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Bioinformatics-driven discovery of rational combination for overcoming EGFR-mutant lung cancer resistance to EGFR therapy. | LitMetric

Bioinformatics-driven discovery of rational combination for overcoming EGFR-mutant lung cancer resistance to EGFR therapy.

Bioinformatics

Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea Division of Medical Oncology, Department of Medicine, Translational Bioinformatics and Cancer Systems Biology Laboratory, University of Colorado Anschutz Medical Campus, 80045 Aurora, Department of Medicine, National Jewish Health, 80206 Denver, Department of Craniofacial Biology, School of Dental Medicine, Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado Anschutz Medical Campus, 80045 Aurora, CO, USA and Department of Computer Science and Engineering, Korea University, Seoul 136-713, Korea.

Published: September 2014

Motivation: Non-small-cell lung cancer (NSCLC) is the leading cause of cancer death in the United States. Targeted tyrosine kinase inhibitors (TKIs) directed against the epidermal growth factor receptor (EGFR) have been widely and successfully used in treating NSCLC patients with activating EGFR mutations. Unfortunately, the duration of response is short-lived, and all patients eventually relapse by acquiring resistance mechanisms.

Result: We performed an integrative systems biology approach to determine essential kinases that drive EGFR-TKI resistance in cancer cell lines. We used a series of bioinformatics methods to analyze and integrate the functional genetics screen and RNA-seq data to identify a set of kinases that are critical in survival and proliferation in these TKI-resistant lines. By connecting the essential kinases to compounds using a novel kinase connectivity map (K-Map), we identified and validated bosutinib as an effective compound that could inhibit proliferation and induce apoptosis in TKI-resistant lines. A rational combination of bosutinib and gefitinib showed additive and synergistic effects in cancer cell lines resistant to EGFR TKI alone.

Conclusions: We have demonstrated a bioinformatics-driven discovery roadmap for drug repurposing and development in overcoming resistance in EGFR-mutant NSCLC, which could be generalized to other cancer types in the era of personalized medicine.

Availability And Implementation: K-Map can be accessible at: http://tanlab.ucdenver.edu/kMap.

Supplementary Information: Supplementary data are available at Bioinformatics online.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4147888PMC
http://dx.doi.org/10.1093/bioinformatics/btu323DOI Listing

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