The Genetics of Cancer: Is Personalization of Cancer Treatment Possible?
Keith T. Flaherty, M.D. Massachusetts General Hospital Cancer Center
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The Genetics of Cancer: Is Personalization of Cancer Treatment Possible? Keith T. Flaherty, M.D. Massachusetts General Hospital Cancer Center Disclosures Board of Directors: Clovis Oncology, Loxo Oncology Scientific Advisory Board:
Keith T. Flaherty, M.D. Massachusetts General Hospital Cancer Center
Alexandrov et al. Nature 2013
Alexandrov et al. Nature 2013
Cancer Genome Atlas Research Network et al. TCGA symposium 2012
200
50% 25% 10%
Sullivan RJ & Flaherty KT. CCR 2014
Cancer Genome Atlas Research Network et al. TCGA symposium 2012
AKT3 MDM2 BRAF MITF
RECIST 30% Decrease
Sosman J et al. NEJM 2012
20 40 60 80 100
Maximum percent reduction from baseline measurement
Best confirmed response Complete response Partial response Progressive disease Stable disease
20 40 60 80 100
Dabrafenib monotherapy Dabrafenib 150 mg BID/Trametinib 2 mg QD
Long G et al. ESMO 2012
Rizvi N et al. CCR 2011
Camidge R et al. Lancet Oncol 2012
Kopetz, ASCO 2010
melanoma colorectal
Sosman J et al. NEJM 2012
Mendoza et al. Trends Biochem Sci. 2011
Kopetz, ASCO 2010 Corcoran ASCO 2012
– De-identified samples submitted to central labs – Whole-exome sequencing (research purposes)
Study agent Stable Disease, Complete or partial response (CR+PR)1 Actionable mutation detected No additional actionable mutations, or withdraw consent Genetic sequencing Progressive disease (PD)1 Off study PD Continue on study agent until progression Check for additional actionable mutations2 Yes No
1CR, PR, SD, and PD as defined by RECIST 2Rebiopsy; if additional mutations, offer new targeted therapy
– Exclude histologies that had been approved by the FDA or had shown lack of efficacy with an agent
Statistical Considerations (within each drug-by-mutation category)
– About 200 genes – SNV, indel, CNV, targeted translocations
– MDAnderson (Hamilton) – MGH (Iafrate) – Yale (Sklar)
tumor content, % necrosis, inflammation, and scanned into high resolution image database
– If sufficient DNA is available, whole-exome sequencing can be performed for research
– RNA will be used for research grade gene expression profiling by either whole-transcriptome or miRNA microarray analysis
Workflow and Turnover Time 22
Tiss issue Fix ixation Path Review Nuc ucleic Ac Acid Ex Extraction Lib Library/Template Prep Seq Sequencing aM aMOI OI Rep eport Review
Sang Sanger Ver erifi ification
Biop iopsy Received 3 DAYS 1 DAY 1 DAY 1 DAY 1 DAY 3 DAYS
Fin Final l Report Tumor content >50% DNA yield > 20 ng
Library yield > 20 pM
Test fragments Total read Reads per BC Coverage NTC, Positive, Negative Controls
– Selective activity in biomarker-defined model – Functional evidence that alterations in target lead to upregulation & dependence – Functional evidence of pathway activation as consequence
Drug Molecular Targets Afatinib EGFR activating (non NSCLC) Afatinib HER2 kinase activating AMG 337 MET amplification AMG 595 EGFR vIII AZD 9291 EGFR T790M (non NSCLC) Crizotinib ALK fusions Crizotinib ROS translocations Dabrafenib + Trametinib BRAF V600E (nonmelanoma) GDC 0032 PIK3CA ampl/mut; WT RAS, No PTEN loss GSK2636771 PTEN Mut, PTEN IHC+ GSK2636771 PTEN Mut, PTEN IHC – GSK2636771 PTEN wt, PTEN IHC - JNJ 493 Ampl FGFR 1,2, or 4; FGFR mut MLN 0128 mTOR mut MLN 0128 TSC1 or TSC2 mut Sunitinib KIT mutations TDM-1 HER 2 ampl (non breast or gastric) Trametinib BRAF nonV600E or fusions Trametinib NF1 mut (arm1) GNAQ,GNA11 mut (arm 2) Trastuzumab/pertuzumab HER2 ampl (non breast or gastric) Vismodegib SMO or PTCH mut VS 6063 NF2 loss