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Kataoka M. Mammographic Density for Personalized Breast Cancer Risk. Radiology 2023; 306:e222129. [PMID: 36125381 DOI: 10.1148/radiol.222129] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Affiliation(s)
- Masako Kataoka
- From the Department of Diagnostic Imaging and Nuclear Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoinkawaharacho, Sakyo-ku, Kyoto 606-8507, Japan
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Dumont M, Weber-Lassalle N, Joly-Beauparlant C, Ernst C, Droit A, Feng BJ, Dubois S, Collin-Deschesnes AC, Soucy P, Vallée M, Fournier F, Lemaçon A, Adank MA, Allen J, Altmüller J, Arnold N, Ausems MGEM, Berutti R, Bolla MK, Bull S, Carvalho S, Cornelissen S, Dufault MR, Dunning AM, Engel C, Gehrig A, Geurts-Giele WRR, Gieger C, Green J, Hackmann K, Helmy M, Hentschel J, Hogervorst FBL, Hollestelle A, Hooning MJ, Horváth J, Ikram MA, Kaulfuß S, Keeman R, Kuang D, Luccarini C, Maier W, Martens JWM, Niederacher D, Nürnberg P, Ott CE, Peters A, Pharoah PDP, Ramirez A, Ramser J, Riedel-Heller S, Schmidt G, Shah M, Scherer M, Stäbler A, Strom TM, Sutter C, Thiele H, van Asperen CJ, van der Kolk L, van der Luijt RB, Volk AE, Wagner M, Waisfisz Q, Wang Q, Wang-Gohrke S, Weber BHF, Devilee P, Tavtigian S, Bader GD, Meindl A, Goldgar DE, Andrulis IL, Schmutzler RK, Easton DF, Schmidt MK, Hahnen E, Simard J. Uncovering the Contribution of Moderate-Penetrance Susceptibility Genes to Breast Cancer by Whole-Exome Sequencing and Targeted Enrichment Sequencing of Candidate Genes in Women of European Ancestry. Cancers (Basel) 2022; 14:cancers14143363. [PMID: 35884425 PMCID: PMC9317824 DOI: 10.3390/cancers14143363] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 06/29/2022] [Accepted: 07/01/2022] [Indexed: 01/27/2023] Open
Abstract
Rare variants in at least 10 genes, including BRCA1, BRCA2, PALB2, ATM, and CHEK2, are associated with increased risk of breast cancer; however, these variants, in combination with common variants identified through genome-wide association studies, explain only a fraction of the familial aggregation of the disease. To identify further susceptibility genes, we performed a two-stage whole-exome sequencing study. In the discovery stage, samples from 1528 breast cancer cases enriched for breast cancer susceptibility and 3733 geographically matched unaffected controls were sequenced. Using five different filtering and gene prioritization strategies, 198 genes were selected for further validation. These genes, and a panel of 32 known or suspected breast cancer susceptibility genes, were assessed in a validation set of 6211 cases and 6019 controls for their association with risk of breast cancer overall, and by estrogen receptor (ER) disease subtypes, using gene burden tests applied to loss-of-function and rare missense variants. Twenty genes showed nominal evidence of association (p-value < 0.05) with either overall or subtype-specific breast cancer. Our study had the statistical power to detect susceptibility genes with effect sizes similar to ATM, CHEK2, and PALB2, however, it was underpowered to identify genes in which susceptibility variants are rarer or confer smaller effect sizes. Larger sample sizes would be required in order to identify such genes.
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Affiliation(s)
- Martine Dumont
- Genomics Center, CHU de Québec-Université Laval Research Center, 2705 Laurier Boulevard, Quebec City, QC GIV 4G2, Canada; (M.D.); (C.J.-B.); (A.D.); (S.D.); (A.-C.C.-D.); (P.S.); (M.V.); (F.F.); (A.L.)
| | - Nana Weber-Lassalle
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany; (N.W.-L.); (C.E.); (R.K.S.); (E.H.)
| | - Charles Joly-Beauparlant
- Genomics Center, CHU de Québec-Université Laval Research Center, 2705 Laurier Boulevard, Quebec City, QC GIV 4G2, Canada; (M.D.); (C.J.-B.); (A.D.); (S.D.); (A.-C.C.-D.); (P.S.); (M.V.); (F.F.); (A.L.)
| | - Corinna Ernst
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany; (N.W.-L.); (C.E.); (R.K.S.); (E.H.)
| | - Arnaud Droit
- Genomics Center, CHU de Québec-Université Laval Research Center, 2705 Laurier Boulevard, Quebec City, QC GIV 4G2, Canada; (M.D.); (C.J.-B.); (A.D.); (S.D.); (A.-C.C.-D.); (P.S.); (M.V.); (F.F.); (A.L.)
| | - Bing-Jian Feng
- Department of Dermatology, University of Utah, Salt Lake City, UT 84103, USA; (B.-J.F.); (D.E.G.)
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA;
| | - Stéphane Dubois
- Genomics Center, CHU de Québec-Université Laval Research Center, 2705 Laurier Boulevard, Quebec City, QC GIV 4G2, Canada; (M.D.); (C.J.-B.); (A.D.); (S.D.); (A.-C.C.-D.); (P.S.); (M.V.); (F.F.); (A.L.)
| | - Annie-Claude Collin-Deschesnes
- Genomics Center, CHU de Québec-Université Laval Research Center, 2705 Laurier Boulevard, Quebec City, QC GIV 4G2, Canada; (M.D.); (C.J.-B.); (A.D.); (S.D.); (A.-C.C.-D.); (P.S.); (M.V.); (F.F.); (A.L.)
| | - Penny Soucy
- Genomics Center, CHU de Québec-Université Laval Research Center, 2705 Laurier Boulevard, Quebec City, QC GIV 4G2, Canada; (M.D.); (C.J.-B.); (A.D.); (S.D.); (A.-C.C.-D.); (P.S.); (M.V.); (F.F.); (A.L.)
| | - Maxime Vallée
- Genomics Center, CHU de Québec-Université Laval Research Center, 2705 Laurier Boulevard, Quebec City, QC GIV 4G2, Canada; (M.D.); (C.J.-B.); (A.D.); (S.D.); (A.-C.C.-D.); (P.S.); (M.V.); (F.F.); (A.L.)
| | - Frédéric Fournier
- Genomics Center, CHU de Québec-Université Laval Research Center, 2705 Laurier Boulevard, Quebec City, QC GIV 4G2, Canada; (M.D.); (C.J.-B.); (A.D.); (S.D.); (A.-C.C.-D.); (P.S.); (M.V.); (F.F.); (A.L.)
| | - Audrey Lemaçon
- Genomics Center, CHU de Québec-Université Laval Research Center, 2705 Laurier Boulevard, Quebec City, QC GIV 4G2, Canada; (M.D.); (C.J.-B.); (A.D.); (S.D.); (A.-C.C.-D.); (P.S.); (M.V.); (F.F.); (A.L.)
| | - Muriel A. Adank
- Family Cancer Clinic, The Netherlands Cancer Institute—Antoni van Leeuwenhoek Hospital, 1066 Amsterdam, The Netherlands; (M.A.A.); (F.B.L.H.); (L.v.d.K.)
| | - Jamie Allen
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (J.A.); (M.K.B.); (S.C.); (P.D.P.P.); (Q.W.); (D.F.E.)
| | - Janine Altmüller
- Cologne Center for Genomics (CCG), Faculty of Medicine, University Hospital Cologne, University of Cologne, 50931 Cologne, Germany; (J.A.); (H.T.)
| | - Norbert Arnold
- Institute of Clinical Molecular Biology, Department of Gynaecology and Obstetrics, University Hospital of Schleswig-Holstein, Campus Kiel, Christian-Albrechts University Kiel, 24105 Kiel, Germany;
| | - Margreet G. E. M. Ausems
- Division Laboratories, Pharmacy and Biomedical Genetics, Department of Genetics, University Medical Center Utrecht, 3584 Utrecht, The Netherlands;
| | - Riccardo Berutti
- Institute of Human Genetics, Technische Universität München, 81675 Munich, Germany; (R.B.); (T.M.S.)
| | - Manjeet K. Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (J.A.); (M.K.B.); (S.C.); (P.D.P.P.); (Q.W.); (D.F.E.)
| | - Shelley Bull
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON M5G 1X5, Canada; (S.B.); (J.G.); (G.D.B.); (I.L.A.)
- Dalla Lana School of Public Health, University of Toronto, Toronto, ON M5T 3M7, Canada
| | - Sara Carvalho
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (J.A.); (M.K.B.); (S.C.); (P.D.P.P.); (Q.W.); (D.F.E.)
| | - Sten Cornelissen
- Division of Molecular Pathology, The Netherlands Cancer Institute—Antoni van Leeuwenhoek Hospital, 1066 Amsterdam, The Netherlands; (S.C.); (R.K.); (M.K.S.)
| | - Michael R. Dufault
- Precision Medicine and Computational Biology, Sanofi Genzyme, Cambridge, MA 02142, USA;
| | - Alison M. Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK; (A.M.D.); (C.L.); (M.S.)
| | - Christoph Engel
- Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 04107 Leipzig, Germany;
| | - Andrea Gehrig
- Centre of Familial Breast and Ovarian Cancer, Department of Medical Genetics, Institute of Human Genetics, University of Würzburg, 97074 Würzburg, Germany;
| | | | - Christian Gieger
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany; (C.G.); (A.P.)
- Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, 85764 Neuherberg, Germany
| | - Jessica Green
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON M5G 1X5, Canada; (S.B.); (J.G.); (G.D.B.); (I.L.A.)
