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Genomic Strategies to Cancer Biology and Cancer Therapy

Genomic Strategies to Cancer Biology and Cancer Therapy. Joseph Nevins Duke Institute for Genome Science and Policy. Transitions in Biology. Observational science. Molecular science. Genomic (data) science. Concept of a Signature. State A State B. Gene expression analysis.

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Genomic Strategies to Cancer Biology and Cancer Therapy

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  1. Genomic Strategies to Cancer Biology and Cancer Therapy Joseph Nevins Duke Institute for Genome Science and Policy

  2. Transitions in Biology Observational science Molecular science Genomic (data) science

  3. Concept of a Signature State A State B Gene expression analysis

  4. Gene Expression Profiles As Surrogates for Biological Phenotypes

  5. Gene Expression Profiles As Surrogates for Biological Phenotypes Gene expression profiles as a common currency for in vitro and in vivo phenotypes

  6. Addressing the Complexity of Cancer

  7. The Challenge of Personalized Cancer Treatment • How to improve prognosis to identify the patients in need of further treatment? • How to identify more effective therapeutic opportunities tailored to the individual patient? Who to treat? How to treat?

  8. Improved Prognosis Using Genomic Signatures Use to refine clinical prognosis But - how to find an opportunity to actually use the refinement

  9. Early Stage NSCLC Treatment Protocol Stage 1a: Observation Stage 1b-3: Adjuvant Therapy Diagnosis Tumor is resected and measured Yet, 25% of Stage 1A patients will recur and die - how to identify these individuals?

  10. A Genomic Predictor of Recurrence Low Risk High Risk Predicted High Risk Probability of Recurrence Predicted Low Risk

  11. Validation of the Genomic Recurrence Predictor CALGB samples Accuracy: 79%

  12. An Opportunity to Improve Prognosis in Lung Cancer

  13. An Opportunity to Improve Prognosis in Lung Cancer

  14. Standard-of-Care • Cisplatin/vinorelbine • Cisplatin/gemcitabine • Cisplatin/docetaxel • Carboplatin/paclitaxel Only a fraction of patients will respond The rest are treated ineffectively How to choose the right therapy for the individual patient?

  15. Herceptin - The Importance of Patient Selection All Breast Cancer Patients Her2+ Breast Cancer Patients Herceptin Herceptin < 10% Response 35-50% Response Can we do the same for commonly used chemotherapies?

  16. A Strategy to Predict Response to Cytotoxic Chemotherapies NCI-60 Cell Panel Drug response data Affymetrix expression data • Identify resistant and sensitive cells • Build expression predictor of response Resistant Sensitive

  17. A Panel of Predictors for Cytotoxic Chemotherapies Docetaxel Topotecan Adriamycin 5-FU Taxol Cytoxan

  18. Predicting Patient Response to Cytotoxic Chemotherapies Paclitaxel Topotecan Adriamycin Probability

  19. Patterns of Predicted Sensitivity to Cytotoxic Chemotherapies Predict drug sensitivity in tumors Etoposide Paclitaxel 5-FU Adriamycin Topotecan Cytoxan Docetaxel Distinct patients sensitive to etoposide and paclitaxel

  20. An Opportunity to Guide Therapy Random Selection A or B Outcome Standard of Care (A or B) Genomics-Guided A or B Outcome Cisplatin/gemcitabine Cisplatin/docetaxel A B Beyond standard of care - how to direct targeted agents?

  21. Signaling Pathways Underlying the Oncogenic Phenotype

  22. Predicting Pathway Status in Tumors Ras Myc E2F Src b-Cat

  23. Predicting Pathway Status in Tumors Ras Myc E2F Src b-Cat Emphasizes the heterogeneity of the disease and therapeutic challenge

  24. A Profile for an Individual Patient Can we use the profile for an individual patient?

  25. SU6656 FTS

  26. Mapping Pathway Status to Cancer Cell Lines Ras Myc E2F Src b-Cat Compare with drug sensitivity

  27. Pathway Signatures Predict Therapeutic Response

  28. SU6656 FTS Roscovitine LY294002 Hypothemycin Rapamycin

  29. Tumor Progression Vogelstein and Fearon Metastatic Carcinoma Normal Colon Adenoma Late Adenoma Carcinoma APC 5q loss -catenin K-Ras 18q loss p53 17p loss 8p loss

  30. Another View of Tumor Progression Premalignant Nevi Primary Melanoma Metastatic Melanoma Normal Skin Benign Nevi

  31. Another View of Tumor Progression Premalignant Nevi Primary Melanoma Metastatic Melanoma Normal Skin Benign Nevi

  32. Another View of Tumor Progression Premalignant Nevi Primary Melanoma Metastatic Melanoma Normal Skin Benign Nevi

  33. Another View of Tumor Progression Premalignant Nevi Primary Melanoma Metastatic Melanoma Normal Skin Benign Nevi

  34. Another View of Tumor Progression Premalignant Nevi Primary Melanoma Metastatic Melanoma Normal Skin Benign Nevi

  35. Another View of Tumor Progression Premalignant Nevi Primary Melanoma Metastatic Melanoma Normal Skin Benign Nevi Further emphasis of the heterogeneity of the disease and therapeutic challenge

  36. The Present…

  37. The Future…

  38. The Future… Etoposide Paclitaxel 5-FU Adriamycin Topotecan Cytoxan Docetaxel

  39. Anil Potti Andrea Bild Jennifer Freedman Seiichi Mori Jeffrey Chang Mike West Holly Dressman David Harpole Phillip Febbo Geoffrey Ginsburg Mike Kelley Sayan Mukherjee Kelly Marcom John Olson Jeffrey Marks

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