1
1 Association of Type and Location of BRCA1 and BRCA2 Mutations with Risk of 2
Breast and Ovarian Cancer 3 4
5 6
Timothy R. Rebbeck, PhD1,2, Nandita Mitra, PhD1,2, Fei Wan, MS2, Lesley McGuffog, 7
BS3, Yael Laitman, MSC4, Anya Kushnir, MSC5, Shani Paluch-Shimon, MD4, Raanan 8
Berger, MD6, Jamal Zidan, MD7, Eitan Friedman, MD, PhD4, Hans Ehrencrona, MD8,9, 9
Marie Stenmark-Askmalm, MD10, Zakaria Einbeigi, MD11, Niklas Loman, MD8, Katja 10
Harbst, PhD8, Johanna Rantala, PhD12, , Beatrice Melin, MD, PhD13, Dezheng Huo, 11
PhD14, Olufunmilayo I. Olopade, MD14, Joyce Seldon, MSGC15, Patricia A. Ganz, MD15, 12
Robert L. Nussbaum, MD16, Salina B. Chan, BS17, Kunle Odunsi, MD, PhD18, Simon A. 13
Gayther, PhD19, Susan M. Domchek, MD1,20, Banu K. Arun, MD21, Karen H. Lu, MD21, 14
Gillian Mitchell, MD22,23, Beth Y. Karlan, MD24, Christine Walsh, MD24, Jenny Lester, 15
MPH24, Andrew K. Godwin, PhD25, Harsh Pathak, PhD25, Eric Ross, PhD26, Mary B. 16
Daly, MD, PhD26, Alice S. Whittemore, PhD27, Esther M. John, PhD, MSPH28, Alexander 17
Miron, PhD29, Mary Beth Terry, PhD30, Wendy K. Chung, MD, PhD31, David E. Goldgar, 18
PhD32, Saundra S. Buys, MD33, Ramūnas Janavičius, MD, PhD34, Laima Tihomirova, 19
MD35, Nadine Tung, MD36, Cecilia M. Dorfling, PhD37, Elizabeth J. van Rensburg, 20
PhD37, Linda Steele, BS38, Susan L. Neuhausen, PhD38, Yuan Chun Ding PhD38, Bent 21
Ejlertsen, MD, PhD39, Anne-Marie Gerdes, MD40, Thomas v. O. Hansen, MD40, Teresa 22
Ramón y Cajal, MD41, Ana Osorio, PhD42, Javier Benitez, MD43, Javier Godino, MD44, 23
Maria- Isabel Tejada, PhD45, Mercedes Duran, PhD46, Jeffrey N. Weitzel, MD47, Kristie 24
A Bobolis, MD47, Sharon R. Sand, CCRP47, Annette Fontaine, MD47, Antonella 25
Savarese, MS48, Barbara Pasini, MD49, Bernard Peissel, MD50, Bernardo Bonanni, 26
PhD51, Daniela Zaffaroni, MD50, Francesca Vignolo-Lutati, MD52, Giulietta Scuvera, 27
MD50, Giuseppe Giannini, MD53, Loris Bernard, PhD54,55, Maurizio Genuardi, MD56, 28
Paolo Radice, MD57,58, Riccardo Dolcetti, PhD59, Siranoush Manoukian, PhD50, Valeria 29
Pensotti, MD55,58, Viviana Gismondi, MD60, Drakoulis Yannoukakos, PhD61, Florentia 30
Fostira, PhD61, Judy Garber, MD, MPH29, Diana Torres, MD62,63, Muhammad Usman 31
Rashid, MD63,64, Ute Hamann, PhD63, Susan Peock, MS3, Debra Frost, MS3, Radka 32
2
Platte, BS3, D. Gareth Evans, MD65, Rosalind Eeles, PhD66, Rosemarie Davidson, 33
PhD67, Diana Eccles, MD68, Trevor Cole, MD69, Jackie Cook, MD70, Carole Brewer, 34
MD71, Shirley Hodgson, MD72, Patrick J. Morrison, MD DSc73, 35
Lisa Walker, MS74, Mary E. Porteous, MD75, M. John Kennedy, MD76, Louise Izatt, MB 36
BChir PhD77, Julian Adlard, MD78, Alan Donaldson, MD79, Steve Ellis, MSc3, Priyanka 37
Sharma, PhD80, Rita Katharina Schmutzler, MD81, Barbara Wappenschmidt, MD81, 38
Alexandra Becker, MD81, Kerstin Rhiem, MD81, Eric Hahnen, MD81, Christoph Engel, 39
MD82, Alfons Meindl, MD83, Stefanie Engert, MD83, Nina Ditsch, MD83, Norbert Arnold, 40
MD84, Hans Jörg Plendl, MD85, Christoph Mundhenke, MD84, Dieter Niederacher, MD86, 41
Markus Fleisch, MD86, Christian Sutter, PhD87, C.R. Bartram, MD87, Nicola Dikow, MD87, 42
Shan Wang-Gohrke, MD88, Dorothea Gadzicki, MD89, Doris Steinemann, MD89, Karin 43
