Emergent Gene Expression Responses to Drug Combinations Predict Higher-Order Drug Interactions
Emergent Gene Expression Responses to Drug Combinations Predict Higher-Order Drug Interactions
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DOI：
10.1016/j.cels.2019.10.004
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发表时间：
2019-11-27
期刊：
影响因子：
9.3
通讯作者：
Bollenbach, Tobias
中科院分区：
文献类型：
--
作者：
Lukacisin, Martin;Bollenbach, Tobias
有效的联合治疗设计需要了解药物相互作用引起的细胞生理学变化。在这里，我们表明，在严格控制的生长速率下测量的两种药物组合的全基因组转录反应可以预测酿酒酵母中第三种药物的高阶拮抗作用。使用等生长分析，超过90%的细胞反应的变化可以分解为三个主成分（PC），具有明确的生物学解释。我们证明，第三个PC捕获紧急转录程序，依赖于两种药物，并可以预测与第三种药物靶向紧急途径的拮抗作用。我们进一步表明，新兴的基因表达模式是最明显的药物比例的药物相互作用是最强的，为未来的测量提供了指导方针。我们的研究结果提供了一个容易适用的处方，发现在其他系统的紧急反应和高阶药物组合。本文的透明同行评审过程的记录包含在补充信息中。
Effective design of combination therapies requires understanding the changes in cell physiology that result from drug interactions. Here, we show that the genome-wide transcriptional response to combinations of two drugs, measured at a rigorously controlled growth rate, can predict higher-order antagonism with a third drug in Saccharomyces cerevisiae. Using isogrowth profiling, over 90% of the variation in cellular response can be decomposed into three principal components (PCs) that have clear biological interpretations. We demonstrate that the third PC captures emergent transcriptional programs that are dependent on both drugs and can predict antagonism with a third drug targeting the emergent pathway. We further show that emergent gene expression patterns are most pronounced at a drug ratio where the drug interaction is strongest, providing a guideline for future measurements. Our results provide a readily applicable recipe for uncovering emergent responses in other systems and for higher-order drug combinations. A record of this paper's transparent peer review process is included in the Supplemental Information.