William Pao, MD, PhD Professor of Medicine Director, Personalized Cancer Medicine Director, Division of Hematology/Oncol

1. Tumor-Genome-Directed Anti-Cancer Therapy: Using Lung Cancer and Melanoma as a ParadigmNCI Workshop on “Next-Generation DNA Sequencing as a Tool for Clinical Decision-making in Cancer Patient Management”May 4, 2012Bethesda, MD William Pao, MD, PhD Professor of Medicine Director, Personalized Cancer Medicine Director, Division of Hematology/Oncology Vanderbilt-Ingram Cancer Center Nashville, TN

2. Disclosure Information I have the following financial relationships to disclose: Patent licensed to MolecularMD for EGFR T790M testing (got total of $500.00 and no royalties) Consulting for MolecularMD, BMS, AstraZeneca, Symphony Evolution, Clovis Oncology Research funding from Xcovery, Enzon, AstraZeneca, Symphogen

3. Traditional View of Cancer Lung Cancer Melanoma Squamous Adeno- carcinoma Large Small

4. Oncogenic Driver Mutations Impact Anticancer Therapy in Humans Lung Cancer Melanoma IPASS NEJM ‘09 Ph II Trial PLX-4032 PASCO ‘09

5. Evolution of Knowledge About ‘Driver Mutations’ in Non-Small Cell Lung Cancer Pao and Girard ’11

6. Spectrum of ‘Driver Mutations’ in 202 East Asian Never Smokers with Lung Adenocarcinoma Li et al ‘11

7. Molecular Subsets  Progress

8. Goals of the VICC PCMI - 2009 • To establish ‘reflex’ testing of ‘common’ clinically relevant genetic alterations in lung cancers and melanomas • To develop a clinically-applicable high-throughput molecular genotyping facility for ‘rarer’ genetic variants • To develop bioinformatic algorithms to report genetic results in the electronic medical record in ways that are clinically useful for practicing oncologists • Collaboration among Depts of Medicine, Pathology, BioInformatics, and VICC

9. What Test? What Should Be in the Test? • Which platform? • SNaPshot (ABI 3730) vs new technology (Sequenom) • Ease of calls • High sensitivity • One panel for all cancers? Or tumor-specific panels? • Feasibility vs. wide-applicability • How often does one really find an ‘actionable’ mutation (e.g. EGFR kinase domain mutation in a melanoma)? • Which mutations? • Occurs in the cancer • Occurs with frequency >1% • Has relevance to existing or emerging targeted therapy

10. How to Implement? • Molecular diagnostics • Assays developed in Pao Lab as collaboration with CLIA-lab • Assays transferred to/re-validated by CLIA-lab • Bioinformatics • Monthly meetings among Bioinformatics, Pathology • Input from practicing clinicians • Pathology workflow • Re-organization/tissue librarian • Education • Consent • Lung – reflex • Melanoma – consent form

11. One Size Does Not Fit All:Melanoma/Lung Ca Molecular Profiling Results 7/1/10-12/31/11 Melanoma Panel: 538 Samples Lung Panel: 451 Samples Cindy Vnencak-Jones

12. First 150 Patients: 20% of BRAF V600 Mutations Would Be Missed by Allele-Specific PCR First 150 Patients: 20% of BRAF V600 Mutations Would Be Missed by Allele-Specific PCR Lovly, Dahlman, Fohn, Su et al‘12 Lovly, Dahlman, Fohn, Su et al‘12

13. First 150 Patients: 40% of Pts with Mutant Metastatic Disease  Genotype-Driven Treatment *This CTNNB1 mutation (CTNNB1 S45P) occurred concurrently with an NRAS Q61L mutation. Lovly, Dahlman, Fohn, Su et al‘12

14. Kinase Fusions in Human Cancers 43-350 222 GXGXXG GXGXXG GXGXXG GXGXXG 117 83 18-62 48-79 # amino acids to fusion GXGXXG GXGXXG GXGXXG 44-64 JAK2 70-201 GXGXXG ABL1 ROS1 NTRK1 BRAF PDGFR 56 GXGXXG Exon (-2) Exon (-1) Exon* ALK RET FGFR1 15-33 15 GXGXXG GXGXXG PDGFR NTRK3 intron (-3) intron (-2) intron (-1) *encodes GXGXXG motif Chmielecki et al ’10; Chmielecki et al ‘11

15. Using NGS to Detect Kinase Fusions Systematically Chmielecki et al ’10; Chmielecki et al ‘11

16. Novel C6orf204-PDGFRbeta Fusion in Pt with Recurrent T-ALL and MPN Chmielecki et al ’10; Chmielecki et al ‘11

17. Summary – Building a Sustainable Model • Impact in the clinic • Prioritize treatment options for existing targeted therapies • Impact on clinical trials • Accelerate accrual to trials with emerging targeted therapies • Enrich for cohorts of pts likely to benefit • Impact on translational science • Create opportunities from the bedside to bench and back • Initiate new projects

18. Goals of the VICC PCMI - 2009 • To establish ‘reflex’ testing of ‘common’ clinically relevant genetic alterations in lung cancers and melanomas • To develop a clinically-applicable high-throughput molecular genotyping facility for ‘rarer’ genetic variants • To develop bioinformatic algorithms to report genetic results in the electronic medical record in ways that are clinically useful for practicing oncologists • Collaboration among Depts of Medicine, Pathology, BioInformatics, and VICC

