| Literature DB >> 32945258 |
Jennifer El Diaz1,2,3, Mehmet Eren Ahsen1,3,4, Thomas Schaffter1,3, Xintong Chen1, Ronald B Realubit5,6, Charles Karan5,6, Andrea Califano5,7,8,9, Bojan Losic1,10,11,12, Gustavo Stolovitzky1,3,5,7.
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.Entities:
Keywords: LNCaP; MCF7; cancer biology; cell biology; computational biology; drug synergy; human; rna-seq; systems biology; transcriptomics
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Year: 2020 PMID: 32945258 PMCID: PMC7546737 DOI: 10.7554/eLife.52707
Source DB: PubMed Journal: Elife ISSN: 2050-084X Impact factor: 8.140