMutated Ovarian Cancer

Testing for BRCA mutation ‐ when ?

Tumour testing for somatic mutation?

Which line ‐ 2nd or 3rd line maintenance?

129

Notes:

Notes:

How are Patients with BRCA1/2Mutations Identified?

Approximately 35% patients with BRCA mutated ovarian cancer have NO family history of cancer

25% BRCA mutated ovarian cancer occurs in > 60 years old

Somatic mutations are found in 5‐6 % HGSOC

All patients with high grade ovarian cancers should be tested for a BRCAmutation

Histological Type is NOT a Good Predictor of BRCAMutation

Frequency of germline BRCA mutation

Total population

Serous Endometrioid Clear Cell Mucinous

Risch HA et al1 13.2% 18.0% 7.1% 0%

Soegaard M et al2 5.8% 5.4% 5.4% 9.1% 0%

Malander S et al3 8% 7.6% 13.0% 12.5% 0%

Alsop4 14.1% 16.6% 6.3% 8.4% ‐

1. Risch HA, et al. J Natl Cancer Inst 2006;98:1694‒1706; 2. Soegaard M et al. Clin Cancer Rev 2008;14:3761‒3767; 3. Malander S et al. Eur J Cancer 2004;40:422‒428. i4 Alsop et al J Clin Oncol 2012 30:2654-2663

130

Notes:

Notes:

Trial PopulationFrequency of

somatic mutations

Hennessy et al1 235 unselected ovarian cancers 11/235: 5%

TCGA network2489 high‐grade serous ovarian

cancers19/316: 6.1%

Pennington et al3 390 ovarian carcinomas 20/367: 5.5%

Ledermann et al4265 high‐grade, recurrent

ovarian carcinomas, platinum‐sensitive

18/265: 6.8%

BRCA Somatic Mutations in Ovarian Cancer

1. Hennessy BT et al. J Clin Oncol 2010;28:3570–3576; 2. The Cancer Genome Atlas Research Network (Suppl.). Nature. 2011;474(7353):609–6153. Pennington P et al. Clin Cancer Res 2014;20(3):764–775; 4. Ledermann J et al. Lancet Oncol 2014;15(8):852–861.

BRCA Somatic Mutations in Ovarian Cancer

Knowledge of BRCA1/2 or other HRD status in patients with ovarian cancer will have crucial implications for choice of therapy in the primary and recurrent disease setting.

All patients diagnosed with non‐mucinous ovarian cancer should be referred for germ‐line or somatic testing of ovarian cancer for BRCA1/2 mutations

?Clinical relevance of other HRD defects – e.g. RAD51C/ ATM

131

Notes:

Notes:

• Key growth factor‐mediated signal transduction pathway

• PIK3CAmutations reported in:

18% of breast ca

17%‐33% of cervical ca

39% of endometrial ca

40% of ovarian ca

• Associated with platinum and taxaneresistance

PI3‐kinase‐AKT‐mTOR Pathway

Tan et al BJC 2013Janku et al J Clin Oncol 2012 From Weigelt and Downward; Front. Oncol., 2012

CBio Portal Oncoprint of mTOR pathway genes in ovarian cancerRed = gene amplifications, Blue = deletions and Green dots = mutations.

Musa & Schneider Transl Cancer Res 2015;4(1):97-106

Frequency of Gene Alterations Noted in mTOR Pathway in Epithelial Ovarian Cancer (n=580) from TCGA

132

Notes:

Notes:

Efficacy of Targeted Sequencing with Matched PI3K/AKT/mTOR inhibitor Therapy

Waterfall plot of patients with breast and gynae cancer harbouring PIK3CA mutations treated with phosphatidylinositol 3‐kinase/AKT mammalian target

of rapamycin inhibitors

Janku et al J Clin Oncol. 2012 Mar 10;30(8):777‐82.

ORR = 30%

Evidence for efficacy in targeting this pathway in EOC remains limited

Good predictive biomarkers urgently needed PIK3CA and PTEN mutations alone do not appear sufficient ?Genotype specificity e.g. H1047R vs E545K, AKT1E17KmutationsContext may be crucial e.g. endometrioid/ clear cell vs high grade serous EOC

Inhibitors of this pathway may have more of a cytostatic effect leading to disease stabilisation vs tumor shrinkage

Duration of response usually short PI3K pathway inhibition alone may be insufficient, and combination strategies may be required.

