The transcriptomic response of cells to a drug combination is more than the sum of the responses to the monotherapies

Elife. 2020 Sep 18:9:e52707. doi: 10.7554/eLife.52707.

Abstract

Our ability to discover effective drug combinations is limited, in part by insufficient understanding of how the transcriptional response of two monotherapies results in that of their combination. We analyzed matched time course RNAseq profiling of cells treated with single drugs and their combinations and found that the transcriptional signature of the synergistic combination was unique relative to that of either constituent monotherapy. The sequential activation of transcription factors in time in the gene regulatory network was implicated. The nature of this transcriptional cascade suggests that drug synergy may ensue when the transcriptional responses elicited by two unrelated individual drugs are correlated. We used these results as the basis of a simple prediction algorithm attaining an AUROC of 0.77 in the prediction of synergistic drug combinations in an independent dataset.

Keywords: LNCaP; MCF7; cancer biology; cell biology; computational biology; drug synergy; human; rna-seq; systems biology; transcriptomics.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Algorithms
  • Computational Biology
  • Drug Combinations*
  • Drug Synergism*
  • Gene Expression*
  • Gene Regulatory Networks / physiology*
  • Humans
  • MCF-7 Cells
  • RNA-Seq
  • Transcription Factors / metabolism
  • Transcriptome*

Substances

  • Drug Combinations
  • Transcription Factors

Associated data

  • GEO/GSE149428