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Cancer Treatment from the DNA Perspective

Cancer Treatment from the DNA Perspective. Peter J. O’Dwyer , MD University of Pennsylvania ECOG-ACRIN Cancer Research Group. DNA Mutation. C. A. A. G. C. T. A. A. C. T. DNA. Normal gene. C. A. A. G. C. G. A. A. C. T. Single base change. C. A. A. G. G. C. G. C.

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Cancer Treatment from the DNA Perspective

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  1. Cancer Treatment from the DNA Perspective Peter J. O’Dwyer, MD University of Pennsylvania ECOG-ACRIN Cancer Research Group

  2. DNA Mutation C A A G C T A A C T DNA Normal gene C A A G C G A A C T Single base change C A A G G C G C T A A C T Additions C T C A A G A A C T Deletions

  3. Oncogenes Normal cell Normal genes regulate cell growth Oncogenes accelerate cell growth and division Cancer cell Mutated/damaged oncogene

  4. Tumor Suppressor Genes Act Like a Brake Pedal Tumor Suppressor Gene Proteins Growth factor Receptor Signaling enzymes Transcriptionfactors DNA Cell nucleus Cell proliferation

  5. Genomics-Driven Trials • Assumption: Given a specific mutation, a particular growth or survival pathway will be activated, so therapy can be directed specifically to it • Disease-Specific • Breast Cancer – I-SPY • Lung Cancer – LUNG-MAP, ALCHEMIST • Colorectal Cancer – ASSIGN (in development) • “Disease-Agnostic” • MATCH

  6. MATCH – Preliminary Hypothesis Primary: That tumors that share common somatic genetic alterations in oncogenes will be variably responsive to therapies targeting the oncogenic pathway based on lineage specific factors.  Secondary: That concomitant somatic genetic alterations will predict responsiveness or resistance.

  7. MATCH TRIAL OVERVIEW Identify mutations/amplifications/translocations in patient tumor sample - eligibility determination Assign patient to relevant agent/regimen – single-arm Phase II design Need to sequence large numbers of tumors (3000pts) and need to have large numbers of targeted treatments Tumor biopsies & sequencing at progression to investigate resistance mechanisms • De-identified samples submitted to central labs • Whole-exome sequencing (research purposes) to detect non-ambiguous germline variants Alliance Spring Group Meeting / May 9, 2014

  8. MATCH: SCHEMA Tumor Biopsy

  9. Statistical Considerations Within each drug-by-mutation category: • Dual Primary Endpoints: • Overall Response Rate 5% vs. 25% or • Progression Free Survival 6 months 15% (median PFS 2.2 m) vs 35% (median PFS 4 m) • One stage design 31 evaluable patients per arm ORR = proportion of patients with objective response (PR+CR) on initial course of study agent PFS6 = proportion of patients alive and progression free at 6 months from initiation of study agent

  10. CLIA LAB NETWORK • Genetic platform: Ion Torrent PGM AmpliSeq custom panel; Oncomine under evaluation • About 200 genes • SNV, indel, CNV, targeted translocations • Immunohistochemical expression of PTEN • Validation within and across sites: same SOP • Possibly additional IHC and FISH, if needed • Lead laboratory: Frederick National Laboratory for Cancer Research (Williams) • Competitively chosen lab sites: • MD Anderson (Hamilton) • MGH (Iafrate) • Yale (Sklar)

  11. SUMMARY In planning for a year, MATCH slated to open by end 2014. Robust state-of-the-art platform finalized September 2014 Agreements close to final with four companies for genotype-specific drugs Strong CTEP-Intergroup collaboration in developing the trial Broad community oncologist and advocate input refined design

  12. NCI MATCH PARTICIPATION

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