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

Authors
Kim, JihyeVasu, Vihas T.Mishra, RangnathSingleton, Katherine R.Yoo, MinjaeLeach, Sonia M.Farias-Hesson, EvelineMason, Robert J.Kang, JaewooRamamoorthy, PreveenKern, Jeffrey A.Heasley, Lynn E.Finigan, James H.Tan, Aik Choon
Issue Date
1-9월-2014
Publisher
OXFORD UNIV PRESS
Citation
BIOINFORMATICS, v.30, no.17, pp.2393 - 2398
Indexed
SCIE
SCOPUS
Journal Title
BIOINFORMATICS
Volume
30
Number
17
Start Page
2393
End Page
2398
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/97440
DOI
10.1093/bioinformatics/btu323
ISSN
1367-4803
Abstract
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.
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