Kast, MD90, Marit Beer, MD91, Raymonda Varon-Mateeva, MD92, Andrea Gehrigm, 44
MD93, Bernhard H. Weber, MD94, Dominique Stoppa-Lyonnet, PhD95,96,97, Olga M. 45
Sinilnikova, PhD98,99, Sylvie Mazoyer, PhD99, Claude Houdayer, PhD95,97, Muriel Belotti, 46
PhD95, Marion Gauthier-Villars, PhD95, Francesca Damiola, PhD99, Nadia Boutry-Kryza, 47
PhD98, Christine Lasset, PhD100,101, Hagay Sobol, PhD102, Jean-Philippe Peyrat, PhD103, 48
Danièle Muller, PhD104, Jean-Pierre Fricker, PhD104, Marie-Agnès Collonge-Rame, 49
PhD105, Isabelle Mortemousque, PhD106, Catherine Nogues, PhD107, Etienne Rouleau, 50
PhD108, Claudine Isaacs, MD109, Anne De Paepe, MD110, Bruce Poppe, MD110, Kathleen 51
Claes, PhD110, Kim De Leeneer, MD110, Marion Piedmonte, MA111, Gustavo Rodriguez, 52
MD112, Katie Wakely, MD113, John Boggess, MD114, Stephanie V. Blank, MD115, Jack 53
Basil, MD116, Masoud Azodi, MD117, Kelly-Anne Phillips, MD22, Trinidad Caldes, MD118, 54
Miguel de la Hoya, PhD118, Atocha Romero, PhD118, Heli Nevanlinna, PhD119, Kristiina 55
Aittomäki, MD120, Annemarie H. van der Hout, MD121, Frans B.L. Hogervorst, PhD122, 56
Senno Verhoef, PhD122, J. Margriet Collée, PhD123, Caroline Seynaeve, MD, PhD124 , 57
Jan C. Oosterwijk, MD, PhD121, Johannes J.P Gille, MD125, Juul T. Wijnen, MD126, 58
Encarna B. Gómez Garcia, MD127, Carolien M. Kets, MD128, Margreet G.E.M. Ausems, 59
MD129, Cora M. Aalfs, MD130, Peter Devilee, MD131, Arjen R. Mensenkamp, MD128, Ava 60
Kwong, MD132,133,134, Edith Olah, PhD, DSc135, Janos Papp, PhD135, Orland Diez, 61
PhD136,137, Conxi Lazaro, PhD138, Esther Darder, PhD139, Ignacio Blanco, MD140, Mónica 62
Salinas, MS140, Anna Jakubowska, PhD141, Jan Lubinski, MD141, Jacek Gronwald, 63
3
PhD141, Katarzyna Jaworska-Bieniek, PhD141,142, Katarzyna Durda, PhD141, Grzegorz 64
Sukiennicki, PhD141, Tomasz Huzarski, PhD141, Tomasz Byrski, PhD141, Cezary 65
Cybulski, PhD141, Aleksandra Toloczko-Grabarek, PhD141, Elżbieta Złowocka-66
Perłowska, PhD141, Janusz Menkiszak, ND143, Adalgeir Arason, ND144,145, Rosa B. 67
Barkardottir, ND144,145, Jacques Simard, PhD146,147, Rachel Laframboise, MD148,149, 68
Marco Montagna, PhD149, Simona Agata, PhD149, Elisa Alducci, PhD149, Ana Peixoto, 69
PhD150, Manuel R. Teixeira, MD, PhD150,151, Amanda B. Spurdle, PhD152, Min Hyuk Lee, 70
MD153, Sue K. Park, MD154, Sung-Won Kim, MD, PhD155, Tara M. Friebel, MPH2, Fergus 71
J. Couch, PhD156,158, Noralane M. Lindor, MD157, Vernon S. Pankratz, PhD158, Lucia 72
Guidugli, PhD156, Xianshu Wang, PhD156, Marc Tischkowitz, PhD159,160, Lenka Foretova, 73
MD161, Joseph Vijai, MD162, Kenneth Offit, MD162, Mark Robson, MD163, Rohini Rau-74
Murthy, MD163, Noah Kauff, MD163, Anneliese Fink-Retter, MD164, Christian F. Singer, 75
MD164, Christine Rappaport, MD164, Daphne Gschwantler-Kaulich, MD164, Georg Pfeiler, 76
MD164, Muy-Kheng Tea, MD164, Andreas Berger, MD164, Mark H. Greene, MD165, 77
Phuong L. Mai, PhD165, Evgeny N. Imyanitov, MD166, Amanda Ewart Toland, PhD167, 78
Leigha Senter, MD168, Anders Bojesen, PhD169, Inge Sokilde Pedersen, PhD170, Anne-79
Bine Skytte, PhD169, Lone Sunde, PhD171, Mads Thomassen, PhD172, Sanne Traasdahl 80
