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Abstract
Abstract Missense mutations can change protein structure, cellular localization, and functions. Such changes lead to the rewiring of protein-protein interaction (PPI) networks, activation of oncogenic pathways, and acquisition of cancer hallmarks. However, the translation of the landscape of oncogenic mutations into clinically actionable biological models for cancer target discovery remains a major challenge. We address this challenge by leveraging the power of computational systems biology supported by high-throughput screening technologies. While some mutations can disrupt the PPIs, others may induce new PPIs that are not natural for the wild-type counterparts. Recently, we have established a quantitative High Throughput differential Screening (qHT-dS) platform [1] to discover such mutant-enabled or neomorph PPIs (neoPPIs). The screening of more than 13,000 mutant interactions revealed a landscape of gain-of-interactions encompassing both oncogenic and tumor suppressor mutations. This emerging neoPPI landscape may offer new mutant-directed therapeutic approaches for precision medicine. However, to infer clinically actionable mechanistic insights into how neoPPIs promote tumorigenesis special computational tools are needed. To inform the neoPPI-based target discovery, we develop a set of innovative informatics tools for discovering Actionable Vulnerabilities Enabled by Rewired Oncogenic Networks (Averon). Implemented in a widely-used Jupyter Notebook format, the Averon streamlines the identification of the oncogenic programs and clinically significant genes that are regulated by neoPPIs in cancer patients. The Averon can recapitulate well-established connectivity between known mutant-dependent PPIs and specific oncogenic pathways and reveal new, previously unknown mechanisms of neoPPI-mediated oncogenic signaling. To inform new therapeutic strategies in neoPPI-dependent cancers, Averon connects neoPPI-regulated genes with available approved drugs and clinical compounds. Together, the Averon provides a powerful informatics environment to determine therapeutically actionable vulnerabilities created by mutant-regulated protein-protein interactions to inform new personalized therapeutic strategies in cancer. Acknowledgments: This work was supported in part by NCI’s Informatics Technology for Cancer Research (ITCR) Program (R21CA274620, A.A.I.), Winship Cancer Institute #IRG-17-181-06 from the American Cancer Society (A.A.I.). Cancer Target Discovery and Development (CTD2) Network (U01CA217875, H.F.), NCI Emory Lung Cancer SPORE (P50CA217691, H.F.), Career Enhancement Program (A.A.I., P50CA217691), Winship Cancer Institute (NIH 5P30CA138292).
Published Version
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