癌症驱动事件是指推动癌症发生的关键基因异常，然而，其确切的分子机制仍不完全理解。在这里，我们的多组学全癌分析通过识别在RNA、蛋白质和磷蛋白水平上测得的癌症驱动因子的显著cis效应和远端trans效应，揭示了癌症驱动因子的影响。显著的观察结果包括点突变和拷贝数变异与蛋白相互作用网络改组之间的关联，特别是，大多数癌症基因都趋于相似的分子状态，这些状态由基于序列的激酶活性配置文件表示。预测的新抗原负担与测得的T细胞浸润之间的相关性暗示了免疫疗法的潜在易感性。癌症标志物的模式因多基蛋白质丰度的不同而变化，从均匀到异质。总体而言，我们的研究表明，全面的蛋白质组学在理解致癌驱动因子的功能状态及其与癌症发展的关系方面具有价值，超越了研究单个癌症类型的限制。版权所有©2023 The Authors。Elsevier Inc.保留所有权利。

Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.