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada;
| | - Karl Hackmann
- Institute for Clinical Genetics, Faculty of Medicine Carl Gustav Carus, Technische Universität Dresden, 01307 Dresden, Germany;
| | - Mohamed Helmy
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada;
- Bioinformatics Institute (BII), Agency for Science, Technology and Research (A*STAR), Singapore 138632, Singapore
- Department of Computer Science, Lakehead University, Thunder Bay, ON P7B 5E1, Canada
| | - Julia Hentschel
- Institute of Human Genetics, University Leipzig, 04103 Leipzig, Germany;
| | - Frans B. L. Hogervorst
- Family Cancer Clinic, The Netherlands Cancer Institute—Antoni van Leeuwenhoek Hospital, 1066 Amsterdam, The Netherlands; (M.A.A.); (F.B.L.H.); (L.v.d.K.)
| | - Antoinette Hollestelle
- Department of Medical Oncology, Erasmus MC Cancer Institute, 3015 Rotterdam, The Netherlands; (A.H.); (M.J.H.); (J.W.M.M.)
| | - Maartje J. Hooning
- Department of Medical Oncology, Erasmus MC Cancer Institute, 3015 Rotterdam, The Netherlands; (A.H.); (M.J.H.); (J.W.M.M.)
| | - Judit Horváth
- Institute of Human Genetics, University of Münster, 48149 Münster, Germany;
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus MC University Medical Center, 3015 Rotterdam, The Netherlands;
| | - Silke Kaulfuß
- Institute of Human Genetics, University Medical Center Göttingen, 37075 Göttingen, Germany;
| | - Renske Keeman
- Division of Molecular Pathology, The Netherlands Cancer Institute—Antoni van Leeuwenhoek Hospital, 1066 Amsterdam, The Netherlands; (S.C.); (R.K.); (M.K.S.)
| | - Da Kuang
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada;
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada;
| | - Craig Luccarini
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK; (A.M.D.); (C.L.); (M.S.)
| | - Wolfgang Maier
- German Center for Neurodegenerative Diseases (DZNE), Department of Neurodegenerative Diseases and Geriatric Psychiatry, Medical Faculty, University Hospital Bonn, 53127 Bonn, Germany;
| | - John W. M. Martens
- Department of Medical Oncology, Erasmus MC Cancer Institute, 3015 Rotterdam, The Netherlands; (A.H.); (M.J.H.); (J.W.M.M.)
| | - Dieter Niederacher
- Department of Gynecology and Obstetrics, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, 40225 Düsseldorf, Germany;
| | - Peter Nürnberg
- Center for Molecular Medicine Cologne (CMMC), Cologne Center for Genomics (CCG), Faculty of Medicine, University Hospital Cologne, University of Cologne, 50931 Cologne, Germany;
| | - Claus-Eric Ott
- Institute of Medical Genetics and Human Genetics, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, 13353 Berlin, Germany;
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764 Neuherberg, Germany; (C.G.); (A.P.)
- Department of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Medical Faculty, Ludwig-Maximilians-Universität München, 80539 Munich, Germany
| | - Paul D. P. Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (J.A.); (M.K.B.); (S.C.); (P.D.P.P.); (Q.W.); (D.F.E.)
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK; (A.M.D.); (C.L.); (M.S.)
| | - Alfredo Ramirez
- Division for Neurogenetics and Molecular Psychiatry, Medical Faculty, University of Cologne, 50937 Cologne, Germany;
| | - Juliane Ramser
- Division of Gynaecology and Obstetrics, Klinikum Rechts der Isar der Technischen Universität München, 81675 Munich, Germany; (J.R.); (A.M.)
| | - Steffi Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, Faculty of Medicine, University of Leipzig, 04103 Leipzig, Germany;
| | - Gunnar Schmidt
- Institute of Human Genetics, Hannover Medical School, 30625 Hannover, Germany;
| | - Mitul Shah
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK; (A.M.D.); (C.L.); (M.S.)
| | - Martin Scherer
- Department of Primary Medical Care, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany;
| | - Antje Stäbler
- Institute of Medical Genetics and Applied Genomics, University of Tübingen, 72076 Tübingen, Germany;
| | - Tim M. Strom
- Institute of Human Genetics, Technische Universität München, 81675 Munich, Germany; (R.B.); (T.M.S.)
| | - Christian Sutter
- Institute of Human Genetics, University Hospital Heidelberg, 69120 Heidelberg, Germany;
| | - Holger Thiele
- Cologne Center for Genomics (CCG), Faculty of Medicine, University Hospital Cologne, University of Cologne, 50931 Cologne, Germany; (J.A.); (H.T.)
| | - Christi J. van Asperen
- Department of Clinical Genetics, Leiden University Medical Center, 2333 Leiden, The Netherlands; (C.J.v.A.); (R.B.v.d.L.)
| | - Lizet van der Kolk
- Family Cancer Clinic, The Netherlands Cancer Institute—Antoni van Leeuwenhoek Hospital, 1066 Amsterdam, The Netherlands; (M.A.A.); (F.B.L.H.); (L.v.d.K.)
| | - Rob B. van der Luijt
- Department of Clinical Genetics, Leiden University Medical Center, 2333 Leiden, The Netherlands; (C.J.v.A.); (R.B.v.d.L.)
- Department of Medical Genetics, University Medical Center, 3584 Utrecht, The Netherlands
| | - Alexander E. Volk
- Institute of Human Genetics, University Medical Center Hamburg-Eppendorf, 20246 Hamburg, Germany;
| | - Michael Wagner
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, 53127 Bonn, Germany;
| | - Quinten Waisfisz
- Department of Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 Amsterdam, The Netherlands;
| | - Qin Wang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (J.A.); (M.K.B.); (S.C.); (P.D.P.P.); (Q.W.); (D.F.E.)
| | - Shan Wang-Gohrke
- Department of Gynaecology and Obstetrics, University of Ulm, 89081 Ulm, Germany;
| | - Bernhard H. F. Weber
- Institute of Human Genetics, Regensburg University, 93053 Regensburg, Germany;
- Institute of Clinical Human Genetics, University Hospital Regensburg, 93053 Regensburg, Germany
| | | | | | - Peter Devilee
- Department of Pathology, Department of Human Genetics, Leiden University Medical Center, 2333 Leiden, The Netherlands;
| | - Sean Tavtigian
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA;
- Department of Oncological Sciences, University of Utah School of Medicine, Salt Lake City, UT 84132, USA
| | - Gary D. Bader
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON M5G 1X5, Canada; (S.B.); (J.G.); (G.D.B.); (I.L.A.)
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada;
- The Donnelly Centre, University of Toronto, Toronto, ON M5S 3E1, Canada;
- Department of Computer Science, University of Toronto, Toronto, ON M5S 3E1, Canada
- Princess Margaret Research Institute, University Health Network, Toronto, ON M5G 0A3, Canada
| | - Alfons Meindl
- Division of Gynaecology and Obstetrics, Klinikum Rechts der Isar der Technischen Universität München, 81675 Munich, Germany; (J.R.); (A.M.)
| | - David E. Goldgar
- Department of Dermatology, University of Utah, Salt Lake City, UT 84103, USA; (B.-J.F.); (D.E.G.)
- Huntsman Cancer Institute, University of Utah, Salt Lake City, UT 84112, USA;
| | - Irene L. Andrulis
- Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON M5G 1X5, Canada; (S.B.); (J.G.); (G.D.B.); (I.L.A.)
- Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada;
| | - Rita K. Schmutzler
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany; (N.W.-L.); (C.E.); (R.K.S.); (E.H.)
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge CB1 8RN, UK; (J.A.); (M.K.B.); (S.C.); (P.D.P.P.); (Q.W.); (D.F.E.)
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge CB1 8RN, UK; (A.M.D.); (C.L.); (M.S.)
| | - Marjanka K. Schmidt
- Division of Molecular Pathology, The Netherlands Cancer Institute—Antoni van Leeuwenhoek Hospital, 1066 Amsterdam, The Netherlands; (S.C.); (R.K.); (M.K.S.)
- Division of Psychosocial Research and Epidemiology, The Netherlands Cancer Institute—Antoni van Leeuwenhoek Hospital, 1066 Amsterdam, The Netherlands
| | - Eric Hahnen
- Center for Familial Breast and Ovarian Cancer, Center for Integrated Oncology (CIO), Faculty of Medicine and University Hospital Cologne, University of Cologne, 50937 Cologne, Germany; (N.W.-L.); (C.E.); (R.K.S.); (E.H.)
| | - Jacques Simard
- Genomics Center, CHU de Québec-Université Laval Research Center, 2705 Laurier Boulevard, Quebec City, QC GIV 4G2, Canada; (M.D.); (C.J.-B.); (A.D.); (S.D.); (A.-C.C.-D.); (P.S.); (M.V.); (F.F.); (A.L.)
