| Literature DB >> 33857424 |
Joo Sang Lee1, Nishanth Ulhas Nair2, Gal Dinstag3, Lesley Chapman2, Youngmin Chung4, Kun Wang2, Sanju Sinha2, Hongui Cha5, Dasol Kim4, Alexander V Schperberg6, Ajay Srinivasan7, Vladimir Lazar8, Eitan Rubin9, Sohyun Hwang10, Raanan Berger11, Tuvik Beker3, Ze'ev Ronai12, Sridhar Hannenhalli2, Mark R Gilbert13, Razelle Kurzrock14, Se-Hoon Lee15, Kenneth Aldape16, Eytan Ruppin17.
Abstract
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.Entities:
Keywords: cancer immunotherapy; patient stratification; precision oncology; synthetic lethality; synthetic rescues; transcriptomics
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Year: 2021 PMID： 33857424 PMCID： PMC9310669 DOI： 10.1016/j.cell.2021.03.030
Source DB: PubMed Journal: Cell ISSN： 0092-8674 Impact factor: 66.850