Reported by R5 李霖昆Supervised by 楊慕華 大夫
Genomics-Driven Oncology: Framework for anEmerging Paradigm
Review article
Journal of Clinical Oncology 31, 15, 1806–1814, May 20th , 2013
Levi A. Garraway
Outline
Introduction Principle and hypothesis of
genomics-driven cancer medicine Hypothesis testing Question encountered Conclusion
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
In 1985: Somatic genetic derangement Diagnostic and prognostic impact Patient stratification
In 1990s and 2000s: Trastuzumab, Imatinib CRC, NSCLC, melanoma
New treatment paradigm
Outline
Introduction Principle and hypothesis of
genomics-driven cancer medicine
Hypothesis testing Question encountered Conclusion
During past decades Tumor biology, genomics technology,
computational innovation, drug discovery
Translational cancer research Driver genetic alteration
Dysregulated protein: Cancer cells depend on
Targeted agentsHypothesis of Cancer genome era
Genomic information to guide Tx3 principles
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
Mutant K-RAS@ Undruggable oncoprotein #Downstream pathway: MEK inhibitor (NSCLC) #Coexist mutation: CDKN2A (CDK inhibitor), PIK3CA
Epigenetic regulation
Metabolic pathway
DNA methylation and Histone demethylation
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
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 PCRHundreds of mutation can be identifiedApplied to Formalin-fixed paraffin-
embedded tumor tissueUnder estimate the actionable tumor
genetic event
Massicely parallel sequencing (MPS) DNA based alteration, test for RNA Mutation identified > Tx developed CostlyFocus the scope, reduced the cost and
time
Genome based patient stratication and therapeutic guidence
Outline
Introduction Principle and hypothesis of
genomics-driven cancer medicine Hypothesis testing Question encountered Conclusion
Outline
Introduction Principle and hypothesis of
genomics-driven cancer medicine Hypothesis testing Question encountered Conclusion
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
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
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
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
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