- Department of Molecular Medicine, Faculty of Medicine, Université Laval, Quebec, QC G1V 0A6, Canada
- Correspondence: ; Tel.: +418-654-2264
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Evans DG, van Veen EM, Howell A, Astley S. Heritability of mammographic breast density. Quant Imaging Med Surg 2020; 10:2387-2391. [PMID: 33269237 DOI: 10.21037/qims-2020-20] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Affiliation(s)
- D Gareth Evans
- Clinical Genetics Service, Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK.,NW Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK.,Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK.,Prevent Breast Cancer Centre, Wythenshawe Hospital Manchester Universities Foundation Trust, Wythenshawe, Manchester, UK.,Manchester Breast Centre, The Christie Hospital, Manchester, UK
| | - Elke M van Veen
- NW Genomic Laboratory Hub, Manchester Centre for Genomic Medicine, Manchester University Hospitals NHS Foundation Trust, Manchester, UK.,Division of Evolution and Genomic Sciences, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
| | - Anthony Howell
- Prevent Breast Cancer Centre, Wythenshawe Hospital Manchester Universities Foundation Trust, Wythenshawe, Manchester, UK.,Manchester Breast Centre, The Christie Hospital, Manchester, UK
| | - Susan Astley
- Prevent Breast Cancer Centre, Wythenshawe Hospital Manchester Universities Foundation Trust, Wythenshawe, Manchester, UK.,Manchester Breast Centre, The Christie Hospital, Manchester, UK.,Division of Informatics, Imaging and Data Science, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester Academic Health Science Centre, Manchester, UK
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Mammographic breast density and its association with urinary estrogens and the fecal microbiota in postmenopausal women. PLoS One 2019; 14:e0216114. [PMID: 31067262 PMCID: PMC6505928 DOI: 10.1371/journal.pone.0216114] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2018] [Accepted: 04/15/2019] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND Breast density, as estimated by mammography, is a strong risk factor for breast cancer in pre- and postmenopausal women, but the determinants of breast density have not yet been established. The aim of this study was to assess if urinary estrogens or gut microbiota alterations are associated with mammographic density in postmenopausal women. METHODS Among 54 cancer-free, postmenopausal controls in the Breast and Colon Health study, we classified low- versus high-density women with Breast Imaging Reporting and Data System (BI-RADS, 5th edition) mammographic screening data, then assessed associations with urinary estrogens and estrogen metabolites (determined by liquid chromatography/tandem mass spectrometry), and fecal microbiota alpha and beta diversity (using Illumina sequencing of 16S rRNA amplicons). RESULTS Multiple logistic regression revealed no significant association between breast density and fecal microbiota metrics (PD_tree P-value = 0.82; un-weighted and weighted UniFrac P = 0.92 and 0.83, respectively, both by MiRKAT). In contrast, total urinary estrogens (and all 15 estrogens/estrogen metabolites) were strongly and inversely associated with breast density (P = 0.01) after adjustment for age and body mass index. CONCLUSION Mammographic density was not associated with the gut microbiota, but it was inversely associated with urinary estrogen levels. IMPACT The finding of an inverse association between urinary estrogens and breast density in cancer-free women adds to the growing breast cancer literature on understanding the relationship between endogenous estrogens and mammographic density.
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Decker B, Allen J, Luccarini C, Pooley KA, Shah M, Bolla MK, Wang Q, Ahmed S, Baynes C, Conroy DM, Brown J, Luben R, Ostrander EA, Pharoah PD, Dunning AM, Easton DF. Rare, protein-truncating variants in ATM, CHEK2 and PALB2, but not XRCC2, are associated with increased breast cancer risks. J Med Genet 2017; 54:732-741. [PMID: 28779002 PMCID: PMC5740532 DOI: 10.1136/jmedgenet-2017-104588] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Revised: 05/09/2017] [Accepted: 05/22/2017] [Indexed: 12/30/2022]
Abstract
BACKGROUND Breast cancer (BC) is the most common malignancy in women and has a major heritable component. The risks associated with most rare susceptibility variants are not well estimated. To better characterise the contribution of variants in ATM, CHEK2, PALB2 and XRCC2, we sequenced their coding regions in 13 087 BC cases and 5488 controls from East Anglia, UK. METHODS Gene coding regions were enriched via PCR, sequenced, variant called and filtered for quality. ORs for BC risk were estimated separately for carriers of truncating variants and of rare missense variants, which were further subdivided by functional domain and pathogenicity as predicted by four in silico algorithms. RESULTS Truncating variants in PALB2 (OR=4.69, 95% CI 2.27 to 9.68), ATM (OR=3.26; 95% CI 1.82 to 6.46) and CHEK2 (OR=3.11; 95% CI 2.15 to 4.69), but not XRCC2 (OR=0.94; 95% CI 0.26 to 4.19) were associated with increased BC risk. Truncating variants in ATM and CHEK2 were more strongly associated with risk of oestrogen receptor (ER)-positive than ER-negative disease, while those in PALB2 were associated with similar risks for both subtypes. There was also some evidence that missense variants in ATM, CHEK2 and PALB2 may contribute to BC risk, but larger studies are necessary to quantify the magnitude of this effect. CONCLUSIONS Truncating variants in PALB2 are associated with a higher risk of BC than those in ATM or CHEK2. A substantial risk of BC due to truncating XRCC2 variants can be excluded.
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Affiliation(s)
- Brennan Decker
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Jamie Allen
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Craig Luccarini
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Karen A Pooley
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Mitul Shah
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Manjeet K Bolla
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Qin Wang
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Shahana Ahmed
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Caroline Baynes
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Don M Conroy
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Judith Brown
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Robert Luben
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Elaine A Ostrander
- Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Paul Dp Pharoah
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Alison M Dunning
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Douglas F Easton
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
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6
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Easton DF, Lesueur F, Decker B, Michailidou K, Li J, Allen J, Luccarini C, Pooley KA, Shah M, Bolla MK, Wang Q, Dennis J, Ahmad J, Thompson ER, Damiola F, Pertesi M, Voegele C, Mebirouk N, Robinot N, Durand G, Forey N, Luben RN, Ahmed S, Aittomäki K, Anton-Culver H, Arndt V, Baynes C, Beckman MW, Benitez J, Van Den Berg D, Blot WJ, Bogdanova NV, Bojesen SE, Brenner H, Chang-Claude J, Chia KS, Choi JY, Conroy DM, Cox A, Cross SS, Czene K, Darabi H, Devilee P, Eriksson M, Fasching PA, Figueroa J, Flyger H, Fostira F, García-Closas M, Giles GG, Glendon G, González-Neira A, Guénel P, Haiman CA, Hall P, Hart SN, Hartman M, Hooning MJ, Hsiung CN, Ito H, Jakubowska A, James PA, John EM, Johnson N, Jones M, Kabisch M, Kang D, Kosma VM, Kristensen V, Lambrechts D, Li N, Lindblom A, Long J, Lophatananon A, Lubinski J, Mannermaa A, Manoukian S, Margolin S, Matsuo K, Meindl A, Mitchell G, Muir K, Nevelsteen I, van den Ouweland A, Peterlongo P, Phuah SY, Pylkäs K, Rowley SM, Sangrajrang S, Schmutzler RK, Shen CY, Shu XO, Southey MC, Surowy H, Swerdlow A, Teo SH, Tollenaar RAEM, Tomlinson I, Torres D, Truong T, Vachon C, Verhoef S, Wong-Brown M, Zheng W, Zheng Y, Nevanlinna H, Scott RJ, Andrulis IL, Wu AH, Hopper JL, Couch FJ, Winqvist R, Burwinkel B, Sawyer EJ, Schmidt MK, Rudolph A, Dörk T, Brauch H, Hamann U, Neuhausen SL, Milne RL, Fletcher O, Pharoah PDP, Campbell IG, Dunning AM, Le Calvez-Kelm F, Goldgar DE, Tavtigian SV, Chenevix-Trench G. No evidence that protein truncating variants in BRIP1 are associated with breast cancer risk: implications for gene panel testing. J Med Genet 2016; 53:298-309. [PMID: 26921362 PMCID: PMC4938802 DOI: 10.1136/jmedgenet-2015-103529] [Citation(s) in RCA: 83] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2015] [Accepted: 12/16/2015] [Indexed: 12/13/2022]
Abstract
BACKGROUND BRCA1 interacting protein C-terminal helicase 1 (BRIP1) is one of the Fanconi Anaemia Complementation (FANC) group family of DNA repair proteins. Biallelic mutations in BRIP1 are responsible for FANC group J, and previous studies have also suggested that rare protein truncating variants in BRIP1 are associated with an increased risk of breast cancer. These studies have led to inclusion of BRIP1 on targeted sequencing panels for breast cancer risk prediction. METHODS We evaluated a truncating variant, p.Arg798Ter (rs137852986), and 10 missense variants of BRIP1, in 48 144 cases and 43 607 controls of European origin, drawn from 41 studies participating in the Breast Cancer Association Consortium (BCAC). Additionally, we sequenced the coding regions of BRIP1 in 13 213 cases and 5242 controls from the UK, 1313 cases and 1123 controls from three population-based studies as part of the Breast Cancer Family Registry, and 1853 familial cases and 2001 controls from Australia. RESULTS The rare truncating allele of rs137852986 was observed in 23 cases and 18 controls in Europeans in BCAC (OR 1.09, 95% CI 0.58 to 2.03, p=0.79). Truncating variants were found in the sequencing studies in 34 cases (0.21%) and 19 controls (0.23%) (combined OR 0.90, 95% CI 0.48 to 1.70, p=0.75). CONCLUSIONS These results suggest that truncating variants in BRIP1, and in particular p.Arg798Ter, are not associated with a substantial increase in breast cancer risk. Such observations have important implications for the reporting of results from breast cancer screening panels.
