1. Academic Validation
  2. Systematic Mapping of Kinase Addiction Combinations in Breast Cancer Cells by Integrating Drug Sensitivity and Selectivity Profiles

Systematic Mapping of Kinase Addiction Combinations in Breast Cancer Cells by Integrating Drug Sensitivity and Selectivity Profiles

  • Chem Biol. 2015 Aug 20;22(8):1144-55. doi: 10.1016/j.chembiol.2015.06.021.
Agnieszka Szwajda 1 Prson Gautam 1 Leena Karhinen 1 Sawan Kumar Jha 1 Jani Saarela 1 Sushil Shakyawar 1 Laura Turunen 1 Bhagwan Yadav 1 Jing Tang 1 Krister Wennerberg 2 Tero Aittokallio 3
Affiliations

Affiliations

  • 1 Institute for Molecular Medicine Finland, FIMM, University of Helsinki, 00014 Helsinki, Finland.
  • 2 Institute for Molecular Medicine Finland, FIMM, University of Helsinki, 00014 Helsinki, Finland. Electronic address: krister.wennerberg@fimm.fi.
  • 3 Institute for Molecular Medicine Finland, FIMM, University of Helsinki, 00014 Helsinki, Finland. Electronic address: tero.aittokallio@fimm.fi.
Abstract

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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