Results from combination studies using PIK3CA/Akt with chemotherapy and other pathway inhibitors in EOC currently awaited

PIK3CA AKT mTOR Pathway Summary

133

Notes:

Notes:

What’s Next for Precision Medicine in Gynaecological Cancer?

Epi-AMesStem-AStem-B

Epi-B

Mesenchymal

IFN-inducibleMHC Class IIIgs

Stem-A

Epi-A/Stem

Epithelial

VCAM1

ZEB1

FN1

PDGFRA

TWIST1

OAS1/2

HLA-Ds

IGH/K/Ls

MYCNCDH3/2

NCAM1TOP2A/BUB1/CCNE1/CENPA

LGR5

WNT5A

DKK3

SFRP1

PROM1

XIST

KRT6A/17/14/19/7

EPCAMCD24

CDH1

MUC1

Epi-A

Epi-B

Mes

Stem-A

Stem-B

p < 0.0001

Five major subgroups were identified within EOC that harbor distinctive signatures of Epithelial, Mesenchymal, or Stem‐like, which confer to different

clinical survival outcomes.

EOC Gene Expression Molecular Subtypes

Tan, Miow & Huang et al., EMBO Mol Med, 2013

Meta-analysis (Tan, Miow, & Huang et al., EMBO MM, 2013) of 1,538 EOCs including all histological types.

5 subtypesshowing survival differences

134

Notes:

Notes:

Molecular Subtypes Likely to Reflect Aggregate Phenotype of Tumour Cells and Microenvironmental Factors

Balkwill et al Journal of Cell Science, 2012

Antiangiogenic Therapy with Bevacizumab Improves PFS in First Line Treatment of Ovarian Cancer

135

Notes:

Notes:

Is the response to bevacizumab affected by the molecular subtype of ovarian cancer?

Is Response to Bevacizumab Dependent on Molecular Subtype? – ICON 7 data

Gourley et al ASCO 2014

Outcome of ‘Immune’ and ‘Proangiogenic’ Groups of Ovarian Cancer in ICON 7

Bev had adverse effect on PFS in immune subgroup

Benefit in pro-angiogenic subgroup

Control arm ICON7Immune and proangiogenic groups

Gourley et al ASCO 2014

136

Notes:

Notes:

Anti‐Microtubule Agents for Stem‐A Subtype

Dr. Clare Scott WEHI, PDXs from Mayo Clinic

Tan, Miow & Huang et al., EMBO Mol Med, 2013

Stem-A/C5-like PDX Stem-A/C5-like Subtype Clinical Trial

Immunotherapy:Anti‐tumour Immune Activation and Checkpoint Inhibition

Gettinger et al 2016

137

Notes:

Notes:

Immunotherapy and Gynaecological Cancers

Immune microenvironment affects disease outcomes in Gynae cancers:

• Ovarian:

– Intraepithelial CD8 TILs and a high CD8+/Treg ratio associated with favorable prognosis (Sato et al, PNAS 2005)

• Cervix:

– Largely HPV driven and reversed CD4/CD8 ratios of tumor‐infiltrating lymphocytes correlated with disease progression (Sheu et al, Cancer 1999)

• Endometrium:

– Presence of tumor‐infiltrating lymphocytes is independent prognostic factor in type I and II endometrial cancer (de Jong et al, Gynaeol Onc 2009)

Herzog et al SGO 2015

CD8+ Killer T Cells (CD8 TIL) are Associated with Survival in HGSC

100

50

0

% overall survival

Years

Dense CD8+ TIL Sparse CD8+ TIL

BCCA/VGH cohorthigh-grade serousoptimally de-bulkedn = 200p = 0.0008

5 10 150 Clarke, B. et al. 2009Milne, K. et al. 2009

138

Notes:

Notes:

Partial Response to PDL1 Inhibitor Avelumab in Metastatic Clear Cell Ovarian Cancer

DisisetalASCO2015

Baseline: 69 mm RLL lesion Week 25: 41 mm (‐40.6%)

• 65 years old; 6 prior lines for metastatic disease• 4th assessment cycle, still on treatment

Ovarian cancers developed at mean 48 years of age

Histologically, endometrioid (35%) and clear cell (17%) tumors were overrepresented.

The underlying MMR gene mutations in these families affected MSH2 in 49%, MSH6 in 33% and MLH1 in 17%.

