Predicting actionable cancer vulnerabilities enabled by mutant-directed protein-protein interactions

癌症是全球第二大死亡原因，每年造成1000多万人死亡。在……里面 在过去的几十年里，人们做出了巨大的努力来了解分子机制 对肿瘤发生的研究，并为癌症的新治疗策略提供信息。解开癌症基因组和蛋白质组 景观显示，基因组改变，如错义突变，通过重新连接促进了肿瘤的发生 蛋白质相互作用网络(PPI)。然而，对突变导向的新变形体如何 PPI(新PPI)导致癌症标志的获得和新PPI致癌的发现 脆弱性仍然是主要挑战。我们建议通过开发小说来应对这一挑战 名为Averon Notebook的计算方法可发现通过Rewire启用的可操作漏洞 致癌网络。为了实现这一目标，我们将利用我们在癌症生物信息学和 实验癌症生物学在众多出版物中展示和长期参与癌症 国家癌症研究所的靶点发现和开发(CTD^2)网络。在过去十年中，我们 建立了全面的生物信息学工作流程和新颖的分析工具，以收集、处理、 整合和分析不同类型的癌症相关数据。把癌症基因组数据和蛋白质结合起来-- 蛋白质相互作用网络和临床化合物，我们开发了OncoPPI门户，已经 使肿瘤发生的多种新的分子机制得以发现。在这个项目中，我们将利用 基于我们在计算科学和癌症生物学方面的专业知识来开发i)一种新的算法来确定 新PPI调节的生物程序，以及ii)确定新PPI中可操作的脆弱性的方法- 受调控的通路。最终，该项目将提供第一个专门设计的计算环境 为了快速识别突变导向的蛋白质-蛋白质相互作用实现的可操作靶点和途径 通知癌症中的靶点发现。

Cancer is the second leading cause of death worldwide, causing more than 10 million deaths every year. In response, tremendous efforts have been made over the past decades to understand the molecular mechanisms of tumorigenesis and inform new therapeutic strategies in cancer. Unraveling the cancer genome and proteome landscapes revealed that genomic alterations, such as missense mutations, promote tumorigenesis by rewiring networks of protein-protein interactions (PPI). However, the understanding of how mutant-directed neomorph PPIs (neoPPI) lead to the acquisition of cancer hallmarks and the discovery of neoPPI-enabled cancer vulnerabilities remain major challenges. We propose to address this challenge by developing novel computational methods termed Averon Notebook to discover actionable vulnerabilities enabled by rewired oncogenic networks. To achieve this goal, we will leverage our expertise in both cancer bioinformatics and experimental cancer biology demonstrated in numerous publications and long-time participation in the Cancer Target Discovery and Development (CTD^2) Network of the National Cancer Institute. Over the past decade, we have established comprehensive bioinformatics workflows and novel analytical tools to collect, process, integrate, and analyze different types of cancer-related data. To integrate cancer genomics data with protein- protein interaction networks and clinical compounds, we have developed the OncoPPi Portal, which has already enabled the discovery of multiple new molecular mechanisms of tumorigenesis. In this project, we will capitalize on our expertise in computational science and cancer biology to develop i) a new algorithm to determine the neoPPI-regulated biological programs, and ii) methods to determine actionable vulnerabilities in neoPPI- regulated pathways. Ultimately, this project will provide the first computational environment specially designed to rapidly identify actionable targets and pathways enabled by mutant-directed protein-protein interactions to inform target discovery in cancer.