Abstract 397: Systematic functional annotation of somatic mutations in cancer

Recent sequencing studies have identified thousands of unique somatic mutations across patient tumors. However, the functional impact of the vast majority of these mutations remains unknown, representing a critical knowledge gap for implementing precision oncology. Here, we report the development of a moderate-throughput functional genomic platform consisting of efficient mutant open reading frame generation, sensitive viability assays using two growth factor-dependent cell models, and functional proteomic profiling of downstream signaling effects for select aberrations. We apply the platform to annotate >1,000 genomic aberrations, including gene amplifications, point mutations, indels, and gene fusions, potentially doubling the number of driver mutations characterized in clinically actionable genes. We show that our platform has higher sensitivity for characterizing weak drivers than pooled screening. Our data are accessible through the user-friendly, open-access data portal we created. Our study will facilitate the discovery of novel biomarkers, improvement of existing prediction algorithms, and development of new therapeutic approaches. Citation Format: Han Liang, Patrick Kwok-Shing Ng, Jun Li, Kang Jin Jeong, Yiling Lu, Song Yi, Nidhi Sahni, Gordon Mills. Systematic functional annotation of somatic mutations in cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 397.