Immunohistochemical loss of the corresponding MMR protein was demonstrated in 92% of tumors

Gynecologic Oncology 121 (2011) 462–465

139

Notes:

Notes:

MOCCA Trial: A Multicentre Phase II randomised trial of MEDI4736 (DURVALUMAB) versus physician’s choice chemotherapy in recurrent

ovarian clear cell adenocarcinomas (MOCCA)

Relapsed Clear Cell Cancer Ovarian Cancer

(>70% clear cell)

Inclusion-Histologically confirmed- WT1 negative-Relapsed after at least 1 line of platinum-based chemotherapy-Measurable disease by RECIST 1.1 -ECOG 0 / 1

Exclusion-Concurrent use of experimental anti-cancer agent-Untreated brain mets

MEDI-4736 (Durvalumab)

1500mg 4 weekly for max.12mths

CAELYX or Investigator’s choice if

prior Rx included caelyx (but antiangiogenic

therapy not permitted)

Crossover on PD

2:1 randomisation

2

1

Primary Endpoint: MOCCA: median PFS improvement from 10 weeks to 20 weeks

Secondary Endpoint: RECIST/ GCIG response

Singapore (GOGS)Korea (KGOG)

Australia (ANZGOG)

N = 31

N = 15

Checkpoint Inhibitors for Endometrial Cancer

MSI‐High tumours:

• ~20–30% of endometrial cancers are characterized by high microsatellite instability (MSI‐H) due to defects in DNA mismatch repair (MMR) pathway.

Replicative DNA polymerase epsilon (POLE) ultra‐mutated tumours:

• 5% of endometrial cancers ‐ predominantly endometrioid, grade III, and associated with peritumoral and tumor infiltrating lymphocytes

Both POLE and MSI‐H tumors exhibit higher numbers of CD8+ TIL characterized by PD1 overexpression

POLE tumours have highest number of predicted neoantigens per tumor sample, followed by MSI‐H tumors, and microsatellite stable tumors

Howitt et al JAMA oncol 2015Billingsley et al Cancer 2015

140

Notes:

Notes:

Endometrial Cancer Molecular Stratification

From TCGA Levine et al

MSI‐H

Clinical Responses to Pembrolizumab

Treatment in MMR Deficient vs Proficient

Cancers

Le DT et al. N Engl J Med 2015;372:2509-2520

RR of 40% and 71% in MSI‐H colorectal and non‐colorectal cohorts (including 2 patients with endometrial cancer) respectively

141

Notes:

Notes:

Immunotherapy for Endometrial Cancer

• A subset of highly immunogenic endometrial cancers characterized by ultra‐high somatic mutations rates resulting from defects in the proof‐reading function of POLE

From TCGA Levine et al

Mutations in the Replicative DNA Polymerase Epsilon (POLE) – the Ultramutated POLE Subtype

Landscape of TMB in >60,000 Clinical Cases

Immunotherapy approval Heavily investigated immunotherapy indication

Fabrizio DA et.al., ESMO 2016 Presentation #: 52O

142

Notes:

Notes:

Frequent Cases with High Mutation Burden in Nearly Every Tumor Type

20 mutations / megabase

Immunotherapy approval Heavily investigated immunotherapy indication


MSI‐High Specimens are a Subset of High TMB Specimens

Microsatellite stable

Microsatellite ambiguous

Microsatellite instable

All specimensn = 46,465

MSI and TMB High n = 550

TMB-Highn = 3,531


143

Notes:

Notes:

Key Questions for Immune Checkpoint Inhibitor Therapy in Gynaecological Cancers

1)What are the predictive biomarkers for checkpoint inhibitors in gynae cancers? PD‐1/PD‐L1 – not consistently predictive MMR/ MSI‐H – but POLE tumours are MSS Tumour mutational burden?

2) How can we overcome immune resistance to enhance the efficacy of checkpoint inhibitors in gynae cancers?

Case Study –Molecular Profiling of Metastatic Endometrioid Ovarian Cancer

50 yr old female with platinum resistant endometrioid ovarian cancer with lung, liver and sacral metastases

Progressed on 3 prior lines of chemotherapy

Referred to NCIS phase I unit ?targeted therapy

144

Notes:

Notes:

• Screening for actionable targets using NGS and copy number analysis in tumour tissue

• All cancer types

• Establish prevalence of mutations in local patients

• Evaluate clinical impact of molecular profiling (RR/PFS/OS)

Integrated Molecular Analysis of Cancer (IMAC) at NCIS

Patient with progressive disease

Consent, screening, tissue collection

Next generation sequencing using Ion Torrent PGM Sequencer withminimum requirement of 10‐