19. Knowledge Gap 94% of community oncologists responded that they discuss genetic mutation testing with their patient 17% of lung cancer patients were aware of genetic mutation testing 44% of oncology nurses did not discuss genetic mutation testing with patients, because they felt they lacked knowledge to discuss it

20. Old Method for Reporting Mutation Results in the Electronic Medical Record Old Method: • Report Template • Scanned into Electronic Health Record as image file (not computable) Challenges: • How to report > 40 mutations in 8 genes? • Whose role to curate knowledge regarding clinical significance? • Lack clinical trial information

21. New Method for Reporting Mutation Results in the EMR Mia Levy

22. My cancer genome

23. My cancer genome

24. My cancer genome

25. My cancer genome

26. My cancer genome

27. My cancer genome

28. My cancer genome 7 Cancers Lung Melanoma Breast Colon Thymic GIST Thyroid 22 Genes 203 Disease-Gene-Variant Relationships ~50,000 visits/>170,000 pageviews/ 119 countries/52 US territories in 1 year (only 8500 oncologists in US) Now ~1000 visits/week

29. My cancer genome Clinical trial search 36,167 Cancer Trials (PDQ) 135 Cancer Diagnoses 437 Cancer Genes (COSMIC)

30. My cancer genome Trial search results can be filtered by geographic location or trial phase

31. Consortium Science Contributors: 30 Informatics: 11 Knowledge Management Experts: 3

32. DIRECT – A Mutation Knowledgebase • DNA-mutation Inventory to Refine and Enhance Cancer Treatment • “COSMIC for clinicians” Horn et al PASCO ‘11

33. >100 Reported EGFR Mutations:How Does One Find Clinical Relevance of a Specific One? Riely et al ‘06

34. www.mycancergenome.org/DIRECT 1022 pts with EGFR mutation/ EGFR TKI-response data; 180 different GFR mutns Horn et al PASCO ‘11

35. Table 2: EGFR Mutations associated with disease control Paul Yeh, Leora Horn

36. Future Directions • DETECT – DNA Evaluation of Tumors for Enhanced Cancer Treatment • Breast ca, colon ca using SNaPshot • NGS on ‘pan-negative’ cases • Develop in-house next-gen panels • Partner with Foundation Medicine, MolecularMD • MyCancerGenome.org – Web-based decision support • Expand content; monthly updates • DIRECT – DNA-mutation Inventory to Refine and Enhance Cancer Treatment • We need a national effort: COSMIC for clinicians • MCG – Drug Compendium

37. Sanford Guide to AntiMicrobrial Therapy

38. MCG Guide to Anticancer Therapy

39. 2 Issues • DIRECT • Journals and/or the NCI should mandate that for genotype-directed clinical trials, ALL individual level patient data, including genotypes, MUST be reported in a public fashion! • FDA-mandated companion diagnostics vs multiplexed assays • Tissue • $ • Time • Lung cancer: EGFR, HER2, PIK3CA, ALK, ROS, RET, etc.

40. Acknowledgements • Pao Lab • Katie Hutchinson • Clinical Informatics • Mia Levy • Scott Sobecki • Jim Tibbetts • Stacy Cooreman • MikCantrell • Dario Giuse • Jonathan Grande • RuAnnSchleicher • UCLA • Toni Ribas • MGH • Dora Dias-Santagata • John Iafrate • Grant Support • Kleberg Foundation • Martell Foundation • Anonymous Foundation • NCI/SU2C-AACR Vanderbilt Ingram Cancer Center Jennifer Pietenpol Ashley Lamb Kim Dahlman Molecular Diagnostics Laboratory Cindy Vnencak-Jones Medical Oncology Christine Lovly Jeff Sosman Leora Horn Carlos Arteaga Pathology Sam Santoro Cheryl Coffin Bioinformatics Junfeng Xia Peilin Jia Zhongming Zhao Knowledge Management Christine Micheel Paul Yeh

41. Acknowledgements • Co-Editor-in-Chief: Mia Levy • Deputy Editor: Christine Lovly • Executive Editor: Christine Micheel • Editorial/Business: Paul Yeh, Ashley Lamb • Contributors:Rick Abramson, Carlos Arteaga, Alberto Bardelli, Justin M. Balko, Paul Bunn, Emily Chan, Haiquan Chen, Christopher Corless, Dan Costa, Allan Espinosa, Jim Fagin, Jill Gilbert, Nicolas Girard, Leora Horn, Vicki Keedy, Marc Ladanyi, Mia Levy, Roger Lo, Christine Lovly, Robert Maki, Ingrid Mayer, Geoff Oxnard, Paul Paik, William Pao, Gregory Riely, David Solit, Ben Solomon, Martin Sos, Jeff Sosman, Roman Thomas • Informatics: Mik Cantrell, Stacy Cooreman, Daniel Carbone, Vincent Gould,Nathan Johnson,Anna Belle Leiserson, Riyad Naser, Ross Oreto, Scott Sobecki, Jim Tibbetts, Mikhail Zemmel • Funding: Kleberg/Martell/Anonymous Foundations; BMS; GE • Awards/Grants: • HHS/Office for the National Coordinator for HIT (ONC) public data and cancer challenge to create health IT applications that use public data and existing technology to help patients and health care professionals prevent, detect, diagnose and treat cancer (Health 2.0) • GE HealthyImagination We welcome academic/industry/gov’t partnerships!