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Affiliation(s)
- Douglas F Easton
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Fabienne Lesueur
- Genetic Epidemiology of Cancer team, Inserm, U900, Institut Curie, Mines ParisTech, Paris, France
| | - Brennan Decker
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK Cancer Genetics and Comparative Genomics Section, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Kyriaki Michailidou
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK Department of Electron Microscopy/Molecular Pathology, The Cyprus Institute of Neurology and Genetics, Nicosia, Cyprus
| | - Jun Li
- Department of Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Jamie Allen
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Craig Luccarini
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Karen A Pooley
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Mitul Shah
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Manjeet K Bolla
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Qin Wang
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Joe Dennis
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Jamil Ahmad
- Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, Lyon, France
| | - Ella R Thompson
- Research Division, Peter MacCallum Cancer Centre, East Melbourne, Australia Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia
| | - Francesca Damiola
- Genetic of Breast Cancer Team, Cancer Research Center of Lyon, Centre Léon Bérard, Lyon, France
| | - Maroulio Pertesi
- Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, Lyon, France
| | - Catherine Voegele
- Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, Lyon, France
| | - Noura Mebirouk
- Genetic Epidemiology of Cancer team, Inserm, U900, Institut Curie, Mines ParisTech, Paris, France
| | - Nivonirina Robinot
- Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, Lyon, France
| | - Geoffroy Durand
- Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, Lyon, France
| | - Nathalie Forey
- Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, Lyon, France
| | - Robert N Luben
- Clinical Gerontology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Shahana Ahmed
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Kristiina Aittomäki
- Department of Clinical Genetics, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Hoda Anton-Culver
- Department of Epidemiology, University of California Irvine, Irvine, California, USA
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Caroline Baynes
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Matthias W Beckman
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany
| | - Javier Benitez
- Human Cancer Genetics Program, Spanish National Cancer Research Centre, Madrid, Spain Centro de Investigación en Red de Enfermedades Raras (CIBERER), Valencia, Spain
| | - David Van Den Berg
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - William J Blot
- International Epidemiology Institute, Rockville, Maryland, USA Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Natalia V Bogdanova
- Department of Radiation Oncology, Hannover Medical School, Hannover, Germany
| | - Stig E Bojesen
- Copenhagen General Population Study, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany University Cancer Center Hamburg (UCCH), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Kee Seng Chia
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Ji-Yeob Choi
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea
| | - Don M Conroy
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Angela Cox
- Sheffield Cancer Research, Department of Oncology, University of Sheffield, Sheffield, UK
| | - Simon S Cross
- Academic Unit of Pathology, Department of Neuroscience, University of Sheffield, Sheffield, UK
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Hatef Darabi
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Peter Devilee
- Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands Department of Pathology, Leiden University Medical Center, Leiden, The Netherlands
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Peter A Fasching
- Department of Gynaecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-EMN, Erlangen, Germany David Geffen School of Medicine, Department of Medicine Division of Hematology and Oncology, University of California, Los Angeles, California, USA
| | - Jonine Figueroa
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA Usher Institute of Population Health Sciences and Informatics, The University of Edinburgh Medical School, Edinburgh, UK
| | - Henrik Flyger
- Department of Breast Surgery, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Florentia Fostira
- Molecular Diagnostics Laboratory, INRASTES, National Centre for Scientific Research "Demokritos", Athens, Greece
| | - Montserrat García-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Gord Glendon
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada
| | - Anna González-Neira
- Human Cancer Genetics Program, Spanish National Cancer Research Centre, Madrid, Spain
| | - Pascal Guénel
- University Paris-Sud, UMRS 1018, Villejuif, France Inserm, CESP Center for research in Epidemiology and Population Health, U1018, Cancer & Environment Group, Villejuif, France
| | - Christopher A Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Steven N Hart
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Mikael Hartman
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore Department of Surgery, National University Health System, Singapore, Singapore
| | - Maartje J Hooning
- Department of Medical Oncology, Family Cancer Clinic, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Chia-Ni Hsiung
- Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Hidemi Ito
- Division of Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Aichi, Japan
| | - Anna Jakubowska
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Paul A James
- Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Esther M John
- Department of Epidemiology, Cancer Prevention Institute of California, Fremont, California, USA Department of Health Research and Policy-Epidemiology, Stanford University School of Medicine, Stanford, California, USA Stanford Cancer Institute, Stanford University School of Medicine, Stanford, California, USA
| | - Nichola Johnson
- Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK Division of Breast Cancer Research, The Institute of Cancer Research, London, UK
| | - Michael Jones
- Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Maria Kabisch
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Daehee Kang
- Cancer Research Institute, Seoul National University College of Medicine, Seoul, Korea Department of Biomedical Sciences, Seoul National University College of Medicine, Seoul, Korea Department of Preventive Medicine, Seoul National University College of Medicine, Seoul National University, Seoul, Korea
| | - Veli-Matti Kosma
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland Cancer Center of Eastern Finland, University of Eastern Finland, Kuopio, Finland
| | - Vessela Kristensen
- Department of Genetics, Institute for Cancer Research, Oslo University Hospital, Radiumhospitalet, Oslo, Norway Faculty of Medicine, K.G. Jebsen Center for Breast Cancer Research, Institute of Clinical Medicine, University of Oslo, Oslo, Norway Department of Clinical Molecular Biology (EpiGen), University of Oslo (UiO), Oslo, Norway
| | - Diether Lambrechts
- Vesalius Research Center, VIB, Leuven, Belgium Laboratory for Translational Genetics, Department of Oncology, University of Leuven, Leuven, Belgium
| | - Na Li
- Research Division, Peter MacCallum Cancer Centre, East Melbourne, Australia Cancer Biology Research Center, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Annika Lindblom
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Jirong Long
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Artitaya Lophatananon
- Division of Health Sciences, Warwick Medical school, Warwick University, Coventry, UK
| | - Jan Lubinski
- Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - Arto Mannermaa
- Institute of Clinical Medicine, Pathology and Forensic Medicine, University of Eastern Finland, Kuopio, Finland Imaging Center, Department of Clinical Pathology, Kuopio University Hospital, Kuopio, Finland Cancer Center of Eastern Finland, University of Eastern Finland, Kuopio, Finland
| | - Siranoush Manoukian
- Unit of Medical Genetics, Department of Preventive and Predictive Medicine, Fondazione IRCCS (Istituto di Ricovero e Cura a Carattere Scientifico) Istituto Nazionale Tumori (INT), Milan, Italy
| | - Sara Margolin
- Department of Oncology-Pathology, Karolinska Institutet, Stockholm, Sweden
| | - Keitaro Matsuo
- Division of Molecular Medicine, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Alfons Meindl
- Division of Gynaecology and Obstetrics, Technische Universität München, Munich, Germany
| | - Gillian Mitchell
- Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia Familial Cancer Centre, Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia
| | - Kenneth Muir
- Division of Health Sciences, Warwick Medical school, Warwick University, Coventry, UK Institute of Population Health, University of Manchester, Manchester, UK
| | | | - Ans van den Ouweland
- Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Paolo Peterlongo
- IFOM, The FIRC (Italian Foundation for Cancer Research) Institute of Molecular Oncology, Milan, Italy
| | - Sze Yee Phuah
- Breast Cancer Research Unit, University Malaya Cancer Research Institute, University Malaya Medical Centre (UMMC), Kuala Lumpur, Malaysia Cancer Research Initiatives Foundation, Sime Darby Medical Centre, Subang Jaya, Malaysia
| | - Katri Pylkäs
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre NordLab, Oulu, Finland Laboratory of Cancer Genetics and Tumor Biology, Cancer Research and Translational Medicine, Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Simone M Rowley
- Research Division, Peter MacCallum Cancer Centre, East Melbourne, Australia
| | | | - Rita K Schmutzler
- Center for Integrated Oncology (CIO), Medical Faculty, University Hospital Cologne, Germany Medical Faculty, Center for Hereditary Breast and Ovarian Cancer, University Hospital Cologne, Germany Center for Molecular Medicine Cologne (CMMC), University of Cologne, Germany
| | - Chen-Yang Shen
- School of Public Health, China Medical University, Taichung, Taiwan Taiwan Biobank, Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Melissa C Southey
- Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Harald Surowy
- Molecular Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany Department of Obstetrics and Gynecology, University of Heidelberg, Heidelberg, Germany
| | - Anthony Swerdlow
- Division of Breast Cancer Research, The Institute of Cancer Research, London, UK Division of Genetics and Epidemiology, The Institute of Cancer Research, London, UK
| | - Soo H Teo
- Breast Cancer Research Unit, University Malaya Cancer Research Institute, University Malaya Medical Centre (UMMC), Kuala Lumpur, Malaysia Cancer Research Initiatives Foundation, Sime Darby Medical Centre, Subang Jaya, Malaysia
| | - Rob A E M Tollenaar
- Department of Surgery, Leiden University Medical Center, Leiden, The Netherlands
| | - Ian Tomlinson
- Wellcome Trust Centre for Human Genetics and Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Diana Torres
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany Institute of Human Genetics, Pontificia Universidad Javeriana, Bogota, Colombia
| | - Thérèse Truong
- University Paris-Sud, UMRS 1018, Villejuif, France Inserm, CESP Center for research in Epidemiology and Population Health, U1018, Cancer & Environment Group, Villejuif, France
| | - Celine Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Senno Verhoef
