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Chromatin interactome mapping at 139 independent breast cancer risk signals.
Beesley, Jonathan; Sivakumaran, Haran; Moradi Marjaneh, Mahdi; Lima, Luize G; Hillman, Kristine M; Kaufmann, Susanne; Tuano, Natasha; Hussein, Nehal; Ham, Sunyoung; Mukhopadhyay, Pamela; Kazakoff, Stephen; Lee, Jason S; Michailidou, Kyriaki; Barnes, Daniel R; Antoniou, Antonis C; Fachal, Laura; Dunning, Alison M; Easton, Douglas F; Waddell, Nicola; Rosenbluh, Joseph; Möller, Andreas; Chenevix-Trench, Georgia; French, Juliet D; Edwards, Stacey L.
Afiliação
  • Beesley J; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Sivakumaran H; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Moradi Marjaneh M; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Lima LG; Current address: UK Dementia Research Institute, Imperial College London, London, UK.
  • Hillman KM; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Kaufmann S; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Tuano N; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Hussein N; Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Australia.
  • Ham S; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Mukhopadhyay P; Faculty of Medicine, The University of Queensland, Brisbane, Australia.
  • Kazakoff S; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Lee JS; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Michailidou K; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Barnes DR; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Antoniou AC; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Fachal L; Department of Electron Microscopy/Molecular Pathology, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus.
  • Dunning AM; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Easton DF; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Waddell N; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
  • Rosenbluh J; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
  • Möller A; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK.
  • Chenevix-Trench G; Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK.
  • French JD; Cancer Program, QIMR Berghofer Medical Research Institute, Brisbane, Australia.
  • Edwards SL; Department of Biochemistry and Molecular Biology, Monash University, Melbourne, Australia.
Genome Biol ; 21(1): 8, 2020 01 07.
Article em En | MEDLINE | ID: mdl-31910858
BACKGROUND: Genome-wide association studies have identified 196 high confidence independent signals associated with breast cancer susceptibility. Variants within these signals frequently fall in distal regulatory DNA elements that control gene expression. RESULTS: We designed a Capture Hi-C array to enrich for chromatin interactions between the credible causal variants and target genes in six human mammary epithelial and breast cancer cell lines. We show that interacting regions are enriched for open chromatin, histone marks for active enhancers, and transcription factors relevant to breast biology. We exploit this comprehensive resource to identify candidate target genes at 139 independent breast cancer risk signals and explore the functional mechanism underlying altered risk at the 12q24 risk region. CONCLUSIONS: Our results demonstrate the power of combining genetics, computational genomics, and molecular studies to rationalize the identification of key variants and candidate target genes at breast cancer GWAS signals.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Cromatina Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Neoplasias da Mama / Cromatina Tipo de estudo: Etiology_studies / Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Ano de publicação: 2020 Tipo de documento: Article