Abstract 4366: Identifying novel recurrent mutations reveals candidate actionable mutations
Authors: Matthew T. Chang, Sizhi Paul Gao, Tripti Shrestha Bhattarai, Tambudzai Shamu, Cyriac Kandoth, Saurabh Asthana, Jocelyn S. Chapman, JianJiong Gao, Nicholas D. Socci, Adam B. Olshen, David M. Hyman, Michael F. Berger, David B. Solit, Nikolaus D. Schultz, Barry S. Taylor
Journal: Cancer Research (2016)

Abstract Mutational hotspots indicate selective pressure across a population of tumor samples and drive the dysregulation of proliferation, invasion, and apoptosis in many human tumors. We recently performed a comprehensive analysis of hotspot mutations in 11,000 retrospectively characterized primary untreated cancers, revealing widespread lineage diversity and mutational specificity. Yet, as broad-based clinical sequencing has begun to guide the routine care of patients, most clinically sequenced cancer patients present with recurrent or metastatic solid tumors. Furthermore, such tumors likely possess distinct mutational patterns driven by prior treatment exposure or treatment-associated evolution after diagnosis that are undetectable in primary untreated samples. We therefore sought to expand our analysis to incorporate such prospectively characterized active cancer patients as part of an ongoing initiative at Memorial Sloan Kettering Cancer Center. With nearly 10,000 patients profiled thus far, this growing prospective dataset with extensive clinical and treatment history is a transformative resource and the largest of its kind. Here, we combined these prospective data with retrospective studies to analyze the somatic mutational landscape of 21,000 cancer patients across 74 cancer types representing the broadest range of human malignancies characterized to date. We developed and applied a biologically and statistically principled computational model to identify hotspots mutated more frequently than would be expected in the absence of selection. This analysis uncovered hundreds of new biologically and therapeutically relevant candidate driver mutations for which targeted agents are currently being investigated in early phase trials. Indeed, we identify several hotspots in key effectors of PI3K and MAPK signaling with differential response in vitro to current investigational therapies suggesting mutant allele-specific therapeutic decisions may be warranted. In total, over half of all hotspot mutations identified were novel, including several novel hotspots in small GTPase RAC1 that are lineage specific and functionally distinct. Understanding the distinct molecular function of these mutations, and the specific mutant alleles at individual codons, is a necessary translational prerequisite for enabling precision oncology through clinical decision support for patients sequenced at the point of care. Citation Format: Matthew T. Chang, Sizhi Paul Gao, Tripti Shrestha Bhattarai, Tambudzai Shamu, Cyriac Kandoth, Saurabh Asthana, Jocelyn S. Chapman, JianJiong Gao, Nicholas D. Socci, Adam B. Olshen, David M. Hyman, Michael F. Berger, David B. Solit, Nikolaus D. Schultz, Barry S. Taylor. Identifying novel recurrent mutations reveals candidate actionable mutations. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4366.