Real-Time Genomic Profiling of Pancreatic Ductal Adenocarcinoma: Potential Actionability and Correlation with Clinical Phenotype - Lowery, Maeve A; Jordan, Emmet J; Basturk, Olca; Ptashkin, Ryan N; Zehir, Ahmet; Berger, Michael F; Leach, Tanisha; Herbst, Brian; Askan, Gokce; Maynard, Hannah; Glassman, Danielle; Covington, Christina; et al. (Clinical cancer research, 2017)
Molecular profiling in cancer has identified potential actionable drug targets that have prompted attempts to discover clinically validated biomarkers to guide therapeutic decision-making and enrollment to clinical trials. We evaluated whether comprehensive genetic analysis of patients with pancreatic adenocarcinoma is feasible within a clinically relevant timeframe and whether such analyses provide predictive and/or prognostic information along with identification of potential targets for therapy. Archival or prospectively acquired FFPE samples and matched normal DNA from = 336 patients with pancreatic cancer were analyzed using a hybridization capture-based, next-generation sequencing assay designed to perform targeted deep sequencing of all exons and selected introns of 410 key cancer-associated genes. Demographic and treatment data were prospectively collected with the goal of correlating treatment outcomes and drug response with molecular profiles. The median time from protocol consent to reporting of the genomic results was 45 days with a median time from tissue delivery of 20 days. All genetic alterations identified were stratified based upon prior evidence that the mutation is a predictive biomarker of drug response using the MSKCC OncoKB classification. Three of 225 patients (1%) received a matched therapy based upon the sequencing results. The practical application of molecular results to guide individual patient treatment is currently limited in patients with pancreatic adenocarcinoma. Future prospective molecular profiling efforts should seek to incorporate routine germline genetic analysis and the identification of DNA profiles that predict for clinical benefit from agents that target DNA damage repair and or immunotherapy. .