- Netherlands Cancer Institute, Antoni van Leeuwenhoek hospital, Amsterdam, The Netherlands
| | - Michelle Wong-Brown
- Division of Genetics, Hunter Area Pathology Service, John Hunter Hospital, Newcastle, New South Wales, Australia
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, Tennessee, USA
| | - Ying Zheng
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Heli Nevanlinna
- Department of Obstetrics and Gynecology, University of Helsinki and Helsinki University Hospital, Helsinki, Finland
| | - Rodney J Scott
- Division of Genetics, Hunter Area Pathology Service, John Hunter Hospital, Newcastle, New South Wales, Australia Division of Molecular Medicine, Pathology North, John Hunter Hospital, Newcastle, New South Wales, Australia
| | - Irene L Andrulis
- Lunenfeld-Tanenbaum Research Institute of Mount Sinai Hospital, Toronto, Ontario, Canada Department of Molecular Genetics, University of Toronto, Ontario, Canada
| | - Anna H Wu
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California, USA
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, University of Melbourne, Melbourne, Victoria, Australia
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Robert Winqvist
- Laboratory of Cancer Genetics and Tumor Biology, Northern Finland Laboratory Centre NordLab, Oulu, Finland Laboratory of Cancer Genetics and Tumor Biology, Cancer Research and Translational Medicine, Biocenter Oulu, University of Oulu, Oulu, Finland
| | - Barbara Burwinkel
- Molecular Epidemiology Group, German Cancer Research Center (DKFZ), Heidelberg, Germany Department of Obstetrics and Gynecology, University of Heidelberg, Heidelberg, Germany
| | - Elinor J Sawyer
- Research Oncology, Division of Cancer Studies, King's College London, Guy's Hospital, London, UK
| | - Marjanka K Schmidt
- Netherlands Cancer Institute, Antoni van Leeuwenhoek hospital, Amsterdam, The Netherlands
| | - Anja Rudolph
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Thilo Dörk
- Gynaecology Research Unit, Hannover Medical School, Hannover, Germany
| | - Hiltrud Brauch
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology, Stuttgart, Germany University of Tübingen, Tübingen, Germany
| | - Ute Hamann
- Molecular Genetics of Breast Cancer, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California, USA
| | - Roger L Milne
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Victoria, Australia Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Victoria, Australia
| | - Olivia Fletcher
- Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, UK Division of Breast Cancer Research, The Institute of Cancer Research, London, UK
| | - Paul D P Pharoah
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Ian G Campbell
- Research Division, Peter MacCallum Cancer Centre, East Melbourne, Australia Sir Peter MacCallum Department of Oncology, The University of Melbourne, Melbourne, Australia Department of Pathology, The University of Melbourne, Melbourne, Victoria, Australia
| | - Alison M Dunning
- Department of Oncology, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
| | - Florence Le Calvez-Kelm
- Genetic Cancer Susceptibility Group, International Agency for Research on Cancer, Lyon, France
| | - David E Goldgar
- Department of Dermatology, University of Utah School of Medicine, Salt Lake City, Utah, USA Cancer Control and Population Sciences, Huntsman Cancer Institute, Salt Lake City, Utah, USA
| | - Sean V Tavtigian
- Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah School of Medicine, Salt Lake City, Utah, USA
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Ramón Y Cajal T, Chirivella I, Miranda J, Teule A, Izquierdo Á, Balmaña J, Sánchez-Heras AB, Llort G, Fisas D, Lope V, Hernández-Agudo E, Juan-Fita MJ, Tena I, Robles L, Guillén-Ponce C, Pérez-Segura P, Luque-Molina MS, Hernando-Polo S, Salinas M, Brunet J, Salas-Trejo MD, Barnadas A, Pollán M. Mammographic density and breast cancer in women from high risk families. Breast Cancer Res 2015; 17:93. [PMID: 26163143 PMCID: PMC4499171 DOI: 10.1186/s13058-015-0604-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2014] [Accepted: 06/24/2015] [Indexed: 11/15/2022] Open
Abstract
Introduction Mammographic density (MD) is one of the strongest determinants of sporadic breast cancer (BC). In this study, we compared MD in BRCA1/2 mutation carriers and non-carriers from BRCA1/2 mutation-positive families and investigated the association between MD and BC among BRCA1/2 mutation carriers per type of mutation and tumor subtype. Methods The study was carried out in 1039 female members of BRCA1 and BRCA2 mutation-positive families followed at 16 Spanish Genetic Counseling Units. Participants’ density was scored retrospectively from available mammograms by a single blinded radiologist using a 5-category scale (<10 %, 10-25 %, 25-50 %, 50-75 %, >75 %). In BC cases, we selected mammograms taken prior to diagnosis or from the contralateral breast, whereas, in non-cases, the last screening mammogram was evaluated. MD distribution in carriers and non-carriers was compared using ordinal logistic models, and the association between MD and BC in BRCA1/2 mutation carriers was studied using logistic regression. Huber-White robust estimators of variance were used to take into account correlations between family members. A similar multinomial model was used to explore this association by BC subtype. Results We identified and scored mammograms from 341 BRCA1, 350 BRCA2 mutation carriers and 229 non-carriers. Compared to non-carriers, MD was significantly lower among BRCA2 mutation carriers (odds ratio (OR) =0.71; P-value=0.04), but not among BRCA1 carriers (OR=0.84; P-value=0.33). MD was associated with subsequent development BC (OR per category of MD=1.45; 95 % confidence interval=1.18-1.78, P-value<0.001), with no significant differences between BRCA1 and BRCA2 mutation carriers (P-value=0.48). Finally, no statistically significant differences were observed in the association of MD with specific BC subtypes. Conclusions Our study, the largest to date on this issue, confirms that MD is an independent risk factor for all BC subtypes in either BRCA1 and BRCA2 mutation carriers, and should be considered a phenotype risk marker in this context.
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Affiliation(s)
| | - Isabel Chirivella
- Medical Oncology Department, Hospital Clinico Universitario de Valencia, Valencia, Spain.
| | - Josefa Miranda
- Foundation General Directorate Public Health and Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, FISABIO - Public Health, Valencia, Spain.
| | - Alexandre Teule
- Hereditary Cancer Program, Catalan Institue of Oncology-IDIBELL, Barcelona, Spain.
| | - Ángel Izquierdo
- Hereditary Cancer Program, Catalan Institute of Oncology-IDIBGI, Girona, Spain.
| | - Judith Balmaña
- Medical Oncology Deartment, Hospital Vall Hebron/Vall Hebron Institute of Oncology, Barcelona, Spain.
| | | | - Gemma Llort
- Genetic Counseling Unit, Corporació Sanitaria Parc tauli, Consorci Sanitari de Terrassa, Terrasa, Spain.
| | - David Fisas
- Medical Oncology Department, Hospital Santa Creu I Sant Pau, Barcelona, Spain.
| | - Virginia Lope
- National Center for Epidemiology, Carlos III Institute of Health, Monforte de Lemos 5, 28029, Madrid, Spain. .,Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Carlos III Institute of Health, Madrid, Spain. .,Consortium Cancer Epidemiology Research Group, Oncology and Hematology Area, IIS Puerta de Hierro (IDIPHIM), Madrid, Spain.
| | - Elena Hernández-Agudo
- Breast Cancer Unit, Clinical Research Programme, Spanish National Cancer Center (CNIO), Madrid, Spain.
| | - María José Juan-Fita
- Medical Oncology Department, Foundation of the Valencian Oncologic Institute, Valencia, Spain.
| | - Isabel Tena
- Medical Oncology Department, Hospital Provincial de Castellón, Castellón, Spain.
| | - Luis Robles
- Medical Oncology Department, Hospital 12 de Octubre, Madrid, Spain.
| | - Carmen Guillén-Ponce
- Medical Oncology Department, Hospital Universitario Ramón y Cajal, IRYCIS, Madrid, Spain.
| | - Pedro Pérez-Segura
- Medical Oncology Department, Hospital Clínico San Carlos, Madrid, Spain.
| | | | | | - Mónica Salinas
- Hereditary Cancer Program, Catalan Institue of Oncology-IDIBELL, Barcelona, Spain.
| | - Joan Brunet
- Hereditary Cancer Program, Catalan Institute of Oncology-IDIBGI, Girona, Spain. .,Medical Sciences Department, School of Medicine, University of Girona, Girona, Spain.
| | - María Dolores Salas-Trejo
- Foundation General Directorate Public Health and Foundation for the Promotion of Health and Biomedical Research in the Valencian Region, FISABIO - Public Health, Valencia, Spain.
| | - Agustí Barnadas
- Medical Oncology Department, Hospital Santa Creu I Sant Pau, Barcelona, Spain.
| | - Marina Pollán
- National Center for Epidemiology, Carlos III Institute of Health, Monforte de Lemos 5, 28029, Madrid, Spain. .,Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Carlos III Institute of Health, Madrid, Spain. .,Consortium Cancer Epidemiology Research Group, Oncology and Hematology Area, IIS Puerta de Hierro (IDIPHIM), Madrid, Spain.
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8
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Stone J, Thompson DJ, Dos Santos Silva I, Scott C, Tamimi RM, Lindstrom S, Kraft P, Hazra A, Li J, Eriksson L, Czene K, Hall P, Jensen M, Cunningham J, Olson JE, Purrington K, Couch FJ, Brown J, Leyland J, Warren RML, Luben RN, Khaw KT, Smith P, Wareham NJ, Jud SM, Heusinger K, Beckmann MW, Douglas JA, Shah KP, Chan HP, Helvie MA, Le Marchand L, Kolonel LN, Woolcott C, Maskarinec G, Haiman C, Giles GG, Baglietto L, Krishnan K, Southey MC, Apicella C, Andrulis IL, Knight JA, Ursin G, Alnaes GIG, Kristensen VN, Borresen-Dale AL, Gram IT, Bolla MK, Wang Q, Michailidou K, Dennis J, Simard J, Pharoah P, Dunning AM, Easton DF, Fasching PA, Pankratz VS, Hopper JL, Vachon CM. Novel Associations between Common Breast Cancer Susceptibility Variants and Risk-Predicting Mammographic Density Measures. Cancer Res 2015; 75:2457-67. [PMID: 25862352 PMCID: PMC4470785 DOI: 10.1158/0008-5472.can-14-2012] [Citation(s) in RCA: 49] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2014] [Accepted: 03/10/2015] [Indexed: 12/30/2022]
Abstract
Mammographic density measures adjusted for age and body mass index (BMI) are heritable predictors of breast cancer risk, but few mammographic density-associated genetic variants have been identified. Using data for 10,727 women from two international consortia, we estimated associations between 77 common breast cancer susceptibility variants and absolute dense area, percent dense area and absolute nondense area adjusted for study, age, and BMI using mixed linear modeling. We found strong support for established associations between rs10995190 (in the region of ZNF365), rs2046210 (ESR1), and rs3817198 (LSP1) and adjusted absolute and percent dense areas (all P < 10(-5)). Of 41 recently discovered breast cancer susceptibility variants, associations were found between rs1432679 (EBF1), rs17817449 (MIR1972-2: FTO), rs12710696 (2p24.1), and rs3757318 (ESR1) and adjusted absolute and percent dense areas, respectively. There were associations between rs6001930 (MKL1) and both adjusted absolute dense and nondense areas, and between rs17356907 (NTN4) and adjusted absolute nondense area. Trends in all but two associations were consistent with those for breast cancer risk. Results suggested that 18% of breast cancer susceptibility variants were associated with at least one mammographic density measure. Genetic variants at multiple loci were associated with both breast cancer risk and the mammographic density measures. Further understanding of the underlying mechanisms at these loci could help identify etiologic pathways implicated in how mammographic density predicts breast cancer risk.
