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dc.contributor.author공구-
dc.date.accessioned2019-11-22T07:03:24Z-
dc.date.available2019-11-22T07:03:24Z-
dc.date.issued2017-04-
dc.identifier.citationNATURE MEDICINE, v. 23, no. 4, page. 517-525en_US
dc.identifier.issn1078-8956-
dc.identifier.issn1546-170X-
dc.identifier.urihttps://www.nature.com/articles/nm.4292-
dc.identifier.urihttps://repository.hanyang.ac.kr/handle/20.500.11754/113626-
dc.description.abstractApproximately 1-5% of breast cancers are attributed to inherited mutations in BRCA1 or BRCA2 and are selectively sensitive to poly(ADP-ribose) polymerase (PARP) inhibitors. In other cancer types, germline and/or somatic mutations in BRCA1 and/or BRCA2 (BRCA1/BRCA2) also confer selective sensitivity to PARP inhibitors. Thus, assays to detect BRCA1/BRCA2-deficient tumors have been sought. Recently, somatic substitution, insertion/deletion and rearrangement patterns, or 'mutational signatures', were associated with BRCA1/BRCA2 dysfunction. Herein we used a lasso logistic regression model to identify six distinguishing mutational signatures predictive of BRCA1/BRCA2 deficiency. A weighted model called HRDetect was developed to accurately detect BRCA1/BRCA2-deficient samples. HRDetect identifies BRCA1/BRCA2-deficient tumors with 98.7% sensitivity (area under the curve (AUC) = 0.98). Application of this model in a cohort of 560 individuals with breast cancer, of whom 22 were known to carry a germline BRCA1 or BRCA2 mutation, allowed us to identify an additional 22 tumors with somatic loss of BRCA1 or BRCA2 and 47 tumors with functional BRCA1/BRCA2 deficiency where no mutation was detected. We validated HRDetect on independent cohorts of breast, ovarian and pancreatic cancers and demonstrated its efficacy in alternative sequencing strategies. Integrating all of the classes of mutational signatures thus reveals a larger proportion of individuals with breast cancer harboring BRCA1/BRCA2 deficiency (up to 22%) than hitherto appreciated (similar to 1-5%) who could have selective therapeutic sensitivity to PARP inhibition.en_US
dc.description.sponsorshipThis work has been performed on data that were previously published. They were generated and funded through the ICGC Breast Cancer Working group by the Breast Cancer Somatic Genetics Study (BASIS), a European research project funded by the European Community's Seventh Framework Programme (FP7/2010-2014) under grant agreement number 242006; the Triple Negative project funded by the Wellcome Trust (grant reference 077012/Z/05/Z) and the HER2+ project funded by Institut National du Cancer (INCa) in France (grants 226-2009, 02-2011, 41-2012, 144-2008, 06-2012). The ICGC Asian Breast Cancer Project was funded through a grant of the Korean Health Technology R&D Project, Ministry of Health & Welfare, Republic of Korea (A111218-SC01). The Oslo Breast Cancer Research Consortium (OSBREAC), Norway (http://www.osbreac.no/), contributed samples to the study. D.G. was supported by the EU-FP7-SUPPRESSTEM project. A.L.R. is partially supported by the Dana-Farber/Harvard Cancer Center SPORE in Breast Cancer (NIH/NCI 5 P50 CA168504-02). A.S. was supported by Cancer Genomics Netherlands (CGC.nl) through a grant from the Netherlands Organisation of Scientific research (NWO). C.S. is supported by a grant from the Breast Cancer Research Foundation. E.B. was funded by EMBL. A.T. acknowledges infrastructure support funding from the NIHR Biomedical Research Centres at Guy's and St Thomas' and Royal Marsden Hospital NHS Foundation Trusts. G.K. is supported by National Research Foundation of Korea (NRF) grants funded by the Korean government (NRF 2015R1A2A1A10052578). S.N.-Z. is a Wellcome Beit Fellow and personally funded by a Wellcome Trust Intermediate Fellowship (WT100183MA). Finally, we would like to acknowledge all members of the ICGC Breast Cancer Working Group and ICGC Asian Breast Cancer Project, for without the foresight of engaging in this scale of collaboration we would not have gained these insights.en_US
dc.language.isoen_USen_US
dc.publisherNATURE PUBLISHING GROUPen_US
dc.subjectCOPY NUMBER ANALYSISen_US
dc.subjectBREAST-CANCERen_US
dc.subjectREPAIR DEFECTSen_US
dc.subjectCHEMOTHERAPYen_US
dc.subjectPREVALENCEen_US
dc.subjectRESISTANCEen_US
dc.subjectLANDSCAPEen_US
dc.subjectOLAPARIBen_US
dc.subjectTHERAPYen_US
dc.subjectGENOMESen_US
dc.titleHRDetect is a predictor of BRCA1 and BRCA2 deficiency based on mutational signaturesen_US
dc.typeArticleen_US
dc.relation.no4-
dc.relation.volume23-
dc.identifier.doi10.1038/nm.4292-
dc.relation.page517-517-
dc.relation.journalNATURE MEDICINE-
dc.contributor.googleauthorDavies, Helen-
dc.contributor.googleauthorGlodzik, Dominik-
dc.contributor.googleauthorMorganella, Sandro-
dc.contributor.googleauthorYates, Lucy R.-
dc.contributor.googleauthorStaaf, Johan-
dc.contributor.googleauthorZou, Xueqing-
dc.contributor.googleauthorRamakrishna, Manasa-
dc.contributor.googleauthorMartin, Sancha-
dc.contributor.googleauthorBoyault, Sandrine-
dc.contributor.googleauthorKong, Gu-
dc.relation.code2017002503-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF MEDICINE[S]-
dc.sector.departmentDEPARTMENT OF MEDICINE-
dc.identifier.pidgkong-
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COLLEGE OF MEDICINE[S](의과대학) > MEDICINE(의학과) > Articles
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