Tissue-Specific Signaling Networks Rewired by Major Somatic Mutations in Human Cancer Revealed by Proteome-Wide Discovery

Massive somatic mutations discovered by large cancer genome sequencing projects provide unprecedented opportunities in the development of precision oncology. However, deep understanding of functional consequences of somatic mutations and identifying actionable mutations and the related drug responses currently remain formidable challenges. Dysfunction of protein posttranslational modification plays critical roles in tumorigenesis and drug responses. In this study, we proposed a novel computational oncoproteomics approach, named kinome-wide network module for cancer pharmacogenomics (KNMPx), for identifying actionable mutations that rewired signaling networks and further characterized tumorigenesis and anticancer drug responses. Specifically, we integrated 746,631 missense mutations in 4,997 tumor samples across 16 major cancer types/subtypes from The Cancer Genome Atlas into over 170,000 carefully curated nonredundant phosphorylation sites covering 18,610 proteins. We found 47 mutated proteins (e.g., ERBB2, TP53, and CTNNB1) that had enriched missense mutations at their phosphorylation sites in pan-cancer analysis. In addition, tissue-specific kinase-substrate interaction modules altered by somatic mutations identified by KNMPx were significantly associated with patient survival. We further reported a kinome-wide landscape of pharmacogenomic interactions by incorporating somatic mutation-rewired signaling networks in 1,001 cancer cell lines via KNMPx. Interestingly, we found that cell lines could highly reproduce oncogenic phosphorylation site mutations identified in primary tumors, supporting the confidence in their associations with sensitivity/resistance of inhibitors targeting EGF, MAPK, PI3K, mTOR, and Wnt signaling pathways. In summary, our KNMPx approach is powerful for identifying oncogenic alterations via rewiring phosphorylation-related signaling networks and drug sensitivity/resistance in the era of precision oncology. (C) 2017 AACR.