生物
转录组
精确肿瘤学
合成致死
癌症研究
杀伤力
计算生物学
精密医学
基因
遗传学
基因表达
DNA修复
作者
Joo Sang Lee,Nishanth Ulhas Nair,Gal Dinstag,Lesley M. Chapman,Youngmin Chung,Kun Wang,Sanju Sinha,Hongui Cha,Dasol Kim,Alexander Schperberg,Ajay Srinivasan,Vladimir Lazar,Eitan Rubin,Sohyun Hwang,Raanan Berger,Tuvik Beker,Ze’ev A. Ronai,Sridhar Hannenhalli,Mark R. Gilbert,Razelle Kurzrock
出处
期刊:Cell
[Cell Press]
日期:2021-04-01
卷期号:184 (9): 2487-2502.e13
被引量:150
标识
DOI:10.1016/j.cell.2021.03.030
摘要
Precision oncology has made significant advances, mainly by targeting actionable mutations in cancer driver genes. Aiming to expand treatment opportunities, recent studies have begun to explore the utility of tumor transcriptome to guide patient treatment. Here, we introduce SELECT (synthetic lethality and rescue-mediated precision oncology via the transcriptome), a precision oncology framework harnessing genetic interactions to predict patient response to cancer therapy from the tumor transcriptome. SELECT is tested on a broad collection of 35 published targeted and immunotherapy clinical trials from 10 different cancer types. It is predictive of patients' response in 80% of these clinical trials and in the recent multi-arm WINTHER trial. The predictive signatures and the code are made publicly available for academic use, laying a basis for future prospective clinical studies.
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