Slide 1. Slide 2. Slide 3. Conflict of Interest. The Role of Pathology/Molecular Diagnostics in Personalized Medicine. NSCLC Landscape Change

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1 Slide 1 The Role of Pathology/Molecular Diagnostics in Personalized Medicine Ignacio I. Wistuba, M.D. Jay and Lori Eissenberg Professor in Lung Cancer Director of the Thoracic Molecular Pathology Lab Departments of Pathology and Thoracic/Head & Neck Medical Oncology M. D. Anderson Cancer Center Slide 2 Conflict of Interest Honoraria: Sanofi Aventis, Johnson & Johnson, Genentech, Champions Inc., Roche, AstraZeneca, and Bristol-Myers Squibbs Research Agreements: Genentech, Pfizer, AstraZeneca, Myriad, Eli-Lilly, and Merck. Slide 3 NSCLC Landscape Change Traditional Adenocarcinoma AKT BRAF VEGFR ALK HER2 EPHA/B PDGFR FGFR Unknown INSR Squamous Large Cell Adenocarcinoma EGFR PI3K MAPK KRAS Squamous Cell Ca FGFR1 Amp EGFRvIII Unknown PI3KCA EGFR TK DDR2

2 Maximum Change in Tumor Size (%) Probability of progression-free survival Probability of progression-free survival Slide 4 Lung Cancer Targeted Therapy Landscape Change Histology - Non-squamous 60% Bevacizumab Pemetrexed Adenocarcinoma - EGFR mutation 10% Erlotonib/Gefitinib - ALK-EML4 fusion 3% Crizotinib - MET amplification 20% - PI3KCA mutation 5% - HER2 mutation 1% Squamous Cell Carcinoma - FGFR1 amplification 22% FGFR TKIs - EGFRvIII mutation 5% EGFR TKIs - PI3KCA mutation 4% PI3KCA inhibitors - DDR2 mutation 3% Dasatinib & Nilotinib Slide 5 EGFR Mutations in NSCLC P- loop Extracellular domain C- helix ATP binding N-lobe cleft TK C-lobe Domain Regulatory A- loop domain Deletions - 46% Duplications/ Insertions - 9% L858R - 39% 1.0 IPASS Trial EGFR mut ( + ) EGFR Mut ( - ) Gefitinib (n=132) Carboplatin/Paclitaxel (n=129) 0.8 Gefitinib (n=91) Carboplatin/Paclitaxel (n=85) HR = 0.48 P< HR = 2.85 P< Months Treatment by subgroup interaction test, p< Months Mok TS et al. N Engl J Med 2009;361: Slide 6 EML4-ALK in Lung Adenocarcinoma 2p23 region Histology FISH Protein (IHC) ALK EML Crizotinib in EML4-ALK (+) Progressive disease Partial response Stable disease Complete response 30% ORR: 57% DCR at 8 weeks: 87% Kwak EL et al. N Engl J Med 2010;363:

3 Progression-Free Survival Progression-Free Survival Slide 7 Lung Adenocarcinoma and NSCLC What is new in 2011? All KRAS mutations are not the same Mutations data of a panel of genes (multiplex analysis) are available Gene signatures associated to EGFR TKI response in EGFR wild-type tumors Mechanisms of EGFR TKI resistance Slide 8 KRAS Mutations in Lung Adenocarcinoma Lodish et al Wild Type Codon 12 Codon 13 Base change 1 G 2 G 3 T 1 G 2 G 3 C Amino Acid (replacing Gly) G T (72%) 1 Cys (45%) 1 Cys (5%) 2 Val (20%) G A (14%) 2 Asp (12%) 2 Asp (1%) G C (14%) 2 Ala (9%) T C (2%) 3 Cys (2%) KRAS Mutation Sequencing Codon 12 (G12C) Codon 13 (G13A) G G T G G C T G T G G C G G T G A C Slide 9 BATTLE Trial Novel Findings: Not All KRAS Mutations Are the Same All treatments Cys/Val n=24 Other n=19 Wild n=172 Gene Expression Analysis mut-kras C or V other 0.4 P = Months since randomization Sorafenib Cys/Val n=11 Other n=9 Wild n=66 P = Months since randomization N. Ihle, G. Powis, et al, AACR 2011

4 Slide 10 BATTLE Trial Novel Findings: Not All KRAS Mutations Are the Same Mut-KRAS C or V other RPPA Analysis NSCLC Cell Lines wt-kras K-RAS Akt RalGDS Mek p70s6k mut-kras-g12d mut-kras-g12c K-Ras Akt Mek p70s6k Akt K-RAS RalGDS Mek p70s6k N. Ihle, G. Powis, et al, AACR 2011 Slide 11 Lung Cancer Mutation Consortium GO Grant Panel 1,000 Adenocarcinomas Mutations (8 genes/115 Assays) AKT1 BRAF EGFR HER2 KRAS MEK1 NRAS PIK3CA FISH C-MET amplification EML4-LK fusion Mutation 294 July, ,234 Consented 1,063 Studied Pending FISH 82 B. Johnsons and the LCMC co-investigators, WCLC 2011 Slide 12 Types of Histology and Cytology Specimens Surgical Resection Advanced Tumor Endobronchial Ultrasound (EBUS) or Pleural Fluid Histology Core Needle Biopsy (CNB) Alcohol-fixed Fine Needle Aspiration (FNA) Alcohol-fixed Cell Block Formalin-fixed and Paraffin-embedded (FFPE) Alcohol-fixed

5 Slide 13 Multiplexed Mutation Assays Tumor Tissue Multiplex PCR Resected Specimen Core Biopsy SNaPshot (Applied Biosystem) Mass ARRAY SNP - Sequenom, Inc Dias-Santagata, EMBO Mol Med 2:146, % Sensitivity and ~20ng DNA/multiplex reaction Slide 14 Lung Cancer Mutation Consortium Incidence of Mutations Detected AKT1 NRAS MEK1 MET AMP HER 2 PIK3CA 2% BRAF 2% NO MUTATION DETECTED EML4-ALK 9% EGFR 18% KRAS 23% Mutation found in 54% (280/516) of tumors completely tested B. Johnson. P. Bunn (PI) and the LCMC co-investigators, WCLC 2011 Slide 15 Mutation Analysis by MassARRAY Sequenom - NSCLC Wild-type BRAF (G469-G1406) Mutant (Homozygous) Data Analysis Well Spectrum BRAF (G464-G1391) Wild-type Mutant (Heterozygous) H. Erickson, E. Kim, and I. Wistuba, 2011

6 Slide 16 BATTLE-1 Clinical Trial Platform for future research Clinical trial program (Phase II) Novel trial design Biopsy-mandated study in lung cancer Biomarker discovery Accrual (3 yrs for accrual; Nov 2006 to Oct 2009) Biopsies obtained 324 Patients randomized 255 Patients evaluable 244 Molecular Profiling Frozen tumor: mrna Affymetrix & proteomic (RPPA) Serum and PBMCs Kim et al, Cancer Discovery, April 2011 Slide 17 Erlotinib Personalized Therapy in Advanced NSCLC: BATTLE-1 Schema Vandetanib Patient Enrollment EGFR VEGF Core Biopsy KRAS/BRAF RXR/CyclinD1 Randomization: Equal Adaptive Erlotinib + Bexarotene Primary end point: 8 week Disease Control (DC) Biomarker Profile Sorafenib E. Kim et al, Cancer Discovery 2011 Slide 18 The BATTLE-1 Gene Expression Signatures Scorecard Signature Derived Validation Predictive? Pathway Signatures EGFR KRAS 3 Clinical sets 2 Clinical sets 3 Clinical sets 1 Cell line set 1 Clinical set 1 Cell line set Yes: EGFR mutations Yes: outcome in resected NSCLC with wt EGFR (prognostic) No: erlotinib response in wt EGFR patients Yes: KRAS mutations in BATTLE No: erlotinib response in wt EGFR patients EMT Cell lines 2 Clinical sets Yes: erlotinib DC in wt EGFR Clinical signatures 5 gene WEE BATTLE Cell lines Yes: erlotinib DC in wt EGFR patients Heymach, Saintigny, Byers, Kim, et al, AACR 2011

7 8wDC (%) Probability of survival Signature value Slide 19 5-Gene Signature Predicts 8-wk DC in EGFR Wild-type Tumors BATTLE-1 mrna Profiling (n=139) 8wDC: Yes 8wDC: No NPR3 C5orf23 P<0.001 LCN2 OGG1 TRIM72 P<0.001 P=ns Signature + Signature - Test for interaction P=0.023 Erlotinib Sorafenib arms arm 8wDC 8wDC No Yes Signature - Signature + Log-rank <0.001 HR= CI P=0.001 Median PFS: 12.5 weeks vs. PFS time (months) 7.2 weeks Saintigny et al, AACR 2011 Slide 20 Fig. 1 The frequency of observed drug resistance mechanisms. Mechanisms of Resistance to EGFR TKI Novel Mechanisms T790M Mutation 49% MET amplification 5% PI3KCA Mutation - 5% EMT Changes 5% SCLC Features 14% Unknown 30% Sequist L V et al. Sci Transl Med 2011;3:75ra26-75ra26 Slide 21 Mechanisms of Resistance to EGFR TKI Adenocarcinoma SCLC H&E Synaptophysin H&E Synaptophysin Sequist L V et al. Sci Transl Med 2011;3:75ra26-75ra26