40ng DNA

FISH and CISH/ Gene expression profiling/ immunohistochemistry

Final Profiling Report

Results reviewed by IMAC tumour

board

Interpretation and

recommendation

Medical Oncologist

FFPE or fresh tissue

?Matched Therapy

• FFPE tissue ok

• Minimum of 10ng DNA required

145

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Notes:

AKT1 inhibitor

Patient with AKT1 E17K mutant endometrioid ovarian cancer with lung, liver and sacral metastases matched to an experimental AKT1 inhibitor

Mol Cancer Ther; 14(11) November 2015

Aug 2015 Oct 2015

Summary: Targeted Therapy for Gynaecological Cancer

New era of targeted therapy in gynaecological cancer Improved outcomes Increase the benefit:risk ratio Improved understanding of disease biology acceleration of new therapeutic developments

Challenges: Predictive biomarkers: Bevacizumab/ PARP inhibitors/ Immunotherapy Optimal timing of new agents in treatment Increase efficacy and durability of response ?combination studies Management of toxicity Cost

Translational studies important to understand reasons for success and failure and to gain new insights in tumour biology that may provide new therapeutic opportunities

146

Notes:

Notes:

THANK YOU

[email protected]


Interactive Dialogue Session with Faculty‐Facilitated Analysis and Discussion Focused on NGS Technologies to Optimize Assessment and

Targeted Therapy for Patients with Gynaecological Malignancies

147

Notes:

Notes:

Based on our evolving understanding of molecular markers and genomic alterations in gynecological cancers — potentially actionable markers extending beyond BRCA1/2, but also including HRD defects, PI3K signaling, and others — hybrid capture NGS comprehensive genomic profiling should be used routinely as a primary methodology for precision‐focused tumor assessment and targeted treatment in patients with advanced ovarian cancer and other gynecological malignancies:

1) Strongly agree

2) Agree

3) Moderately agree

4) Agree somewhat

5) Disagree




ESMO Asia 2016

An Oncologist’s Bid to Personalise Patient Care with

Genomic Profiling

Dr Wong Seng WengMedical Director & Consultant Medical Oncologist

The Cancer CentreSingapore Medical Group

Paragon Medical & Mt Elizabeth Novena Specialist CentreVisiting Consultant

Mt Elizabeth Hospital & Mt Elizabeth Novena HospitalAdjunct Clinician Scientist, Institute of Bioengineering and Nanotechnology,

Agency for Science, Technology and Research (A*STAR)

148

Notes:

Notes:

Comprehensive Genomic Profiling for Gastrointestinal Cancers

The Foundational Role of Mutation‐Based Molecular Targets to Optimize Cancer Management


HonorariaAstra Zeneca

Bayer Schering Pharma

Bristol‐Myers Squibb

Eisai

Eli Lilly

Hospira

Merck Serono

Merck Sharp & Dohme (MSD)

Mundipharma

Novartis

Orient Europharma

Pfizer

Roche

Advisory BoardsAstra Zeneca

Bayer Schering Pharma

Bristol‐Myers Squibb

Eli Lilly

Hospira

Merck Serono

Merck Sharp & Dohme (MSD)

Novartis

Orient Europharma

Pfizer

Roche

149

Notes:

Notes:

What Oncologists Want…

150

Notes:

Notes:


Patient


Patient

Family

151

Notes:

Notes:


• Pick therapy destined to work

Patient

Family



• Drop therapies destined to fail

Patient

Family

152

Notes:

Notes:



• Proven therapies


Patient

Family




• Investigational therapies


Patient

Family

153

Notes:

Notes:




• Investigational therapies


Patient

• PickupfamilialcancersyndromesFamily

So Many Tools…

Mikail et al, Cancer Lett., 2016; 374(2): 187-91.

154

Notes:

Notes:

So Many Genes…The Cancer Genome Atlas (TCGA)

So Many Targets…

155

Notes:

Notes:

The Cancer Genome Atlas (TCGA)

The Cancer Genome Atlas (TCGA)

156

Notes:

Notes:

Upfront Molecular Testing in Advanced GI Cancers

Lights, Camera, Action…

S. Mikhail, et al. Oncotarget. 2015;6:22206‐13.

89% (50/56) with at least 1 actionable mutation.

Prevalence

Cell‐cycle abnormalities: 58%

HER2 amplification: 30%

PIK3CAmutations: 14%

MCL1 amplification: 11%

PTEN loss: 9%

MET amplification: 5%

Picking the Winners…Proven Therapies…Is It Time to Drop IHC, FISH?

