通过整合药物敏感性和选择性谱对乳腺癌细胞中激酶依赖性组合进行系统定位。

Chemistry & biology Pub Date : 2015-08-20 Epub Date: 2015-07-23 DOI:10.1016/j.chembiol.2015.06.021
Agnieszka Szwajda, Prson Gautam, Leena Karhinen, Sawan Kumar Jha, Jani Saarela, Sushil Shakyawar, Laura Turunen, Bhagwan Yadav, Jing Tang, Krister Wennerberg, Tero Aittokallio
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引用次数: 22

摘要

化学扰动筛选提供了识别可操作的癌症特异性脆弱性的可能性。然而,大多数激酶抑制剂或其他癌症靶点会产生多药理学效应,这使得直接从药物反应表型确定靶点依赖性变得复杂。在这项研究中,我们开发了一种化学系统生物学方法,该方法集成了综合药物敏感性和选择性分析,以提供对单靶点和多靶点致癌信号成瘾的功能见解。当应用于21种乳腺癌细胞系时,用40种激酶抑制剂进行干扰,亚型特异性成瘾模式与患者衍生亚型一致,同时在异质乳腺癌之间显示出相当大的差异。对这些预测的实验验证揭示了激酶靶点之间的一些共同依赖性,导致它们的抑制剂之间出现意想不到的协同组合,例如在三阴性基底样HCC1937细胞系中,达沙替尼和阿西替尼。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Systematic Mapping of Kinase Addiction Combinations in Breast Cancer Cells by Integrating Drug Sensitivity and Selectivity Profiles.

Chemical perturbation screens offer the possibility to identify actionable sets of cancer-specific vulnerabilities. However, most inhibitors of kinases or other cancer targets result in polypharmacological effects, which complicate the identification of target dependencies directly from the drug-response phenotypes. In this study, we developed a chemical systems biology approach that integrates comprehensive drug sensitivity and selectivity profiling to provide functional insights into both single and multi-target oncogenic signal addictions. When applied to 21 breast cancer cell lines, perturbed with 40 kinase inhibitors, the subtype-specific addiction patterns clustered in agreement with patient-derived subtypes, while showing considerable variability between the heterogeneous breast cancers. Experimental validation of the top predictions revealed a number of co-dependencies between kinase targets that led to unexpected synergistic combinations between their inhibitors, such as dasatinib and axitinib in the triple-negative basal-like HCC1937 cell line.

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来源期刊
Chemistry & biology
Chemistry & biology 生物-生化与分子生物学
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