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Yang, M.* ; Jaaks, P.* ; Dry, J.* ; Garnett, M.* ; Menden, M. ; Saez-Rodriguez, J.*

Stratification and prediction of drug synergy based on target functional similarity.

NPJ Syst. Biol. Appl. 6:16 (2020)
Verlagsversion Forschungsdaten DOI
Open Access Gold
Creative Commons Lizenzvertrag
Drug combinations can expand therapeutic options and address cancer's resistance. However, the combinatorial space is enormous precluding its systematic exploration. Therefore, synergy prediction strategies are essential. We here present an approach to prioritise drug combinations in high-throughput screens and to stratify synergistic responses. At the core of our approach is the observation that the likelihood of synergy increases when targeting proteins with either strong functional similarity or dissimilarity. We estimate the similarity applying a multitask machine learning approach to basal gene expression and response to single drugs. We tested 7 protein target pairs (representing 29 combinations) and predicted their synergies in 33 breast cancer cell lines. In addition, we experimentally validated predicted synergy of the BRAF/insulin receptor combination (Dabrafenib/BMS-754807) in 48 colorectal cancer cell lines. We anticipate that our approaches can be used for prioritization of drug combinations in large scale screenings, and to maximize the efficacy of drugs already known to induce synergy, ultimately enabling patient stratification.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Schlagwörter Cancer; Braf; Therapy; Inhibition; Melanoma; Colon; Pairs
ISSN (print) / ISBN 2056-7189
e-ISSN 2056-7189
Quellenangaben Band: 6, Heft: 1, Seiten: , Artikelnummer: 16 Supplement: ,
Verlag Nature Publishing Group
Verlagsort London
Begutachtungsstatus Peer reviewed