SYNERGxDB

A comprehensive database to explore synergistic drug combinations for biomarker discovery

Description: Many studies have highlighted the use of drug combination approaches in the treatment of tumors, which have been shown to provide aid in overcoming cancer treatment failures. However, the impact of genetics on variability in combo responses for discovering predictive and prognostic biomarkers is currently unknown. To help solve this issue, we created SYNERGxDB, a web-application that possesses the largest database of seven collections of pharmacological and molecular profiles of corresponding cell lines (124 cell lines in 11 tissue types and 1,962 drugs/compounds - 15,268 combinations). This application allows researchers and clinicians to identify novel synergistic drug combinations, in order to discover potential prognostic and predictive biomarkers that can help improve patient prognosis and selection.

Authors: Heewon Seo, Denis Tkachuk & Benjamin Haibe-Kains
Lab: Haibe-Kains
Resource Type: Database
Keywords: SYNERGxDB, drug combination, biomarkers, datasets, cell lines, molecular profiles, pharmacogenomics, visualization
Licensing:

Citation

Heewon Seo, Denis Tkachuk, Chantal Ho, Anthony Mammoliti, Aria Rezaie, Seyed Ali Madani Tonekaboni, Benjamin Haibe-Kains, SYNERGxDB: an integrative pharmacogenomic portal to identify synergistic drug combinations for precision oncology, Nucleic Acids Research, Volume 48, Issue W1, 02 July 2020, Pages W494–W501, https://doi.org/10.1093/nar/gkaa421
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