8 Slide 22 Squamous Cell Lung Carcinoma Landscape Change Traditional 2011 Squamous Large Cell Adenocarcinoma Unknown FGFR1 Amp EGFRvIII PI3KCA EGFR TK DDR2 Slide 23 New Target Therapy in Squamous Cell Carcinoma of the Lung Gen Frequency Drug FGFR1 amplification 22% FGFR TKIs EGFRvIII mutation 5% EGFR TKIs PI3KCA mutation 3.6% PI3KCA inhib. EGFR TK mutation 3.4% EGFR TKIs DDR2 mutation 3.2% Dasatanib Nilotinib Okashi and Pao, Cancer Discovery, April 2011 Slide 24 FGFR1 Amplification in Squamous Cell Carcinoma (9%) Weiss J et al. Sci Transl Med 2010;2:62ra93-62ra93

9 Frequency (%) Slide 25 FGFR1 Copy Number Gain (CNG) Analysis by FISH in NSCLC (n=326) Adenocarcinoma (n=217) Squamous Cell (n=89) 20% 17% 13% 11% 7% 1% 4 10 Amplification FGFR1 CNG Tang et al, 2011 Slide 26 FGFR1 Copy Number Analysis by FISH in NSCLC 10 Copies (SCC) Amplification (SCC) 10 Copies (ADCA) 10 Copies (ADCA) Tang et al, 2011 Slide 27 DDR2 Gene Mutations in Squamous Cell Carcinoma of the Lung (3.2%) Hammerman et al, Cancer Discovery April, 2011

10 Slide 28 DDR2 Mutant Tumor Sensitive to Dasatinib Hammerman et al, Cancer Discovery April, 2011 Slide 29 BRAF Inactivating Mutation Associate Sensitive to Dasatinib Tumor BRAF Y472C Mutation B. Sen, and F. Johnson et al, unpublished, 2011 Slide 30 Tissue is the Emperor - For diagnosis, the pathologist needs some! Advanced Tumor Core Needle Biopsy (CNB) Fine Needle Aspiration (FNA) What s the problem? I gave you at least 10 cells!

11 % Reads Mapped WT Seq T/N log Scatterplot: TN IW array vs. TN IW RNAseq (Casewise MD deletion) TN IW RNAseq = * TN IW array Correlation: r = TN IW array 95% confidence Slide 31 Pathology Algorithm of Small Tissue Specimens for Management of Lung Cancer Patients SCLC NSCLC NOS EML4-ALK EGFR FGFR1 Amp DDR2 Mut Panel: MET ampl PI3KCA BRAF HER2 K-, N-, H-RAS MEK AKT NSCLC NOS? IHC: TTF-1 CK 5/7 P63 Small Biopsy Adenocarcinoma Squamous Cell Ca Others EML4-ALK EGFR Panel: MET ampl PI3KCA BRFA HER2 K-, N-, H- RAS MEK AKT FGFR1 Amp DDR2 Mut Panel: PI3KCA BRAF HER2 K-, N-, H-RAS MEK AKT Slide 32 Evolution of Genome Sequencing Technology 1986: Sequencing one genome: Cost = $3 billion Time = 1 decade 2010: Sequencing one genome: Costs = $10 thousand Time = 3 weeks 2012: Sequencing one genome: Cost = $1 thousand Time = 1 week Slide 33 Next Generation of Sequencing NSCLC Core Needle Biopsies (CNB) Frozen CNB: NSCLC 1mm Exome Seq (DNA) Whole Transcriptome (WT-mRNA) Small RNA Seq (mirna) Percentage of WT Reads Mapped: 10 CNB vs. 10 Resected NSCLCs Correlation of WT Seq and mrna Array Profiling of 11 NSCLCs r=0.48 P=10-8 TN IW RNAseq CNB Resected Microarray T/N log2 Wistuba et al, unpublished, 2011

12 Slide 34 Molecular Pathology of Lung Cancer: 2011 New actionable genetic abnormalities continued to be discovered in NSCLC In lung adenocarcinoma and NSCLC: All KRAS mutations are not the same ~50% of tumors have actionable gene mutations Gene expression signatures predict response to EGFR TKI in EGFR wild-type tumors Novel mechanisms and changes associated to EGFR TKI resistance Squamous cell carcinoma shows distinct genetic abnormalities: FGFR1 amp and DDR2 mutations Next generation sequencing shows a promise for application to clinical settings Slide 35 Acknowledgements MD Anderson Cancer Center Thoracic Molecular Pathology Lab Heidi Erickson Hector Galindo Nana Hanson Christina McDowell Annette Basey Chi-Wan Chow Zuoming Chu Junya Fujimoto Lakshmi Kakarala MD Anderson Cancer Center Edward Kim (Medical Oncology) Waun Ki Hong (Medical Oncology) Roy Herbst (Medical Oncology) John Heymach (Medical Oncology) Scott Lippman (Medical Oncology) Gordon Mills (System Biology) Katherine Stemke-Hale (System Biology) Cesar Moran (Pathology) Neda Kalhor (Pathology) Jack Lee (Biostatistics) Support US Department of Defense BATTLE and PROSPECT, Stading Family, Cohen- Reinauch BATTLE-2 Fund and V Foundation