Synthetic lethality-mediated precision oncology via the tumor transcriptome

Joo Sang Lee, Nishanth Ulhas Nair, Gal Dinstag, Lesley Chapman, Youngmin Chung, Kun Wang, Sanju Sinha, Hongui Cha, Dasol Kim, Alexander V. Schperberg, Ajay Srinivasan, Vladimir Lazar, Eitan Rubin, Sohyun Hwang, Raanan Berger, Tuvik Beker, Ze'ev Ronai, Sridhar Hannenhalli, Mark R. Gilbert, Razelle KurzrockSe Hoon Lee, Kenneth Aldape, Eytan Ruppin

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish
Pages (from-to)2487-2502.e13
Issue number9
StatePublished - 29 Apr 2021


  • Aged
  • Biomarkers, Tumor/antagonists & inhibitors
  • Clinical Trials as Topic
  • Female
  • Follow-Up Studies
  • Gene Expression Regulation, Neoplastic/drug effects
  • Humans
  • Immunotherapy
  • Male
  • Molecular Targeted Therapy
  • Neoplasms/drug therapy
  • Precision Medicine
  • Prognosis
  • Prospective Studies
  • Retrospective Studies
  • Survival Rate
  • Synthetic Lethal Mutations
  • Transcriptome/drug effects
  • cancer immunotherapy
  • patient stratification
  • precision oncology
  • synthetic lethality
  • synthetic rescues
  • transcriptomics

All Science Journal Classification (ASJC) codes

  • General Biochemistry,Genetics and Molecular Biology


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