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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 Kurzrock
  • Se Hoon Lee, Kenneth Aldape, Eytan Ruppin
  • National Institutes of Health
  • Ltd
  • Sungkyunkwan University
  • University of California at Los Angeles
  • Datar Cancer Genetics Limited
  • Worldwide Innovative Network (WIN) Association-WIN Consortium
  • Ben-Gurion University of the Negev
  • CHA University
  • Sheba Medical Center at Tel Hashomer
  • Sanford Burnham Prebys Medical Discovery Institute
  • University of California at San Diego

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Pages (from-to)2487-2502.e13
JournalCell
Volume184
Issue number9
DOIs
StatePublished - 29 Apr 2021

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • cancer immunotherapy
  • patient stratification
  • precision oncology
  • synthetic lethality
  • synthetic rescues
  • transcriptomics

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