Moeller, PhD172, Torben A. Kruse, PhD172, Uffe Birk Jensen, PhD171, Maria Adelaide 81
Caligo, MD173, Paolo Aretini, MD173, Soo-Hwang Teo, PhD174,175, Christina G. Selkirk, 82
MS, CCRP176, Peter J. Hulick, MD, MMSc176, Sue Healey, BS152, Douglas F. Easton, 83
PhD3, Georgia Chenevix-Trench, PhD152, Antonis C. Antoniou, PhD3, Katherine L. 84
Nathanson, MD1,20, for the CIMBA Consortium 85
86
87
88 1 Abramson Cancer Center, Perelman School of Medicine University of Pennsylvania, 89
Philadelphia, PA, USA 90 2Center for Clinical Epidemiology and Biostatistics, Perelman School of Medicine at the 91
University of Pennsylvania, Philadelphia, PA, USA 92 3 Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary 93
Care, University of Cambridge, UK 94
4
4 Sheba Medical Center, Tel Aviv, Israel 95 5 The Susanne Levy Gertner Oncogenetics Unit, Sheba Medical Center, Tel Hashomer, 96
Israel 97 6 The Oncology Institute, Sheba Medical Center, Tel Hashomer, Israel 98 7 The Oncology Institute, Rivkah Ziv Medical Center Zefat, Israel 99 8 Department of Oncology, Lund University, Lund, Sweden 100 9 Department of Immunology, Genetics and Pathology, Uppsala University, Uppsala, 101
Sweden 102 10 Division of Clinical Genetics, Department of Clinical and Experimental Medicine, 103
Linköping University, Linköping, Sweden 104 11 Department of Oncology, Sahlgrenska University Hospital, Gothenburg, Sweden 105 12 Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden 106 13 Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden 107 14 Center for Clinical Cancer Genetics and Global Health, University of Chicago Medical 108
Center, Chicago, USA 109 15 UCLA Schools of Medicine and Public Health, Division of Cancer Prevention & 110
Control Research, Jonsson Comprehensive Cancer Center, Los Angeles, CA, USA 111 16 Department of Medicine and Genetics, University of California, San Francisco, USA 112 17 Cancer Risk Program, Helen Diller Family Cancer Center, University of California, 113
San Francisco, USA 114 18Department of Gynecologic Oncology, Roswell Park Cancer Institute, Buffalo, NY, 115
USA 116 19 Department of Preventive Medicine, Keck School of Medicine, University of Southern 117
California, California, USA 118 20 Department of Medicine, Perelman School of Medicine at the University of 119
Pennsylvania, Philadelphia, PA, USA 120 21 University of Texas MD Anderson Cancer Center, Houston, TX, USA 121 22 Division of Cancer Medicine, Peter MacCallum Cancer Centre, East Melbourne, 122
Victoria, Australia 123 23 Sir Peter MacCallum Department of Oncology, The University of Melbourne, 124
Melbourne Australia 125
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24 Women's Cancer Program at the Samuel Oschin Comprehensive Cancer Institute, 126
Cedars-Sinai Medical Center, Los Angeles, USA 127 25Department of Pathology and Laboratory Medicine, University of Kansas Medical 128
Center, Kansas City, KS, USA 129 26 Fox Chase Cancer Center, Philadelphia, Pennsylvania, USA 130 27 Department of Health Research & Policy, Stanford University School of Medicine, 131
Stanford, California, USA 132 28 Department of Epidemiology, Cancer Prevention Institute of California, Fremont, 133