157

Notes:

Notes:

Picking the Winners…Proven Therapies…Is It Time to Drop IHC, FISH?

66% (12/18) HER2+ by IHC/FISH showed amplification by NGS.

92% (12/13) HER2 amplification by NGS were HER2+ by IHC/FISH.

S. Mikhail, et al. Oncotarget. 2015;6:22206-13.

Experience from MD Anderson

Total cohort: 2000

GI cancers: 19%

F. Meric-Bernstam, et al. J. Clin. Oncol. 2015;33:2753-62.

Therapy Pancreas Colorectal Gastroeso

W KRAS 79% 67% 16%

W/O KRAS 16% 31% 11%

Picking the Winners…Investigational Therapies…

Is There Always Action after the Lights and Camera?

158

Notes:

Notes:


Total cohort: 2000

GI cancers: 19%

39% (789) with at least 1 actionable mutation

Number enrolled in genotype‐matched trials:__________

F. Meric‐Bernstam, et al. J. Clin. Oncol. 2015;33:2753‐62.




Total cohort: 2000

GI cancers: 19%


Number enrolled in genotype‐matched trials:__________

Poll:1) 10‐20%

2) 20‐50%

3) 50‐80%

4) 80‐100%

F. Meric‐Bernstam, et al. J. Clin. Oncol. 2015;33:2753‐62.



159

Notes:

Notes:


Total cohort: 2000

GI cancers: 19%


Number enrolled in genotype‐matched trials:

83 patients

11% of those with actionable mutations

4% of cohort

F. Meric-Bernstam, et al. J. Clin. Oncol. 2015;33:2753-62.




Total cohort: 2000

Number enrolled in genotype‐matched trials: 83 patients

11% of those with actionable mutations

4% of cohort

Reasons cited: Patient preference

Poor PS (median delay 26 days)

Lack of trials/trial slots

Trial ineligibility

Insurance denialF. Meric‐Bernstam, et al. J. Clin. Oncol. 2015;33:2753‐62.



160

Notes:

Notes:

Experience from France (SHIVA trial)

8‐centres phase II trial

195 patients (actionable mutations by NGS with available targeted therapies) – 17% with GI cancers

99 in experimental arm (targeted therapy)

96 in control arm (investigators’ choice of conventional therapy)

Median PFS

Experimental arm:_____

Control arm:______

C. Le Tourneau, et al. Lancet Oncol. 2015;16:1324‐34


Is There Always an Oscar After the Action?

Experience from France (SHIVA trial)

8‐centres phase II trial

195 patients (actionable mutations by NGS with available targeted therapies) – 17% with GI cancers

• 99 in experimental arm (targeted therapy)

• 96 in control arm (investigators’ choice of conventional therapy)

Median PFS• Experimental arm: 2.3 months

• Control arm: 2.0 months (HR: 0.88, p=0.41)

• Grade 3/4 toxicity: No difference

C. Le Tourneau, et al. Lancet Oncol. 2015;16:1324‐34


Is There Always an Oscar After the Action?

161

Notes:

Notes:

One man’s experience from Singapore

68‐year‐old Chinese lady with advanced pancreatic cancer

Peritoneal metastases

PS: 2

Treatment:

• Nab‐paclitaxel/gemcitabine: PR

• mFOLFOX6: SD

• Irinotecan: PD





162

Notes:

Notes:

Is There Hope?


50‐year‐old Chinese gentleman with stage III colon cancer

K/N‐RAS wild type

MSI: low

Treatment:

Adjuvant XELOX

Peritoneal metastases 2 months post adjuvant

FOLFIRI/cetuximab: PD

Regorafenib: PD

mFOLFOX/bevacizumab: PD

Is There Hope?

163

Notes:

Notes:

VemurafenibMonotherapy: Not Effective in BRAFmCRC

Corcoran et al, Cancer Discov. 2012; Montero‐Conde et al, Cancer Discov. 2012; Prahallad et al, Nature 2012.

RAS

BRAF

CRAF

MEK

ERK

EGFR

PROLIFERATION & SURVIVAL

NODRUG

‐100

‐75

‐50

‐25

0

25

50

75

100

%Chan

ge From Baselin

e

(Sum of Lesion Size)

5% Response Rate

Kopetz et al, J Clin Oncol, 2010.