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Affiliation(s)
- Jennifer Stone
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Western Australia, Australia
| | - Deborah J Thompson
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Isabel Dos Santos Silva
- Department of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Christopher Scott
- Department of Health Sciences Research, Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Rulla M Tamimi
- Channing Laboratory, Department of Medicine, Brigham and Women's Hospital, Boston, Massachusetts. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Sara Lindstrom
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts. Program in Genetic Epidemiology and Statistical Genetics, Harvard School of Public Health, Boston, Massachusetts. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Aditi Hazra
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts
| | - Jingmei Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden. Human Genetics, Genome Institute of Singapore, Singapore, Singapore
| | - Louise Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Matt Jensen
- Department of Health Sciences Research, Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Julie Cunningham
- Department of Laboratory Medicine and Pathology, Division of Experimental Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - Janet E Olson
- Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota
| | - Kristen Purrington
- Department of Oncology, Wayne State University School of Medicine and Karmanos Cancer Institute, Detroit, Michigan
| | - Fergus J Couch
- Department of Laboratory Medicine and Pathology, Division of Experimental Pathology, Mayo Clinic College of Medicine, Rochester, Minnesota. Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota
| | - Judith Brown
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jean Leyland
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Ruth M L Warren
- Department of Radiology, University of Cambridge, Addenbrooke's NHS Foundation Trust, Cambridge, United Kingdom
| | - Robert N Luben
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Kay-Tee Khaw
- MRC Centre for Nutritional Epidemiology in Cancer Prevention and Survival (CNC), University of Cambridge, Cambridge, United Kingdom
| | - Paula Smith
- Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Sebastian M Jud
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-Nuremberg, Erlangen-Nuremberg, Germany
| | - Katharina Heusinger
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-Nuremberg, Erlangen-Nuremberg, Germany
| | - Matthias W Beckmann
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-Nuremberg, Erlangen-Nuremberg, Germany
| | - Julie A Douglas
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan
| | - Kaanan P Shah
- Department of Human Genetics, University of Michigan Medical School, Ann Arbor, Michigan
| | - Heang-Ping Chan
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | - Mark A Helvie
- Department of Radiology, University of Michigan Medical School, Ann Arbor, Michigan
| | | | | | - Christy Woolcott
- Department of Obstetrics and Genecology, IWK Health Centre, Halifax, Canada
| | | | - Christopher Haiman
- Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Graham G Giles
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Laura Baglietto
- Cancer Epidemiology Centre, Cancer Council Victoria, Melbourne, Australia. Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia. Centre for Research in Epidemiology and Population Health, Gustave Roussy Institute, Villejuif Cedex, France. Paris-South University, Villejuif, France
| | - Kavitha Krishnan
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Melissa C Southey
- Department of Pathology, University of Melbourne, Melbourne, Australia
| | - Carmel Apicella
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Irene L Andrulis
- Center for Cancer Genetics, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Ontario, Canada. Department of Molecular Genetics, University of Toronto, Toronto, Ontario, Canada
| | - Julia A Knight
- Prosserman Centre for Health Research, Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Toronto, Canada. Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Giske Ursin
- Institute of Basic Medical Sciences, University of Oslo, Norway. Department of Preventive Medicine, University of Southern California, California
| | - Grethe I Grenaker Alnaes
- Department of Genetics, Institute for Cancer Research, The Norwegian Radium Hospital, Montebello, Oslo, Norway
| | - Vessela N Kristensen
- Department of Genetics, Institute for Cancer Research, The Norwegian Radium Hospital, Montebello, Oslo, Norway
| | - Anne-Lise Borresen-Dale
- Department of Genetics, Institute for Cancer Research, The Norwegian Radium Hospital, Montebello, Oslo, Norway
| | - Inger Torhild Gram
- Faculty of Health Sciences, Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | - Manjeet K Bolla
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Qin Wang
- Faculty of Health Sciences, Department of Community Medicine, UiT The Arctic University of Norway, Tromsø, Norway
| | - Kyriaki Michailidou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Joe Dennis
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jacques Simard
- Centre Hospitalier Universitaire de Québec Research Center and Laval University, Quebec, Canada
| | - Paul Pharoah
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Alison M Dunning
- Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom. Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
| | - Peter A Fasching
- University Breast Center Franconia, Department of Gynecology and Obstetrics, University Hospital Erlangen, Friedrich-Alexander University Erlangen-Nuremberg, Comprehensive Cancer Center Erlangen-Nuremberg, Erlangen-Nuremberg, Germany. Department of Medicine, Division of Hematology and Oncology, David Geffen School of Medicine, University of California at Los Angeles, Los Angeles, California
| | - V Shane Pankratz
- Department of Health Sciences Research, Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, Minnesota
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
| | - Celine M Vachon
- Department of Health Sciences Research, Division of Epidemiology, Mayo Clinic, Rochester, Minnesota.
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Mammographic density and breast cancer risk by family history in women of white and Asian ancestry. Cancer Causes Control 2015; 26:621-6. [PMID: 25761408 DOI: 10.1007/s10552-015-0551-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2014] [Accepted: 03/04/2015] [Indexed: 10/23/2022]
Abstract
PURPOSE Mammographic density, i.e., the radiographic appearance of the breast, is a strong predictor of breast cancer risk. To determine whether the association of breast density with breast cancer is modified by a first-degree family history of breast cancer (FHBC) in women of white and Asian ancestry, we analyzed data from four case-control studies conducted in the USA and Japan. METHODS The study population included 1,699 breast cancer cases and 2,422 controls, of whom 45% reported white (N = 1,849) and 40% Asian (N = 1,633) ancestry. To standardize mammographic density assessment, a single observer re-read all mammograms using one type of interactive thresholding software. Logistic regression was applied to estimate odds ratios (OR) while adjusting for confounders. RESULTS Overall, 496 (12%) of participants reported a FHBC, which was significantly associated with breast cancer risk in the adjusted model (OR 1.51; 95% CI 1.23-1.84). There was a statistically significant interaction on a multiplicative scale between FHBC and continuous percent density (per 10 % density: p = 0.03). The OR per 10% increase in percent density was higher among women with a FHBC (OR 1.30; 95% CI 1.13-1.49) than among those without a FHBC (OR 1.14; 1.09-1.20). This pattern was apparent in whites and Asians. The respective ORs were 1.45 (95% CI 1.17-1.80) versus 1.22 (95% CI 1.14-1.32) in whites, whereas the values in Asians were only 1.24 (95% CI 0.97-1.58) versus 1.09 (95% CI 1.00-1.19). CONCLUSIONS These findings support the hypothesis that women with a FHBC appear to have a higher risk of breast cancer associated with percent mammographic density than women without a FHBC.
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Brand JS, Humphreys K, Thompson DJ, Li J, Eriksson M, Hall P, Czene K. Volumetric Mammographic Density: Heritability and Association With Breast Cancer Susceptibility Loci. J Natl Cancer Inst 2014; 106:dju334. [DOI: 10.1093/jnci/dju334] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
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11
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Gierach GL, Li H, Loud JT, Greene MH, Chow CK, Lan L, Prindiville SA, Eng-Wong J, Soballe PW, Giambartolomei C, Mai PL, Galbo CE, Nichols K, Calzone KA, Olopade OI, Gail MH, Giger ML. Relationships between computer-extracted mammographic texture pattern features and BRCA1/2 mutation status: a cross-sectional study. Breast Cancer Res 2014. [PMID: 25159706 DOI: 10.1186/preaccept-1744229618121391] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION Mammographic density is similar among women at risk of either sporadic or BRCA1/2-related breast cancer. It has been suggested that digitized mammographic images contain computer-extractable information within the parenchymal pattern, which may contribute to distinguishing between BRCA1/2 mutation carriers and non-carriers. METHODS We compared mammographic texture pattern features in digitized mammograms from women with deleterious BRCA1/2 mutations (n = 137) versus non-carriers (n = 100). Subjects were stratified into training (107 carriers, 70 non-carriers) and testing (30 carriers, 30 non-carriers) datasets. Masked to mutation status, texture features were extracted from a retro-areolar region-of-interest in each subject's digitized mammogram. Stepwise linear regression analysis of the training dataset identified variables to be included in a radiographic texture analysis (RTA) classifier model aimed at distinguishing BRCA1/2 carriers from non-carriers. The selected features were combined using a Bayesian Artificial Neural Network (BANN) algorithm, which produced a probability score rating the likelihood of each subject's belonging to the mutation-positive group. These probability scores were evaluated in the independent testing dataset to determine whether their distribution differed between BRCA1/2 mutation carriers and non-carriers. A receiver operating characteristic analysis was performed to estimate the model's discriminatory capacity. RESULTS In the testing dataset, a one standard deviation (SD) increase in the probability score from the BANN-trained classifier was associated with a two-fold increase in the odds of predicting BRCA1/2 mutation status: unadjusted odds ratio (OR) = 2.00, 95% confidence interval (CI): 1.59, 2.51, P = 0.02; age-adjusted OR = 1.93, 95% CI: 1.53, 2.42, P = 0.03. Additional adjustment for percent mammographic density did little to change the OR. The area under the curve for the BANN-trained classifier to distinguish between BRCA1/2 mutation carriers and non-carriers was 0.68 for features alone and 0.72 for the features plus percent mammographic density. CONCLUSIONS Our findings suggest that, unlike percent mammographic density, computer-extracted mammographic texture pattern features are associated with carrying BRCA1/2 mutations. Although still at an early stage, our novel RTA classifier has potential for improving mammographic image interpretation by permitting real-time risk stratification among women undergoing screening mammography.