California, USA 134 29 Dana-Farber Cancer Institute, Boston, Massachusetts, USA 135 30 Department of Epidemiology, Columbia University, New York, NY, USA 136 31 Departments of Pediatrics and Medicine, Columbia University, New York, NY, USA 137 32 Department of Dermatology, University of Utah School of Medicine, Salt Lake City, 138
Utah, USA 139 33 Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah 140
School of Medicine, Salt Lake City, USA 141 34 Vilnius University Hospital Santariskiu Clinics, Hematology, Oncology and 142
Transfusion Medicine Center, Department of Molecular and Regenerative Medicine; 143
State Research Institute Innovative Medicine Center Vilnius, Lithuania 144 35 Latvian Biomedical Research and Study Centre, Riga, Latvia 145 36 Department of Medical Oncology, Beth Israel Deaconess Medical Center Boston, MA, 146
USA 147 37 Department of Genetics, University of Pretoria, Pretoria, South Africa 148 38 Department of Population Sciences, Beckman Research Institute of City of Hope, 149
Duarte, CA, USA 150 39 Department of Oncology, Rigshospitalet, Copenhagen University Hospital, 151
Copenhagen, Denmark 152 40 Center for Genomic Medicine, Rigshospitalet, Copenhagen University Hospital, 153
Copenhagen, Denmark 154 41 Oncology Service, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain 155
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42 Human Genetics Group, Spanish National Cancer Centre (CNIO), Madrid, Spain, and 156
Biomedical Network on Rare Diseases (CIBERER). 157 43 Human Genetics Group and Genotyping Unit, Spanish National Cancer Centre 158
(CNIO), Madrid, Spain, and Biomedical Network on Rare Diseases (CIBERER). 159 44 Hospital clinico Universitario "Lozano Blesa", Zaragoza, Spain. Instituto de 160
investigación sanitaria de Aragón (IIS) 161 45 Molecular Genetics Laboratory (Department of Genetics), Cruces University Hospital 162
Barakaldo, Bizkaia, Spain 163 46 Institute of Biology and Molecular Genetics. Universidad de Valladolid (IBGM-UVA), 164
Valladolid, Spain. 165 47 Clinical Cancer Genetics, City of Hope Clinical Cancer Genetics Community 166
Research Network City of Hope, 1500 East Duarte Road, Duarte, California 91010 USA 167 48 Unit of Genetic Counselling, Medical Oncology Department, Istituto Nazionale Tumori 168
Regina Elena, Rome, Italy 169 49 Department of Medical Science, University of Turin, Turin, Italy and and AO Città 170
della Salute e della Scienza, Turin, Italy 171 50 Unit of Medical Genetics, Department of Preventive and Predictive Medicine, 172
Fondazione IRCCS Istituto Nazionale Tumori (INT), Milan, Italy 173 51 Division of Cancer Prevention and Genetics, Istituto Europeo di Oncologia, Milan, 174
Italy 175 52 AO Città della Salute e della Scienza, Turin, Italy 176 53 Department of Molecular Medicine, University La Sapienza, Rome, Italy 177 54 Department of Experimental Oncology, Istituto Europeo di Oncologia., Milan, Italy 178 55 Cogentech Cancer Genetic Test Laboratory, Milan, Italy 179 56 Unit of Medical Genetics, Department of Biomedical, Experimental and Clinical 180
Sciences, University of Florence, Florence, Italy and FiorGen Foundation for 181
