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
{"title":"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。","authors":"Agnieszka Szwajda,&nbsp;Prson Gautam,&nbsp;Leena Karhinen,&nbsp;Sawan Kumar Jha,&nbsp;Jani Saarela,&nbsp;Sushil Shakyawar,&nbsp;Laura Turunen,&nbsp;Bhagwan Yadav,&nbsp;Jing Tang,&nbsp;Krister Wennerberg,&nbsp;Tero Aittokallio","doi":"10.1016/j.chembiol.2015.06.021","DOIUrl":null,"url":null,"abstract":"<p><p>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. </p>","PeriodicalId":9772,"journal":{"name":"Chemistry & biology","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2015-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.chembiol.2015.06.021","citationCount":"22","resultStr":"{\"title\":\"Systematic Mapping of Kinase Addiction Combinations in Breast Cancer Cells by Integrating Drug Sensitivity and Selectivity Profiles.\",\"authors\":\"Agnieszka Szwajda,&nbsp;Prson Gautam,&nbsp;Leena Karhinen,&nbsp;Sawan Kumar Jha,&nbsp;Jani Saarela,&nbsp;Sushil Shakyawar,&nbsp;Laura Turunen,&nbsp;Bhagwan Yadav,&nbsp;Jing Tang,&nbsp;Krister Wennerberg,&nbsp;Tero Aittokallio\",\"doi\":\"10.1016/j.chembiol.2015.06.021\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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. </p>\",\"PeriodicalId\":9772,\"journal\":{\"name\":\"Chemistry & biology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.chembiol.2015.06.021\",\"citationCount\":\"22\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chemistry & biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1016/j.chembiol.2015.06.021\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2015/7/23 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chemistry & biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.chembiol.2015.06.021","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2015/7/23 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
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。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
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.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Chemistry & biology
Chemistry & biology 生物-生化与分子生物学
自引率
0.00%
发文量
0
审稿时长
4-8 weeks
期刊最新文献
ADP-ribosylserine hydrolase ARH3 of Latimeria chalumnae in complex with ADP-ribosyl-L-arginine Halophilic Protein Adaptation Results from Synergistic Residue-Ion Interactions in the Folded and Unfolded States. Human ISPD Is a Cytidyltransferase Required for Dystroglycan O-Mannosylation. Reciprocal Regulation of ERα and ERβ Stability and Activity by Diptoindonesin G. Biosynthesis of Neocarazostatin A Reveals the Sequential Carbazole Prenylation and Hydroxylation in the Tailoring Steps.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1