Reported by R5 李霖昆 Supervised by 楊慕華 大夫

1. Review article Genomics-Driven Oncology: Framework for an Emerging Paradigm Levi A. Garraway Reported by R5 李霖昆 Supervised by 楊慕華 大夫 Journal of Clinical Oncology 31, 15, 1806–1814, May 20th , 2013

2. Outline • Introduction • Principle and hypothesis of genomics-driven cancer medicine • Hypothesis testing • Question encountered • Conclusion

3. In 1973: • Masaharu Sakurai and Avery A. Sandburg • Karyotype abnomality - leukemia - prognosis • After 3 years: AML  minor or major karyotypic alteration • In mid 1980s: • Guide leukemia Tx • Clinical trial design: patient stratification • Cancer Gene (oncogen / tumor suppressor gene) • Comprise normal genes: derangement • Oncogenesis, tumor progression, response to Tx • Tumor virus

4. In 1985: • Somatic genetic derangement • Diagnostic and prognostic impact • Patient stratification • In 1990s and 2000s: • Trastuzumab, Imatinib • CRC, NSCLC, melanoma  New treatment paradigm

5. Outline • Introduction • Principle and hypothesis of genomics-driven cancer medicine • Hypothesis testing • Question encountered • Conclusion

6. During past decades • Tumor biology, genomics technology, computational innovation, drug discovery • Translational cancer research • Driver genetic alteration • Dysregulated protein: Cancer cells depend on • Targeted agents • Hypothesis of Cancer genome era • Genomic information to guide Tx • 3 principles

7. Principle 1: molecular pathway • Somatic / germline genetic mutation • Mitogenic signal transduction pathway • Cell cycle control • Apoptosis • Ubquitin proteolysis • WNT-β catenin signaling: self-renwal • Differentiation • DNA repair pathways • Checkpoints • Epigenetic/chromatin modification • Metabolism

10. Mutant K-RAS @ Undruggable oncoprotein #Downstream pathway: MEK inhibitor (NSCLC) #Coexist mutation: CDKN2A (CDK inhibitor), PIK3CA

11. Epigenetic regulation

12. Metabolic pathway DNA methylation and Histone demethylation

13. Principle 2: anti-cancer agents • In 2004: • 11 targeted agents, 4 category entering clinical trial • RTK, angiogenic, serine/theonine kinases, cell growth/protein translation • In 2012: • 19 targeted agents have approval • 150 compound in study

17. Principle 3: Technology • Formalin-fixed paraffin-embedded tumor tissue • Difficult to identify > 2-3 genes • Allele-based mutational profiling technologies • Mass spectrometric genotyping • Allele-specific PCR • Hundreds of mutation can be identified • Applied to Formalin-fixed paraffin-embedded tumor tissue • Under estimate the actionable tumor genetic event

18. Massicely parallel sequencing (MPS) • DNA based alteration, test for RNA • Mutation identified > Tx developed • Costly • Focus the scope, reduced the cost and time • Genome based patient stratication and therapeutic guidence

19. Outline • Introduction • Principle and hypothesis of genomics-driven cancer medicine • Hypothesis testing • Question encountered • Conclusion

21. Outline • Introduction • Principle and hypothesis of genomics-driven cancer medicine • Hypothesis testing • Question encountered • Conclusion

22. Question 1 • Which mutational profiling approaches will be most enabling for genomics-driven cancer medicine? • Genomic/epigenomic profile • Technical and analytic validation: sensitivity, specificity, time, cost, data storage and transfer

23. Question 2 • What interpretive frameworks may render complex genomic data accessible to oncologists? • Usually not evidence based • Data integration to prevent premature and inappropriate use of the genomic data • Science driven computational algorithms • Rule based • Knowledge based

24. Question 3 • What clinical trial designs will optimally interrogate the utility of tumor genomic information? • More subtypes: selection of patients of specific genomic profile • Genotype - to - phenotype construct • Phenotype - to - genotype approach • Early cancer drug development • Empirical pharmacology  mechanism-based framework

25. Question 4 • How will oncologists and patients handle the return of large-scale genomic information? Return • Beneficence and respect: return results to patients • Incentive to participate clinical trial Not return • Need genetic counselor • Uncertain significance of some mutation

26. Conclusion • Comprehensive genomic information – better Tx outcome • Genomic driven paradigm is complementary : • Immunotherapy • Targeting microenvironment • Stem cell based Tx • Conventional Tx • Genomic profile must be evaluated as part of clinical features • Drug toxicity, tumor heterogeneity, complexity of tumor genomic information  may limited the role  Work hard at work worth doing