SYS-Mut: Decoding the Functional Significance of Rare Somatic Mutations in Cancer

Current tailored-therapy efforts in cancer are largely focused on a small number of highly recurrently-mutated driver genes but therapeutic targeting of these oncogenes remains challenging. On the other hand, the vast number of genes mutated infrequently across cancers have received less attention, in part, due to a lack of understanding of their biologic significance. Here we present SYS-Mut, a systems biology platform that can robustly infer the biologic consequences of somatic mutations by integrating routine multi-omic profiles in primary tumors. We established the accuracy of SYS-Mut by recapitulating the functional impact of known driver genes in PanCancer datasets. Subsequent application of SYS-Mut on low-frequency gene mutations in Head and Neck Cancers (HNSC), followed by molecular and pharmacogenetic validation, revealed the lipidogenic network as a novel therapeutic vulnerability in aggressive HNSC. SYS-Mut is thus a robust scalable framework that enables discovery of new targetable avenues in cancer. ### Competing Interest Statement Vinay Varadan is currently employed at Merck Research Laboratories. The authors declare no other competing interests.