Pharmacogenomics, Sesto Fiorentino (FI), Italy 182 57 Unit of Molecular Bases of Genetic Risk and Genetic Testing, Department of 183
Preventive and Predictive Medicine, Fondazione IRCCS Istituto Nazionale Tumori (INT), 184
Milan, Italy 185 58 IFOM, Fondazione Istituto FIRC di Oncologia Molecolare, Milan, Italy. 186
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59 Cancer Bioimmunotherapy Unit, Centro di Riferimento Oncologico, IRCCS, Aviano 187
(PN), Italy 188 60 Unit of Hereditary Cancer, Department of Epidemiology, Prevention and Special 189
Functions, IRCCS AOU San Martino - IST Istituto Nazionale per la Ricerca sul Cancro, 190
Genoa, Italy 191 61 Molecular Diagnostics Laboratory, IRRP, National Centre for Scientific Research 192
"Demokritos" Aghia Paraskevi Attikis, Athens, Greece 193 62 Instituto de Genética Humana, Pontificia Universidad Javeriana, Bogotá, Colombia 194 63 Molecular Genetics of Breast Cancer, Deutsches Krebsforschungszentrum (DKFZ), 195
Heidelberg, Germany 196 64 Department of Basic Sciences, Shaukat Khanum Memorial Cancer Hospital and 197
Research Centre (SKMCH & RC), Lahore, Pakistan 198 65 Genetic Medicine, Manchester Academic Health Sciences Centre, Central 199
Manchester University Hospitals NHS Foundation Trust, Manchester, UK 200 66 Oncogenetics Team, The Institute of Cancer Research and Royal Marsden NHS 201
Foundation Trust, UK 202 67 Ferguson-Smith Centre for Clinical Genetics, Yorkhill Hospitals, Glasgow, UK 203 68 Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton, UK 204 69 West Midlands Regional Genetics Service, Birmingham Women’s Hospital Healthcare 205
NHS Trust, Edgbaston, Birmingham, UK 206 70 Sheffield Clinical Genetics Service, Sheffield Children’s Hospital, Sheffield, UK 207 71 Department of Clinical Genetics, Royal Devon & Exeter Hospital, Exeter, UK 208 72 Clinical Genetics Department, St Georges Hospital, University of London, UK 209 73 Northern Ireland Regional Genetics Centre, Belfast City Hospital, Belfast, UK 210 74 Oxford Regional Genetics Service, Churchill Hospital, Oxford, UK 211 75 South East of Scotland Regional Genetics Service, Western General Hospital, 212
Edinburgh, UK 213 76 Academic Unit of Clinical and Molecular Oncology, Trinity College Dublin and St 214
James's Hospital, Dublin, Eire 215 77 South East Thames Regional Genetics Service, Guy’s Hospital London, UK 216 78 Yorkshire Regional Genetics Service, Leeds, UK 217
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79 South West Regional Genetics Service, Bristol, UK 218 80 Department of Hematology and Oncology, University of Kansas Medical Center, 219
Kansas City, KS, USA 220 81 Centre of Familial Breast and Ovarian Cancer and Centre for Integrated Oncology 221
(CIO), University Hospital of Cologne, Germany 222 82 Institute for Medical Informatics, Statistics and Epidemiology, University of Leipzig, 223
Germany 224 83 Department of Gynaecology and Obstetrics, Division of Tumor Genetics, Klinikum 225
rechts der Isar, Technical University Munich, Germany 226 84 Department of Gynecology and Obstetrics, University Medical Center Schleswig-227
Holstein, Campus Kiel, Germany 228 85 Institute of Human Genetics, University Medical Center Schleswig-Holstein, Campus 229