‐100

‐75

‐50

‐25

0

25

50

75

100

%Chan

ge From Baselin

e

(Sum of Lesion Size)

MEK116833 Phase 1/2 Study Design

Dabrafenib+Panitumumab

D 150 mg BID P 6 mg/kg Q2W N = 20

Dabrafenib+Panitumumab+ Trametinib

D 150 mg BID P 6 mg/kg Q2WT 2 mg QDN = 35 total; N = 24 RP2R

Panitumumab+ Trametinib

EGFR AcquiredResistance

P + T

N = 12/20

N = 2/20

P 6mg/kg Q2WT 2mg QD

N = 5 N = 1

March 16, 2015 Data Cut

164

Notes:

Notes:

Best Response With Confirmation Percent Change from Baseline at Maximum Reduction in Tumor Measurement

• D+P (N = 20)• CR+PR: 2 (10%)• Stable disease: 16 (80%)

• D+P+T (N = 35) • CR+PR: 9 (26%) • Stable disease: 21 (60%)

Color: confirmed responseHeight of bar: best unconfirmed response

‐80

‐60

‐40

‐20

0

20

40

60

80

100

‐100

‐80

‐60

‐40

‐20

0

20

40

60

80

100

‐100

*Maximum reduction from baseline is 0%+RP2R cohort

+

++

+ + + + + + + + + + + + + + + + + + + + +*

Maxim

um % Chan

ge from Baseline

*Maximum reduction from baseline is 0%

Progressive diseaseStable diseasePartial responseComplete response

Maxim

um % Chan

ge from Baseline

* *

Duration on Study

• D+P (N = 20)• > 6 months: 5 (25%)

• D+P+T (N = 35)• > 6 months: 9 (26%) • > 1 year: 4 (11%)

87654321 9 10 11 12 13 14 15 16 17 180


First responseDisease ProgressedCrossover


First responseDisease Progressed

Ongoing

Treatment Duration (Months)

Median Duration of Response: 5.4 mos (2.7, not available)

165

Notes:

Notes:

Is There Hope?


50‐year‐old Chinese gentleman with stage III colon cancer

• K/N‐RAS wild type

• MSI: low

Treatment:

• Adjuvant XELOX

• Peritoneal metastases 2 months post adjuvant

• FOLFIRI/cetuximab: PD

• Regorafenib: PD

• mFOLFOX/bevacizumab: PD

• Dabrafenib/Panitumumab/Trametinib: PR

• PFS: 6 months

Dropping the Losers…

Resistance to anti‐EGFR monoclonal antibodies in mCRC

KRAS, NRAS exons 2, 3, 4

BRAF

PIK3CA

PTEN loss

MET amplification

High Resolution Melting

KRAS (codons 12 & 13)• Direct sequencing: 45%

• HRM: 60%

• Resistant mutation (inclusive of BRAF, PIK3CA, PTEN) detected in 87% of non‐responders

J.G. Guedes, et al. BMC Cancer. 2013;13:169

166

Notes:

Notes:

Dropping the Losers…

Resistance to Trastuzumab in advanced gastroesophageal cancers

MET amplification

PTEN loss

A.K. Paulson, et al. Mol. Cancer Res. 2013;11:1112‐21

X. Zhang, et al. Oncology. 2015; 88: 76‐85

Colorectal cancer

Familial CRC syndromes: 5%

Familial Adenomatous Polyposis (FAP): APC gene mutation

Polyposis with MUTYH gene mutation

Hereditary Nonpolyposis CRC: MLH1, MSH2, MSH6, PMS2

Familial component: 30%

NGS vs Sanger sequencing

Miss‐rate: 4%

Homopolymeric DNA sequences

M. Simbolo, et al. Heredit. Cancer Clin. Pract. 2015;13:18

We Are Family…

167

Notes:

Notes:

We Are Family…

Gastric cancerHereditary diffuse gastric cancer: CDH1mutation

Other hereditary cancer syndromes: BRCA2

S. Mikhail, et al. Oncotarget. 2015;6:22206‐13.



Patients with GI Malignancies

168

Notes:

Notes:

Based on our evolving understanding of molecular markers and genomic alterations in GI malignancies, hybrid capture NGS comprehensive genomic profiling should be used routinely as a primary methodology for precision‐focused tumor assessment and targeted treatment in patients with advanced GI cancers.

1) Strongly agree

2) Agree

3) Moderately agree

4) Agree somewhat

5) Disagree




Documents

Comprehensive Genomic Profiling to Optimize Precision‐Focused Cancer Managementclinicalwebcasts.com/slidecasts/2017/Singapore-SlideCAST-286.pdf · 1 Notes: Notes: Comprehensive