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  • 标题:Identifying mutant-specific multi-drug combinations using comparative network reconstruction
  • 本地全文:下载
  • 作者:Evert Bosdriesz ; João M. Fernandes Neto ; Anja Sieber
  • 期刊名称:iScience
  • 印刷版ISSN:2589-0042
  • 出版年度:2022
  • 卷号:25
  • 期号:8
  • 页码:1-18
  • DOI:10.1016/j.isci.2022.104760
  • 语种:English
  • 出版社:Elsevier
  • 摘要:SummaryTargeted inhibition of aberrant signaling is an important treatment strategy in cancer, but responses are often short-lived. Multi-drug combinations have the potential to mitigate this, but to avoid toxicity such combinations must be selective and given at low dosages. Here, we present a pipeline to identify promising multi-drug combinations. We perturbed an isogenic PI3K mutant and wild-type cell line pair with a limited set of drugs and recorded their signaling state and cell viability. We then reconstructed their signaling networks and mapped the signaling response to changes in cell viability. The resulting models, which allowed us to predict the effect of unseen combinations, indicated that no combination selectively reduces the viability of the PI3K mutant cells. However, we were able to validate 25 of the 30 combinations that we predicted to be anti-selective. Our pipeline enables efficient prioritization of multi-drug combinations from the enormous search space of possible combinations.Graphical abstractDisplay OmittedHighlights•Systematics drug perturbations measurements in isogenic PI3K wild-type and mutant cells•Mutant-specific reconstruction and quantification of signal transduction networks•Short-term signaling response is predictive for longer term cell viability•25 out of 30 model predictions of mutant-specific multi-drug combinations validatedBioinformatics; Pharmacoinformatics; Systems biology; In silico biology
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