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, Prson Gautam, Leena Karhinen, Sawan Kumar Jha, Jani Saarela, Sushil Shakyawar, Laura Turunen, Bhagwan Yadav, Jing Tang, Krister Wennerberg, 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":"22 8","pages":"1144-55"},"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, Prson Gautam, Leena Karhinen, Sawan Kumar Jha, Jani Saarela, Sushil Shakyawar, Laura Turunen, Bhagwan Yadav, Jing Tang, Krister Wennerberg, 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\":\"22 8\",\"pages\":\"1144-55\"},\"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}
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.