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Exome sequencing identifies breast cancer susceptibility genes and defines the contribution of coding variants to breast cancer risk

Wilcox N 1 , Dumont M 2 , González-Neira A 3 , Carvalho S 1 , Joly Beauparlant C 2 , Crotti M 1 Show all authors , Luccarini C 4 , Soucy P 2 , Dubois S 2 , Nuñez-Torres R 3 , Pita G 3 , Gardner EJ 5 , Dennis J 1 , Alonso MR 3 , Álvarez N 3 , Baynes C 4 , Collin-Deschesnes AC 2 , Desjardins S 2 , Becher H 6 , Behrens S 7 , Bolla MK 1 , Castelao JE 8 , Chang-Claude J 7 , Cornelissen S 9 , Dörk T 10 , Engel C 11 , Gago-Dominguez M 12 , Guénel P 13 , Hadjisavvas A 14 , Hahnen E 15 , Hartman M 16 , Herráez B 3 , SGBCC Investigators , Jung A 7 , Keeman R 9 , Kiechle M 17 , Li J 18 , Loizidou MA 14 , Lush M 1 , Michailidou K 1 , Panayiotidis MI 14 , Sim X 16 , Teo SH 19 , Tyrer JP 4 , van der Kolk LE 20 , Wahlström C 21 , Wang Q 1 , Perry JRB 5 , Benitez J 22 , Schmidt MK 9 , Schmutzler RK 15 , Pharoah PDP 1 , Droit A 2 , Dunning AM 4 , Kvist A 21 , Devilee P 23 , Easton DF 24 , Simard J 2

Affiliations 

  • 1 Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
  • 2 Genomics Center, Centre Hospitalier Universitaire de Québec-Université Laval Research Center, Québec City, Quebec, Canada
  • 3 Human Genotyping Unit-CeGen, Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
  • 4 Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, UK
  • 5 MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
  • 6 Institute of Medical Biometry and Epidemiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
  • 7 Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
  • 8 Oncology and Genetics Unit, Instituto de Investigación Sanitaria Galicia Sur (IISGS), Xerencia de Xestion Integrada de Vigo-SERGAS, Vigo, Spain
  • 9 Division of Molecular Pathology, The Netherlands Cancer Institute, Amsterdam, the Netherlands
  • 10 Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
  • 11 Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, Leipzig, Germany
  • 12 Cancer Genetics and Epidemiology Group, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS) Foundation, Complejo Hospitalario Universitario de Santiago, SERGAS, Santiago de Compostela, Spain
  • 13 Team 'Exposome and Heredity,' CESP, Gustave Roussy, INSERM, University Paris-Saclay, UVSQ, Villejuif, France
  • 14 Department of Cancer Genetics, Therapeutics and Ultrastructural Pathology, The Cyprus Institute of Neurology & Genetics, Nicosia, Cyprus
  • 15 Center for Familial Breast and Ovarian Cancer, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
  • 16 Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore City, Singapore
  • 17 Division of Gynaecology and Obstetrics, Klinikum rechts der Isar der Technischen Universität München, Munich, Germany
  • 18 Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore City, Singapore. lijm1@gis.a-star.edu.sg
  • 19 Breast Cancer Research Programme, Cancer Research Malaysia, Subang Jaya, Malaysia
  • 20 Family Cancer Clinic, The Netherlands Cancer Institute-Antoni van Leeuwenhoek hospital, Amsterdam, the Netherlands
  • 21 Division of Oncology, Department of Clinical Sciences Lund, Lund University, Lund, Sweden
  • 22 Human Genetics Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
  • 23 Department of Pathology, Leiden University Medical Center, Leiden, the Netherlands
  • 24 Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK. dfe20@medschl.cam.ac.uk
Nat Genet, 2023 Sep;55(9):1435-1439.
PMID: 37592023 DOI: 10.1038/s41588-023-01466-z

Abstract

Linkage and candidate gene studies have identified several breast cancer susceptibility genes, but the overall contribution of coding variation to breast cancer is unclear. To evaluate the role of rare coding variants more comprehensively, we performed a meta-analysis across three large whole-exome sequencing datasets, containing 26,368 female cases and 217,673 female controls. Burden tests were performed for protein-truncating and rare missense variants in 15,616 and 18,601 genes, respectively. Associations between protein-truncating variants and breast cancer were identified for the following six genes at exome-wide significance (P 

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