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Affiliation(s)
- Gretchen L Gierach
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rm, 7-E108, Bethesda 20892-9774, MD, USA.
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12
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Gierach GL, Li H, Loud JT, Greene MH, Chow CK, Lan L, Prindiville SA, Eng-Wong J, Soballe PW, Giambartolomei C, Mai PL, Galbo CE, Nichols K, Calzone KA, Olopade OI, Gail MH, Giger ML. Relationships between computer-extracted mammographic texture pattern features and BRCA1/2 mutation status: a cross-sectional study. Breast Cancer Res 2014; 16:424. [PMID: 25159706 PMCID: PMC4268674 DOI: 10.1186/s13058-014-0424-8] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2014] [Accepted: 07/31/2014] [Indexed: 12/24/2022] Open
Abstract
Introduction Mammographic density is similar among women at risk of either sporadic or BRCA1/2-related breast cancer. It has been suggested that digitized mammographic images contain computer-extractable information within the parenchymal pattern, which may contribute to distinguishing between BRCA1/2 mutation carriers and non-carriers. Methods We compared mammographic texture pattern features in digitized mammograms from women with deleterious BRCA1/2 mutations (n = 137) versus non-carriers (n = 100). Subjects were stratified into training (107 carriers, 70 non-carriers) and testing (30 carriers, 30 non-carriers) datasets. Masked to mutation status, texture features were extracted from a retro-areolar region-of-interest in each subject’s digitized mammogram. Stepwise linear regression analysis of the training dataset identified variables to be included in a radiographic texture analysis (RTA) classifier model aimed at distinguishing BRCA1/2 carriers from non-carriers. The selected features were combined using a Bayesian Artificial Neural Network (BANN) algorithm, which produced a probability score rating the likelihood of each subject’s belonging to the mutation-positive group. These probability scores were evaluated in the independent testing dataset to determine whether their distribution differed between BRCA1/2 mutation carriers and non-carriers. A receiver operating characteristic analysis was performed to estimate the model’s discriminatory capacity. Results In the testing dataset, a one standard deviation (SD) increase in the probability score from the BANN-trained classifier was associated with a two-fold increase in the odds of predicting BRCA1/2 mutation status: unadjusted odds ratio (OR) = 2.00, 95% confidence interval (CI): 1.59, 2.51, P = 0.02; age-adjusted OR = 1.93, 95% CI: 1.53, 2.42, P = 0.03. Additional adjustment for percent mammographic density did little to change the OR. The area under the curve for the BANN-trained classifier to distinguish between BRCA1/2 mutation carriers and non-carriers was 0.68 for features alone and 0.72 for the features plus percent mammographic density. Conclusions Our findings suggest that, unlike percent mammographic density, computer-extracted mammographic texture pattern features are associated with carrying BRCA1/2 mutations. Although still at an early stage, our novel RTA classifier has potential for improving mammographic image interpretation by permitting real-time risk stratification among women undergoing screening mammography. Electronic supplementary material The online version of this article (doi:10.1186/s13058-014-0424-8) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Gretchen L Gierach
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rm, 7-E108, Bethesda 20892-9774, MD, USA.
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13
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Huo CW, Chew GL, Britt KL, Ingman WV, Henderson MA, Hopper JL, Thompson EW. Mammographic density-a review on the current understanding of its association with breast cancer. Breast Cancer Res Treat 2014; 144:479-502. [PMID: 24615497 DOI: 10.1007/s10549-014-2901-2] [Citation(s) in RCA: 144] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2013] [Accepted: 02/24/2014] [Indexed: 01/07/2023]
Abstract
There has been considerable recent interest in the genetic, biological and epidemiological basis of mammographic density (MD), and the search for causative links between MD and breast cancer (BC) risk. This report will critically review the current literature on MD and summarize the current evidence for its association with BC. Keywords 'mammographic dens*', 'dense mammary tissue' or 'percent dens*' were used to search the existing literature in English on PubMed and Medline. All reports were critically analyzed. The data were assigned to one of the following aspects of MD: general association with BC, its relationship with the breast hormonal milieu, the cellular basis of MD, the generic variations of MD, and its significance in the clinical setting. MD adjusted for age, and BMI is associated with increased risk of BC diagnosis, advanced tumour stage at diagnosis and increased risk of both local recurrence and second primary cancers. The MD measures that predict BC risk have high heritability, and to date several genetic markers associated with BC risk have been found to also be associated with these MD risk predictors. Change in MD could be a predictor of the extent of chemoprevention with tamoxifen. Although the biological and genetic pathways that determine and perhaps modulate MD remain largely unresolved, significant inroads are being made into the understanding of MD, which may lead to benefits in clinical screening, assessment and treatment strategies. This review provides a timely update on the current understanding of MD's association with BC risk.
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Affiliation(s)
- C W Huo
- Department of Surgery, University of Melbourne, St. Vincent's Hospital, Melbourne, Australia,
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Varghese JS, Smith PL, Folkerd E, Brown J, Leyland J, Audley T, Warren RML, Dowsett M, Easton DF, Thompson DJ. The heritability of mammographic breast density and circulating sex-hormone levels: two independent breast cancer risk factors. Cancer Epidemiol Biomarkers Prev 2012; 21:2167-75. [PMID: 23074290 DOI: 10.1158/1055-9965.epi-12-0789] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
BACKGROUND Mammographic breast density and endogenous sex-hormone levels are both strong risk factors for breast cancer. This study investigated whether there is evidence for a shared genetic basis between these risk factors. METHODS Using data on 1,286 women from 617 families, we estimated the heritabilities of serum estradiol, testosterone, and sex-hormone binding globulin (SHBG) levels and of three measures of breast density (dense area, nondense area, and percentage density). We tested for associations between hormone levels and density measures and estimated the genetic and environmental correlations between pairs of traits using variance and covariance components models and pedigree-based maximum likelihood methods. RESULTS We found no significant associations between estradiol, testosterone, or SHBG levels and any of the three density measures, after adjusting for body mass index (BMI). The estimated heritabilities were 63%, 66%, and 65% for square root-transformed adjusted percentage density, dense area, and nondense area, respectively, and 40%, 25%, and 58% for log-transformed-adjusted estradiol, testosterone, and SHBG. We found no evidence of a shared genetic basis between any hormone levels and any measure of density, after adjusting for BMI. The negative genetic correlation between dense and nondense areas remained significant even after adjustment for BMI and other covariates (ρ = -0.34; SE = 0.08; P = 0.0005). CONCLUSIONS Breast density and sex hormones can be considered as independent sets of traits. IMPACT Breast density and sex hormones can be used as intermediate phenotypes in the search for breast cancer susceptibility loci.
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Affiliation(s)
- Jajini S Varghese
- Department of Public Heath and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
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Barnes DR, Antoniou AC. Unravelling modifiers of breast and ovarian cancer risk for BRCA1 and BRCA2 mutation carriers: update on genetic modifiers. J Intern Med 2012; 271:331-43. [PMID: 22443199 DOI: 10.1111/j.1365-2796.2011.02502.x] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Pathogenic mutations in the tumour suppressor genes BRCA1 and BRCA2 confer increased risks for breast and ovarian cancer and account for approximately 15% of the excess familial risk of breast cancer amongst first-degree relatives of patients with breast cancer. There is considerable evidence indicating that these risks vary by other genetic and environmental factors clustering in families. In the past few years, based on the availability of genome-wide association data and samples from large collaborative studies, several common alleles have been found to modify breast or ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. These common alleles explain a small proportion of the genetic variability in breast or ovarian cancer risk for mutation carriers, suggesting more modifiers remain to be identified. We review the so far identified genetic modifiers of breast and ovarian cancer risk and consider the implications for risk prediction. BRCA1 and BRCA2 mutation carriers could be some of the first to benefit from clinical applications of common variants identified through genome-wide association studies. However, to be able to provide more individualized risk estimates, it will be important to understand how the associations vary with different tumour characteristics and their interactions with other genetic and environmental modifiers.
