HER family kinase domain mutations promote tumor progression and can predict response to treatment in human breast cancer

Handle URI:
http://hdl.handle.net/10754/556829
Title:
HER family kinase domain mutations promote tumor progression and can predict response to treatment in human breast cancer
Authors:
Boulbes, Delphine R.; Arold, Stefan T. ( 0000-0001-5278-0668 ) ; Chauhan, Gaurav B.; Blachno, Korina V.; Deng, Nanfu; Chang, Wei-Chao; Jin, Quanri; Huang, Tzu-Hsuan; Hsu, Jung-Mao; Brady, Samuel W.; Bartholomeusz, Chandra; Ladbury, John E.; Stone, Steve; Yu, Dihua; Hung, Mien-Chie; Esteva, Francisco J.
Abstract:
Resistance to HER2-targeted therapies remains a major obstacle in the treatment of HER2-overexpressing breast cancer. Understanding the molecular pathways that contribute to the development of drug resistance is needed to improve the clinical utility of novel agents, and to predict the success of targeted personalized therapy based on tumor-specific mutations. Little is known about the clinical significance of HER family mutations in breast cancer. Because mutations within HER1/EGFR are predictive of response to tyrosine kinase inhibitors (TKI) in lung cancer, we investigated whether mutations in HER family kinase domains are predictive of response to targeted therapy in HER2-overexpressing breast cancer. We sequenced the HER family kinase domains from 76 HER2-overexpressing invasive carcinomas and identified 12 missense variants. Patients whose tumors carried any of these mutations did not respond to HER2 directed therapy in the metastatic setting. We developed mutant cell lines and used structural analyses to determine whether changes in protein conformation could explain the lack of response to therapy. We also functionally studied all HER2 mutants and showed that they conferred an aggressive phenotype and altered effects of the TKI lapatinib. Our data demonstrate that mutations in the finely tuned HER kinase domains play a critical function in breast cancer progression and may serve as prognostic and predictive markers.
KAUST Department:
Biological and Environmental Sciences and Engineering (BESE) Division; Computational Bioscience Research Center (CBRC)
Citation:
HER family kinase domain mutations promote tumor progression and can predict response to treatment in human breast cancer 2015, 9 (3):586 Molecular Oncology
Journal:
Molecular Oncology
Issue Date:
11-Nov-2014
DOI:
10.1016/j.molonc.2014.10.011
Type:
Article
ISSN:
15747891
Additional Links:
http://linkinghub.elsevier.com/retrieve/pii/S1574789114002506
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC); Biological and Environmental Sciences and Engineering (BESE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorBoulbes, Delphine R.en
dc.contributor.authorArold, Stefan T.en
dc.contributor.authorChauhan, Gaurav B.en
dc.contributor.authorBlachno, Korina V.en
dc.contributor.authorDeng, Nanfuen
dc.contributor.authorChang, Wei-Chaoen
dc.contributor.authorJin, Quanrien
dc.contributor.authorHuang, Tzu-Hsuanen
dc.contributor.authorHsu, Jung-Maoen
dc.contributor.authorBrady, Samuel W.en
dc.contributor.authorBartholomeusz, Chandraen
dc.contributor.authorLadbury, John E.en
dc.contributor.authorStone, Steveen
dc.contributor.authorYu, Dihuaen
dc.contributor.authorHung, Mien-Chieen
dc.contributor.authorEsteva, Francisco J.en
dc.date.accessioned2015-06-12T06:29:53Zen
dc.date.available2015-06-12T06:29:53Zen
dc.date.issued2014-11-11en
dc.identifier.citationHER family kinase domain mutations promote tumor progression and can predict response to treatment in human breast cancer 2015, 9 (3):586 Molecular Oncologyen
dc.identifier.issn15747891en
dc.identifier.doi10.1016/j.molonc.2014.10.011en
dc.identifier.urihttp://hdl.handle.net/10754/556829en
dc.description.abstractResistance to HER2-targeted therapies remains a major obstacle in the treatment of HER2-overexpressing breast cancer. Understanding the molecular pathways that contribute to the development of drug resistance is needed to improve the clinical utility of novel agents, and to predict the success of targeted personalized therapy based on tumor-specific mutations. Little is known about the clinical significance of HER family mutations in breast cancer. Because mutations within HER1/EGFR are predictive of response to tyrosine kinase inhibitors (TKI) in lung cancer, we investigated whether mutations in HER family kinase domains are predictive of response to targeted therapy in HER2-overexpressing breast cancer. We sequenced the HER family kinase domains from 76 HER2-overexpressing invasive carcinomas and identified 12 missense variants. Patients whose tumors carried any of these mutations did not respond to HER2 directed therapy in the metastatic setting. We developed mutant cell lines and used structural analyses to determine whether changes in protein conformation could explain the lack of response to therapy. We also functionally studied all HER2 mutants and showed that they conferred an aggressive phenotype and altered effects of the TKI lapatinib. Our data demonstrate that mutations in the finely tuned HER kinase domains play a critical function in breast cancer progression and may serve as prognostic and predictive markers.en
dc.relation.urlhttp://linkinghub.elsevier.com/retrieve/pii/S1574789114002506en
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Molecular Oncology. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Molecular Oncology, 11 November 2014. DOI: 10.1016/j.molonc.2014.10.011en
dc.subjectBiomarkeren
dc.subjectDrug resistanceen
dc.subjectLapatiniben
dc.subjectKinase domainen
dc.subjectHER family mutationen
dc.titleHER family kinase domain mutations promote tumor progression and can predict response to treatment in human breast canceren
dc.typeArticleen
dc.contributor.departmentBiological and Environmental Sciences and Engineering (BESE) Divisionen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.identifier.journalMolecular Oncologyen
dc.eprint.versionPost-printen
dc.contributor.institutionDepartments of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USAen
dc.contributor.institutionDepartments of Biochemistry & Molecular Biology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USAen
dc.contributor.institutionDepartments of Center for Biomolecular Structure and Function, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USAen
dc.contributor.institutionDepartments of Molecular & Cellular Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USAen
dc.contributor.institutionGraduate Institute of Cancer Biology and Center for Molecular Medicine, China Medical University Hospital, Taichung, 404 Taiwanen
dc.contributor.institutionMyriad Genetics, Salt Lake City, UT 84108, USAen
dc.contributor.institutionLaura and Isaac Perlmutter Cancer Center, New York University Langone Medical Center, 160 E. 34th Street, New York, NY 10016, USAen
dc.contributor.institutionSchool of Molecular and Cell Biology, University of Leeds, Leeds LS2 9jT, UKen
kaust.authorArold, Stefan T.en
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