Abstract 528: Identify and prioritize candidate neoantigens from cancer exome sequencing with unmatched accuracy

Abstract

Abstract Somatic, nonsynonymous genetic alterations present in cancer can lead to the formation of novel protein sequences and thus production of immunogenic “non-self” neoantigens. Some of those neoantigens will be processed, presented on MHC molecules, and induce tumor-specific T cell responses. Because neoantigens play central roles in the cancer-immunity cycle, it is critical to identify the most potent immunogenic neoantigens effectively and accurately. Combining PGDx's highly accurate cancer exome analyses (CancerXome™) with in silico neoantigen prediction, we have launched ImmunoSelect-R™ that identifies and prioritizes the most relevant mutation-derived neoantigens. To ensure detection of true somatic mutations and prevent false positive mutations from confounding neoantigen identification, ImmunoSelect utilizes CancerXome that delivers unparalleled cancer whole exome sequencing accuracy, achieving 95% sensitivity and 97% positive predictive value at 10% mutant allele frequency with 150x coverage. ImmunoSelect also provides accurate HLA typing from whole exome sequencing with >99.9% sensitivity and specificity. Once exome-based mutations and novel open-reading-frames are identified and HLA genotypes defined, ImmunoSelect utilizes state of art bioinformatics pipelines for prediction and prioritization of the most relevant neoantigens. When applied to a set of experimentally validated neoantigens, ImmunoSelect identified 18 out of 19 of them as being strong neoantigen candidates, suggesting a sensitivity of greater than 90%. Moreover, ImmunoSelect consistently ranked experimentally validated neoantigens within top 20% of all neoantigen candidates derived from whole exome sequencing. In summary, ImmunoSelect is able to identify and prioritize candidate neoantigens from cancer exome sequencing results effectively and accurately, enabling personalized cancer vaccine development, adoptive T-cell transfer, and prediction of response to checkpoint inhibitors Citation Format: James White, Sam Angiuoli, Mark Sausen, Sian Jones, Lisa Kann, Manish Shukla, Maria Sevdali, Victor Velculescu, Luis Diaz, Theresa Zhang. Identify and prioritize candidate neoantigens from cancer exome sequencing with unmatched accuracy. [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 528.