Bioinformatics-driven discovery of rational combination for overcoming EGFR-mutant lung cancer resistance to EGFR therapy
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Jihye | - |
dc.contributor.author | Vasu, Vihas T. | - |
dc.contributor.author | Mishra, Rangnath | - |
dc.contributor.author | Singleton, Katherine R. | - |
dc.contributor.author | Yoo, Minjae | - |
dc.contributor.author | Leach, Sonia M. | - |
dc.contributor.author | Farias-Hesson, Eveline | - |
dc.contributor.author | Mason, Robert J. | - |
dc.contributor.author | Kang, Jaewoo | - |
dc.contributor.author | Ramamoorthy, Preveen | - |
dc.contributor.author | Kern, Jeffrey A. | - |
dc.contributor.author | Heasley, Lynn E. | - |
dc.contributor.author | Finigan, James H. | - |
dc.contributor.author | Tan, Aik Choon | - |
dc.date.accessioned | 2021-09-05T05:29:29Z | - |
dc.date.available | 2021-09-05T05:29:29Z | - |
dc.date.created | 2021-06-15 | - |
dc.date.issued | 2014-09-01 | - |
dc.identifier.issn | 1367-4803 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/97440 | - |
dc.description.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. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | OXFORD UNIV PRESS | - |
dc.subject | GROWTH-FACTOR RECEPTOR | - |
dc.subject | GENE-EXPRESSION SIGNATURES | - |
dc.subject | KINASE INHIBITOR SELECTIVITY | - |
dc.subject | SYNTHETIC LETHAL | - |
dc.subject | CELLS | - |
dc.subject | MECHANISM | - |
dc.subject | MODULATOR | - |
dc.subject | DISEASE | - |
dc.subject | GENOME | - |
dc.subject | SEQ | - |
dc.title | Bioinformatics-driven discovery of rational combination for overcoming EGFR-mutant lung cancer resistance to EGFR therapy | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kang, Jaewoo | - |
dc.contributor.affiliatedAuthor | Tan, Aik Choon | - |
dc.identifier.doi | 10.1093/bioinformatics/btu323 | - |
dc.identifier.scopusid | 2-s2.0-84907027923 | - |
dc.identifier.wosid | 000342912400042 | - |
dc.identifier.bibliographicCitation | BIOINFORMATICS, v.30, no.17, pp.2393 - 2398 | - |
dc.relation.isPartOf | BIOINFORMATICS | - |
dc.citation.title | BIOINFORMATICS | - |
dc.citation.volume | 30 | - |
dc.citation.number | 17 | - |
dc.citation.startPage | 2393 | - |
dc.citation.endPage | 2398 | - |
dc.type.rims | ART | - |
dc.type.docType | Article; Proceedings Paper | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Biochemistry & Molecular Biology | - |
dc.relation.journalResearchArea | Biotechnology & Applied Microbiology | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Mathematical & Computational Biology | - |
dc.relation.journalResearchArea | Mathematics | - |
dc.relation.journalWebOfScienceCategory | Biochemical Research Methods | - |
dc.relation.journalWebOfScienceCategory | Biotechnology & Applied Microbiology | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Interdisciplinary Applications | - |
dc.relation.journalWebOfScienceCategory | Mathematical & Computational Biology | - |
dc.relation.journalWebOfScienceCategory | Statistics & Probability | - |
dc.subject.keywordPlus | GROWTH-FACTOR RECEPTOR | - |
dc.subject.keywordPlus | GENE-EXPRESSION SIGNATURES | - |
dc.subject.keywordPlus | KINASE INHIBITOR SELECTIVITY | - |
dc.subject.keywordPlus | SYNTHETIC LETHAL | - |
dc.subject.keywordPlus | CELLS | - |
dc.subject.keywordPlus | MECHANISM | - |
dc.subject.keywordPlus | MODULATOR | - |
dc.subject.keywordPlus | DISEASE | - |
dc.subject.keywordPlus | GENOME | - |
dc.subject.keywordPlus | SEQ | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.