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Affiliation(s)
- D R Barnes
- Department of Public Health and Primary Care, Centre for Cancer Genetic Epidemiology, University of Cambridge, Cambridge, UK
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Yaghjyan L, Colditz GA, Rosner B, Tamimi RM. Mammographic breast density and breast cancer risk by menopausal status, postmenopausal hormone use and a family history of breast cancer. Cancer Causes Control 2012; 23:785-90. [PMID: 22438073 DOI: 10.1007/s10552-012-9936-7] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2011] [Accepted: 03/02/2012] [Indexed: 02/07/2023]
Abstract
PURPOSE Few studies have investigated the association between breast density and breast cancer by a family history of breast cancer, menopausal status, and postmenopausal hormone use (PMH). We investigated if associations of breast density and breast cancer differ according to the status of these risk factors. METHODS This study included 1,481 incident breast cancer cases diagnosed within the Nurses' Health Study I and II cohorts and 2,779 matched controls. Breast density was measured from digitized film images with computerized techniques. Information on breast cancer risk factors was obtained prospectively from the biennial questionnaires before the date of the cancer diagnosis for cancer cases and their matched controls. The data were analyzed with logistic regression. RESULTS Breast cancer risk increased with increasing percent breast density in all strata (p for trend in all subsets <0.0001). The density-related risk of breast cancer was similar in women with and without a family history (OR = 4.00 [95 % CI 2.01-7.94] vs. 3.71 [95 % CI 2.79-4.94] for density ≥50 % vs. <10 %, p for interaction = 0.53). The magnitude of the association between density and breast cancer risk, however, appeared to be stronger in premenopausal women than in postmenopausal women without PMH history (OR = 5.49 [95 % CI 2.44-12.39] vs. 3.02 [95 % CI 1.62-5.63] for density ≥50 % vs. <10 %, p-heterogeneity = 0.17) and appeared to be stronger in postmenopausal women currently using hormones compared with postmenopausal women who never used PMH (OR = 4.50 [95 % CI 2.99-6.78] vs. 3.02, p-heterogeneity = 0.20) or with past hormone use (OR = 4.50 vs. 3.71 [95 % CI 1.90-7.23], p-heterogeneity = 0.23). CONCLUSIONS Findings on associations by menopausal status/hormone use are suggestive and should be examined in additional larger studies.
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Affiliation(s)
- Lusine Yaghjyan
- Department of Surgery, Washington University in St. Louis School of Medicine, St. Louis, MO, USA
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Varghese JS, Thompson DJ, Michailidou K, Lindström S, Turnbull C, Brown J, Leyland J, Warren RML, Luben RN, Loos RJ, Wareham NJ, Rommens J, Paterson AD, Martin LJ, Vachon CM, Scott CG, Atkinson EJ, Couch FJ, Apicella C, Southey MC, Stone J, Li J, Eriksson L, Czene K, Boyd NF, Hall P, Hopper JL, Tamimi RM, Rahman N, Easton DF. Mammographic breast density and breast cancer: evidence of a shared genetic basis. Cancer Res 2012; 72:1478-84. [PMID: 22266113 PMCID: PMC3378688 DOI: 10.1158/0008-5472.can-11-3295] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3,628 breast cancer cases and 5,190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of single-nucleotide polymorphisms (SNP) were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case-control status as the outcome. This analysis was repeated using 10 different cutoff points for the most significant density SNPs (1%-10% representing 5,222-50,899 SNPs). Permutation analysis was also conducted across all 10 cutoff points. The association between risk score and breast cancer was significant for all cutoff points from 3% to 10% of top density SNPs, being most significant for the 6% (2-sided P = 0.002) to 10% (P = 0.001) cutoff points (overall permutation P = 0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR = 1.31; 95% confidence interval (CI), 1.08-1.59] compared with women in the bottom 10%. Together, our results show that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants.
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Affiliation(s)
- Jajini S Varghese
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Deborah J Thompson
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Kyriaki Michailidou
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Sara Lindström
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
| | - Clare Turnbull
- Section of Cancer Genetics, The Institute of Cancer Research, Sutton, Surrey, UK
| | - Judith Brown
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Jean Leyland
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Ruth ML Warren
- Department of Radiology, University of Cambridge, Addenbrooke’s NHS Foundation Trust Cambridge, UK
| | - Robert N Luben
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Ruth J Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Nicholas J Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Johanna Rommens
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Andrew D Paterson
- Program in Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada
- Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Lisa J Martin
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada
| | - Celine M Vachon
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | | | | | - Fergus J Couch
- Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Carmel Apicella
- Centre for M.E.G.A. Epidemiology, Melbourne School of Population Health, The University of Melbourne, Melbourne, Australia
| | - Melissa C Southey
- Genetic Epidemiology Laboratory, Department of Pathology, The University of Melbourne, Melbourne, Australia
| | - Jennifer Stone
- Centre for M.E.G.A. Epidemiology, Melbourne School of Population Health, The University of Melbourne, Melbourne, Australia
| | - Jingmei Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Human Genetics, Genome Institute of Singapore, Singapore
| | - Louise Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Norman F Boyd
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada
| | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - John L Hopper
- Centre for M.E.G.A. Epidemiology, Melbourne School of Population Health, The University of Melbourne, Melbourne, Australia
| | - Rulla M Tamimi
- Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA
- Channing Laboratory, Brigham and Women’s Hospital, Boston, MA, USA
| | - Nazneen Rahman
- Section of Cancer Genetics, The Institute of Cancer Research, Sutton, Surrey, UK
| | - Douglas F Easton
- Centre for Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
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Martin LJ, Melnichouk O, Guo H, Chiarelli AM, Hislop TG, Yaffe MJ, Minkin S, Hopper JL, Boyd NF. Family history, mammographic density, and risk of breast cancer. Cancer Epidemiol Biomarkers Prev 2010; 19:456-63. [PMID: 20142244 DOI: 10.1158/1055-9965.epi-09-0881] [Citation(s) in RCA: 70] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
PURPOSE Mammographic density is a strong and highly heritable risk factor for breast cancer. The purpose of this study was to examine the extent to which mammographic density explains the association of family history of breast cancer with risk of the disease. SUBJECTS AND METHODS We carried out three nested case-control studies in screening programs that included in total 2,322 subjects (1,164 cases and 1,158 controls). We estimated the independent and combined associations of family history and percent mammographic density at baseline with subsequent breast cancer risk. RESULTS After adjustment for age and other risk factors, compared with women with no affected first-degree relatives, percent mammographic density was 3.1% greater for women with one affected first-degree relative, and 7.0% greater for women with two or more affected relatives (P = 0.001 for linear trend across family history categories). The odds ratios for breast cancer risk were 1.37 [95% confidence interval (95% CI), 1.10-1.72] for having one affected relative, and 2.45 (95% CI, 1.30-4.62) for having two or more affected relatives (P for trend = 0.0002). Adjustment for percent mammographic density reduced these odds ratios by 16% and 14%, respectively. Percent mammographic density explained 14% (95% CI, 4-39%) of the association of family history (at least one affected first-degree relative) with breast cancer risk. CONCLUSIONS Percent mammographic density has features of an intermediate marker for breast cancer, and some of the genes that explain variation in percent mammographic density might be associated with familial risk of breast cancer.
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Affiliation(s)
- Lisa J Martin
- Campbell Family Institute for Breast Cancer Research, Ontario Cancer Institute, Toronto, Ontario, Canada.
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19
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Genetic influences on mammographic density in Korean twin and family: the Healthy Twin study. Breast Cancer Res Treat 2010; 124:467-74. [DOI: 10.1007/s10549-010-0852-9] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2009] [Accepted: 03/16/2010] [Indexed: 11/26/2022]
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20
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Gierach GL, Loud JT, Chow CK, Prindiville SA, Eng-Wong J, Soballe PW, Giambartolomei C, Mai PL, Galbo CE, Nichols K, Calzone KA, Vachon C, Gail MH, Greene MH. Mammographic density does not differ between unaffected BRCA1/2 mutation carriers and women at low-to-average risk of breast cancer. Breast Cancer Res Treat 2010; 123:245-55. [PMID: 20130984 DOI: 10.1007/s10549-010-0749-7] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2010] [Accepted: 01/13/2010] [Indexed: 11/26/2022]
Abstract
Elevated mammographic density (MD) is one of the strongest risk factors for sporadic breast cancer. Epidemiologic evidence suggests that MD is, in part, genetically determined; however, the relationship between MD and BRCA1/2 mutation status is equivocal. We compared MD in unaffected BRCA1/2 mutation carriers enrolled in the U.S. National Cancer Institute's Clinical Genetics Branch's Breast Imaging Study (n = 143) with women at low-to-average breast cancer risk enrolled in the same study (n = 29) or the NCI/National Naval Medical Center's Susceptibility to Breast Cancer Study (n = 90). The latter were BRCA mutation-negative members of mutation-positive families or women with no prior breast cancer, a Pedigree Assessment Tool score <8 (i.e., low risk of a hereditary breast cancer syndrome) and a Gail score <1.67. A single experienced mammographer measured MD using a computer-assisted thresholding method. We collected standard breast cancer risk factor information in both studies. Unadjusted mean percent MD was higher in women with BRCA1/2 mutations compared with women at low-to-average breast cancer risk (37.3% vs. 33.4%; P = 0.04), but these differences disappeared after adjusting for age and body mass index (34.9% vs. 36.3%; P = 0.43). We explored age at menarche, nulliparity, age at first birth, menopausal status, number of breast biopsies, and exposure to exogenous hormonal agents as potential confounders of the MD and BRCA1/2 association. Taking these factors into account did not significantly alter the results of the age/body mass index-adjusted analysis. Our results do not provide support for an independent effect of BRCA1/2 mutation status on mammographic density.
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Affiliation(s)
- Gretchen L Gierach
- Hormonal and Reproductive Epidemiology Branch, Division of Cancer Epidemiology and Genetics, Office of Preventive Oncology, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
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