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David Jablons, M.D. Professor and Chief, Section of General Thoracic Surgery

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David Jablons, M.D. Professor and Chief, Section of General Thoracic Surgery

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  1. Please note, these are the actual video-recorded proceedings from the live CME event and may include the use of trade names and other raw, unedited content. Select slides from the original presentation are omitted where Research To Practice was unable to obtain permission from the publication source and/or author. Links to view the actual reference materials have been provided for your use in place of any omitted slides.

  2. Large-Scale International Validation of a qPCR-Based Genetic Assay Prognostic of Survival in Resected Non-Squamous Cell NSCLC David Jablons, M.D. Professor and Chief, Section of General Thoracic Surgery Ada Distinguished Professor and Program Leader Thoracic Oncology LaboratoryHelen Diller Family Comprehensive Cancer Center University of California, San Francisco

  3. A practical genomic prognostic assay Measure expression of 14 cancer pathways + reference genes (CLIA-certified Laboratory) 361 stage I-IV non-squamous FFPE samples (UCSF Training Cohort)

  4. A practical genomic prognostic assay Measure expression of 14 cancer pathways + reference genes (CLIA-certified Laboratory) L2-penalized Cox Proportional Hazards Modeling 361 stage I-IV non-squamous FFPE samples (UCSF Training Cohort) Prognostic Algorithm

  5. A practical genomic prognostic assay Measure expression of 14 cancer pathways + reference genes (CLIA-certified Laboratory) L2-penalized Cox Proportional Hazards Modeling 361 stage I-IV non-squamous FFPE samples (UCSF Training Cohort) Prognostic Algorithm Analytical Assay Validation (CLIA-certified Laboratory)

  6. A practical genomic prognostic assay Measure expression of 14 cancer pathways + reference genes (CLIA-certified Laboratory) L2-penalized Cox Proportional Hazards Modeling 361 stage I-IV non-squamous FFPE samples (UCSF Training Cohort) Prognostic Algorithm Kaiser Northern California 433 stage I Analytical Assay Validation (CLIA-certified Laboratory) Independent Validation China Clinical Trials Consortium 1006 stage I-III

  7. A practical genomic prognostic assay Measure expression of 14 cancer pathways + reference genes (CLIA-certified Laboratory) L2-penalized Cox Proportional Hazards Modeling 361 stage I-IV non-squamous FFPE samples (UCSF Training Cohort) paraffin-tissues Prognostic Algorithm Kaiser Northern California 433 stage I Analytical Assay Validation (CLIA-certified Laboratory) Independent Validation China Clinical Trials Consortium 1006 stage I-III

  8. A practical genomic prognostic assay Measure expression of 14 cancer pathways + reference genes (CLIA-certified Laboratory) L2-penalized Cox Proportional Hazards Modeling 361 stage I-IV non-squamous FFPE samples (UCSF Training Cohort) paraffin-tissues qPCR Prognostic Algorithm Kaiser Northern California 433 stage I Analytical Assay Validation (CLIA-certified Laboratory) Independent Validation China Clinical Trials Consortium 1006 stage I-III

  9. A practical genomic prognostic assay Measure expression of 14 cancer pathways + reference genes (CLIA-certified Laboratory) L2-penalized Cox Proportional Hazards Modeling 361 stage I-IV non-squamous FFPE samples (UCSF Training Cohort) paraffin-tissues qPCR Prognostic Algorithm Kaiser Northern California 433 stage I blinded Analytical Assay Validation (CLIA-certified Laboratory) Independent Validation China Clinical Trials Consortium 1006 stage I-III

  10. Study Cohorts (n=1800)

  11. Algorithm Development – UCSF Cohort Overall survival (%): 80% versus 35%, based on 14 cancer-related oncogenes

  12. Blinded Assay Validation Kaiser Cohort (n = 420) China Cohort (n = 967) Overall Survival 75% versus 48% 80% versus 45%

  13. Stage Independence (China) • Stage I disease (low risk = 83.0% [73.8–89.1]; intermediate risk = 67.7% [54.8–77.7]; high risk = 64.6% [57.9–70.5]) • Stage II disease (low risk = 54.2% [30.1–73.2]; intermediate risk = 45.8% [26.2–63.4]; high risk = 38.1% [29.4–46.8]) • Stage III disease (low risk = 53.3% [32.6–70.3]; intermediate risk = 43.3% [27.2–58.5]; high risk = 24.0% [17.5–30.9])

  14. Multivariate Models Kaiser cohort (n = 420) China cohort (n = 967)

  15. China stage I-IIA (n=540) New TNMM Staging

  16. Conventional Staging • No data support the use of adjuvant treatment in patients with stage IA tumors as defined by conventional criteria • Use of such treatment in patients with stage IB disease is lent support by only controversial evidence

  17. New TNMM Staging The addition of the molecular assay gave better risk discrimination than did NCCN risk criteria alone

  18. Genetic Assay Outperforms Conventional Methods • The molecular assay was the strongest predictor of 5 year mortality compared with standard criteria (sex, age, smoking status, etc) • Outperformed the NCCN guidelines used to identify high-risk patients with stage I disease

  19. Conclusions • There is a clear need to improve NSCLC staging • A robust, practical assay prognostic of survival after resection has been developed using qPCR and paraffin-tissues • This multi-gene assay has been independently validated in two large international cohorts • The multi-gene assay can outperform conventional risk factors / staging and may lead to personalized therapies for patients with early stage non-squamous NSCLC

  20. Thank you • UCSF Thoracic Oncology Laboratory David JablonsMichael Mann Patrick Pham Mike Mulvihill Marc Segal Roshni Ray Kirk Jones Dan Raz Zhidong Xu Thierry Jahan Biao He • Kaiser Northern California Stephen Van Den Eeden Charles Quesenberry Laurel Habel • China Clinical Trials Consortium Jianxing He Zhi-Hua Zhu Wen GaoHuanrong Zhang Bo SuQiuhua Deng Zongfei WangJiangfen Zhou Huiling LiMei-Chun Huang Che-Chung Yeh • Pinpoint Genomics David Berryman Jerry Hurst Fatemeh Zaiei

  21. Sunday, February 12, 2012Hollywood, Florida Co-Chairs Rogerio C Lilenbaum, MD Mark A Socinski, MD Co-Chair and Moderator Neil Love, MD Faculty Walter J Curran Jr, MD David Jablons, MD Mark G Kris, MD Suresh Ramalingam, MD Alan B Sandler, MD

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