@article{935f6cfae5e04d47901ccfe8216944ff,
title = "Synthetic lethality-mediated precision oncology via the tumor transcriptome",
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{\textquoteright} 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.",
keywords = "cancer immunotherapy, patient stratification, precision oncology, synthetic lethality, synthetic rescues, transcriptomics",
author = "Lee, \{Joo Sang\} and Nair, \{Nishanth Ulhas\} and Gal Dinstag and Lesley Chapman and Youngmin Chung and Kun Wang and Sanju Sinha and Hongui Cha and Dasol Kim and Schperberg, \{Alexander V.\} and Ajay Srinivasan and Vladimir Lazar and Eitan Rubin and Sohyun Hwang and Raanan Berger and Tuvik Beker and Ze'ev Ronai and Sridhar Hannenhalli and Gilbert, \{Mark R.\} and Razelle Kurzrock and Lee, \{Se Hoon\} and Kenneth Aldape and Eytan Ruppin",
note = "This research is supported in part by the Intramural Research Program of the National Institutes of Health (NIH), National Cancer Institute (NCI), Center for Cancer Research (CCR). This work utilized the computational resources of the NIH HPC Biowulf cluster. We thank E. Michael Gertz, Alejandro A. Sch{\"a}ffer, Sanna Madan, Peng Jiang, Tom Misteli, and Louis Staudt for providing many helpful comments. We thank all the patients and clinicians involved in the clinical trials analyzed in this study. We thank Elizabeth Jaffe, Ignacio Melero, Robert Prins, Raul Rabadan, Antoni Ribas, Jeffrey Thompson, Nitin Roper, and Udayan Guha for sharing their data. This publication is partly based on research using data from Tempus Labs that has been made available through Vivli. Vivli has not contributed to or approved of and is not in any way responsible for the contents of this publication. J.S.L. is partly supported by a grant of the National Research Foundation of Korea funded by the Korean Government ( NRF-2020R1A2C2007652 ) and Institute of Information \& Communications Technology Planning \& Evaluation (IITP) grant funded by the Korean Government (MSIT) (no. 2019-0-00421 , AI Graduate School Support Program [Sungkyunkwan University]). This research is supported in part by the Intramural Research Program of the National Institutes of Health (NIH), National Cancer Institute (NCI), Center for Cancer Research (CCR). This work utilized the computational resources of the NIH HPC Biowulf cluster. We thank E. Michael Gertz, Alejandro A. Sch?ffer, Sanna Madan, Peng Jiang, Tom Misteli, and Louis Staudt for providing many helpful comments. We thank all the patients and clinicians involved in the clinical trials analyzed in this study. We thank Elizabeth Jaffe, Ignacio Melero, Robert Prins, Raul Rabadan, Antoni Ribas, Jeffrey Thompson, Nitin Roper, and Udayan Guha for sharing their data. This publication is partly based on research using data from Tempus Labs that has been made available through Vivli. Vivli has not contributed to or approved of and is not in any way responsible for the contents of this publication. J.S.L. is partly supported by a grant of the National Research Foundation of Korea funded by the Korean Government (NRF-2020R1A2C2007652) and Institute of Information \& Communications Technology Planning \& Evaluation (IITP) grant funded by the Korean Government (MSIT) (no. 2019-0-00421, AI Graduate School Support Program [Sungkyunkwan University]). J.S.L. and E.R. led the study and J.S.L. K.A. and E.R. wrote the manuscript. N.U.N. and G.D. helped with the computational analysis. L.C. S.S. K.W. H.C. A.V.S. S.H. E.R. V.L. R.B. A.S. and S.-H.L. helped with data collection. N.U.N. G.D. D.K. and Y.C. helped reviewing the source code. N.U.N. G.D. T.B. Z.R. S.H. M.R.G. R.K. and K.A. contributed to the conceptual construction of the study. E.R. is a co-founder of Medaware, Metabomed, and Pangea Therapeutics (divested from the latter). E.R. serves as a non-paid scientific consultant to Pangea Therapeutics, a company developing a precision oncology SL-based multi-omics approach. J.S.L. is a scientific consultant; T.B. is chief executive officer and chief technical officer; G.D. is head of research and development; R.B. is a member of the Scientific Advisory Board; and Z.R. is a co-founder and a scientific advisor at Pangea Therapeutics. R.K. receives research funding from Genentech, Merck Serono, Pfizer, Boehringer Ingelheim, TopAlliance, Takeda, Incyte, Debiopharm, Medimmune, Sequenom, Foundation Medicine, Konica Minolta, Grifols, Omniseq, and Guardant; received consultant, speaker, and/or advisory board fees for X-Biotech, Neomed, Pfizer, Actuate Therapeutics, Roche, Turning Point Therapeutics, TD2/Volastra, and Bicara Therapeutics; has an equity interest in IDbyDNA and CureMatch; serves on the board of CureMatch and CureMetrix; and is a co-founder of CureMatch. A patent application associated with this manuscript is in process.",
year = "2021",
month = apr,
day = "29",
doi = "10.1016/j.cell.2021.03.030",
language = "English (US)",
volume = "184",
pages = "2487--2502.e13",
journal = "Cell",
issn = "0092-8674",
publisher = "Elsevier B.V.",
number = "9",
}