Document Type

Article

Publication Date

6-10-2020

Keywords

JGM, JAXCC

JAX Source

Nat Commun 2020 Jun 10; 11(1):2935

PMID

32523045

DOI

https://doi.org/10.1038/s41467-020-16735-2

Abstract

Personalized cancer treatments using combinations of drugs with a synergistic effect is attractive but proves to be highly challenging. Here we present an approach to uncover the efficacy of drug combinations based on the analysis of mono-drug effects. For this we used dose-response data from pharmacogenomic encyclopedias and represent these as a drug atlas. The drug atlas represents the relations between drug effects and allows to identify independent processes for which the tumor might be particularly vulnerable when attacked by two drugs. Our approach enables the prediction of combination-therapy which can be linked to tumor-driving mutations. By using this strategy, we can uncover potential effective drug combinations on a pan-cancer scale. Predicted synergies are provided and have been validated in glioblastoma, breast cancer, melanoma and leukemia mouse-models, resulting in therapeutic synergy in 75% of the tested models. This indicates that we can accurately predict effective drug combinations with translational value.

Comments

This is an openaccess article distributed under the terms of the Creative Commons Attribution 4.0 International license.

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