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Functional Proteomics and Deep Network Interrogation Reveal a Complex Mechanism of Action of Midostaurin in Lung Cancer Cells.
- Source :
-
Molecular & cellular proteomics : MCP [Mol Cell Proteomics] 2018 Dec; Vol. 17 (12), pp. 2434-2447. Date of Electronic Publication: 2018 Sep 14. - Publication Year :
- 2018
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Abstract
- Lung cancer is associated with high prevalence and mortality, and despite significant successes with targeted drugs in genomically defined subsets of lung cancer and immunotherapy, the majority of patients currently does not benefit from these therapies. Through a targeted drug screen, we found the recently approved multi-kinase inhibitor midostaurin to have potent activity in several lung cancer cells independent of its intended target, PKC, or a specific genomic marker. To determine the underlying mechanism of action we applied a layered functional proteomics approach and a new data integration method. Using chemical proteomics, we identified multiple midostaurin kinase targets in these cells. Network-based integration of these targets with quantitative tyrosine and global phosphoproteomics data using protein-protein interactions from the STRING database suggested multiple targets are relevant for the mode of action of midostaurin. Subsequent functional validation using RNA interference and selective small molecule probes showed that simultaneous inhibition of TBK1, PDPK1 and AURKA was required to elicit midostaurin's cellular effects. Immunoblot analysis of downstream signaling nodes showed that combined inhibition of these targets altered PI3K/AKT and cell cycle signaling pathways that in part converged on PLK1. Furthermore, rational combination of midostaurin with the potent PLK1 inhibitor BI2536 elicited strong synergy. Our results demonstrate that combination of complementary functional proteomics approaches and subsequent network-based data integration can reveal novel insight into the complex mode of action of multi-kinase inhibitors, actionable targets for drug discovery and cancer vulnerabilities. Finally, we illustrate how this knowledge can be used for the rational design of synergistic drug combinations with high potential for clinical translation.<br /> (© 2018 Ctortecka et al.)
- Subjects :
- Biomarkers, Tumor antagonists & inhibitors
Cell Cycle drug effects
Cell Line, Tumor
Cell Survival drug effects
Drug Discovery
Drug Synergism
Humans
RNA Interference
Signal Transduction drug effects
Staurosporine pharmacology
Polo-Like Kinase 1
Aurora Kinase A antagonists & inhibitors
Carcinoma, Non-Small-Cell Lung metabolism
Cell Cycle Proteins antagonists & inhibitors
Lung Neoplasms metabolism
Protein Serine-Threonine Kinases antagonists & inhibitors
Protein-Tyrosine Kinases antagonists & inhibitors
Proteomics methods
Proto-Oncogene Proteins antagonists & inhibitors
Staurosporine analogs & derivatives
Subjects
Details
- Language :
- English
- ISSN :
- 1535-9484
- Volume :
- 17
- Issue :
- 12
- Database :
- MEDLINE
- Journal :
- Molecular & cellular proteomics : MCP
- Publication Type :
- Academic Journal
- Accession number :
- 30217950
- Full Text :
- https://doi.org/10.1074/mcp.RA118.000713