Kiel, Germany 230 86 Department of Gynaecology and Obstetrics, University Hospital Düsseldorf, Heinrich-231
Heine University Düsseldorf, Germany 232 87 Institute of Human Genetics, Department of Human Genetics, University Hospital 233
Heidelberg, Germany 234 88 Department of Gynaecology and Obstetrics, University Hospital Ulm, Germany 235 89 Institute of Cell and Molecular Pathology, Hannover Medical School, Hannover, 236
Germany 237 90 Department of Gynaecology and Obstetrics, University Hospital Carl Gustav Carus, 238
Technical University Dresden, Germany 239 91 Institute of Human Genetics, Technical University Dresden, Germany 240 92 Institute of Human Genetics, Campus Virchov Klinikum, Charite Berlin, Germany 241 93 Centre of Familial Breast and Ovarian Cancer, Department of Medical Genetics, 242
Institute of Human Genetics, University Würzburg, Germany 243 94 Institute of Human Genetics, University Regensburg, Germany 244 95 Institut Curie, Department of Tumour Biology, Paris, France 245 96 Institut Curie, INSERM U830, Paris, France 246 97 Université Paris Descartes, Sorbonne Paris Cité, France 247
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98 Unité Mixte de Génétique Constitutionnelle des Cancers Fréquents, Hospices Civils 248
de Lyon – Centre Léon Bérard, Lyon, France 249 99 INSERM U1052, CNRS UMR5286, Université Lyon 1, Centre de Recherche en 250
Cancérologie de Lyon, Lyon, France 251 100 Université Lyon 1, CNRS UMR5558, Lyon, France 252 101 Unité de Prévention et d’Epidémiologie Génétique, Centre Léon Bérard, Lyon, 253
France 254 102 Département Oncologie Génétique, Prévention et Dépistage, INSERM CIC-P9502, 255
Institut Paoli-Calmettes/Université d'Aix-Marseille II, Marseille, France 256 103 Laboratoire d'Oncologie Moléculaire Humaine, Centre Oscar Lambret, Lille, France 257 104 Unité d’Oncogénétique, CLCC Paul Strauss, Strasbourg, France 258 105 Service de Génétique Biologique-Histologie-Biologie du Développement et de la 259
Reproduction, Centre Hospitalier Universitaire de Besançon, Besançon, France 260 106 Service de Génétique, Centre Hospitalier Universitaire Bretonneau, Tours, France 261 107 Oncogénétique Clinique, Hôpital René Huguenin/Institut Curie, Saint-Cloud, France 262 108 Laboratoire d'Oncogénétique, Hôpital René Huguenin/Institut Curie, Saint-Cloud, 263
France 264 109 Lombardi Comprehensive Cancer Center, Georgetown University, Washington DC, 265
USA 266 110 Center for Medical Genetics, Ghent University, Ghent, Belgium 267 111 GOG Statistical & Data Center, Buffalo, NY, US 268 112 Evanston Hospital, Evanston, IL, US 269 113 Tufts University, Medford, MA, US 270 114 University of North Carolina, Chapel Hill, NC, US 271 115 New York University, New York, NY, US 272 116 Ohio State, Good Samaritan Hospital, Cincinnati, OH, US 273 117 Yale University School of Medicine, New Haven, CT, US 274 118 Molecular Oncology Laboratory, Hospital Clinico San Carlos, IdISSC, Madrid, Spain 275 119 Department of Obstetrics and Gynecology, University of Helsinki and Helsinki 276
University Central Hospital, Helsinki, Finland 277
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120 Department of Clinical Genetics, Helsinki University Central Hospital, Helsinki, 278
