蛋白质基因组学
生物
癌变
计算生物学
癌症
遗传学
基因组
基因组学
基因
作者
Yize Li,Eduard Porta‐Pardo,Collin Tokheim,Matthew H. Bailey,Tomer M. Yaron,Vasileios Stathias,Yifat Geffen,Kathleen J. Imbach,Song Cao,Shankara Anand,Yo Akiyama,Wenke Liu,Matthew A. Wyczalkowski,Yizhe Song,Erik Storrs,Michael C. Wendl,Wubing Zhang,Mustafa Sibai,Victoria Ruiz‐Serra,Wen-Wei Liang
出处
期刊:Cell
[Cell Press]
日期:2023-08-01
卷期号:186 (18): 3921-3944.e25
被引量:49
标识
DOI:10.1016/j.cell.2023.07.014
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI