Systematic Mapping of Kinase Addiction Combinations in Breast Cancer Cells by Integrating Drug Sensitivity and Selectivity Profiles. Issue 8 (20th August 2015) - Szwajda, Agnieszka; Gautam, Prson; Karhinen, Leena; Jha, Sawan Kumar; Saarela, Jani; Shakyawar, Sushil; Turunen, Laura; Yadav, Bhagwan; Tang, Jing; Wennerberg, Krister; Aittokallio, Tero
Summary: 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. Graphical Abstract: Highlights: Chemical systems biology tool for mapping kinase signal addictions in cancer cells Makes use of a network of interactions between kinase inhibitors and their targets We detected subtype-specific addiction patterns across 21 breast cancer cell lines We identified both co-essential target pairs and synergistic drug combinations Abstract : Szwajda et al. developed a systems biology approach that integrates drug selectivity and sensitivity profiles to identify pharmacologically actionable signal addictions, both single and combinatorial, in given cancer cells. Such druggable molecular vulnerabilities may lead to stratified therapeutic strategies in various cancer subtypes.