Finland 279 121 Department of Genetics, University Medical Center, Groningen University, 280
Groningen, The Netherlands 281 122 Family Cancer Clinic, Netherlands Cancer Institute, Amsterdam, The Netherlands 282 123 Department of Clinical Genetics, Family Cancer Clinic, Erasmus University Medical 283
Center, Rotterdam, The Netherlands 284 124 Department of Medical Oncology, Family Cancer Clinic, Erasmus University Medical 285
Center, Rotterdam, The Netherlands 286 125 Department of Clinical Genetics, VU University Medical Centre, Amsterdam, The 287
Netherlands 288 126 Department of Human Genetics & Department of Clinical Genetics, Leiden University 289
Medical Center, Leiden, The Netherlands 290 127 Department of Clinical Genetics and GROW, School for Oncology and 291
Developmental Biology, MUMC, Maastricht, The Netherlands 292 128 Department of Human Genetics, Radboud University Nijmegen Medical Centre, 293
Nijmegen, The Netherlands 294 129 Department of Medical Genetics, University Medical Center Utrecht, Utrecht, The 295
Netherlands 296 130 Department of Clinical Genetics, Academic Medical Center, Amsterdam, The 297
Netherlands 298 131 Department of Human Genetics & Department of Pathology, Leiden University 299
Medical Center, Leiden, The Netherlands 300 132 The Hong Kong Hereditary Breast Cancer Family Registry 301 133 Cancer Genetics Center, Hong Kong Sanatorium and Hospital, Hong Kong 302 134 Department of Surgery, The University of Hong Kong, Hong Kong 303 135 Department of Molecular Genetics, National Institute of Oncology, Budapest, 304
Hungary 305 136 Oncogenetics Laboratory, Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron 306
Research Institute (VHIR), Universitat Autonoma de Barcelona 307 137 University Hospital of Vall d'Hebron, Barcelona, Spain. 308
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138 Molecular Diagnostic Unit, Hereditary Cancer Program, IDIBELL-Catalan Institute of 309
Oncology, Barcelona, Spain 310 139 Genetic Counseling Unit, Hereditary Cancer Program, IDIBGI-Catalan Institute of 311
Oncology, Girona, Spain 312 140 Genetic Counseling Unit, Hereditary Cancer Program, IDIBELL-Catalan Institute of 313
Oncology, Barcelona, Spain 314 141 Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, 315
Poland. 316 142 Postgraduate School of Molecular Medicine, Warsaw Medical University, Warsaw, 317
Poland. 318 143 Chair and Department of Surgical Gynecology and Gynecological Oncology of Adults 319
and Adolescents, Pomeranian Medical University, Szczecin, Poland 320 144 Department of Pathology, Landspitali University Hospital 321 145 BMC, Faculty of Medicine, University of Iceland, Reykjavik, Iceland 322 146 Canada Research Chair in Oncogenetics, Cancer Genomics Laboratory, Centre 323
Hospitalier Universitaire de Québec Research Center, Quebec City (Quebec), Canada 324 147 Laval University, 2705 Laurier Boulevard, T3-57, Quebec City (Quebec), Canada 325 148 Medical Genetics Division, Centre Hospitalier Universitaire de Québec Quebec City 326
(Quebec), Canada 327 149 Immunology and Molecular Oncology Unit, Veneto Institute of Oncology IOV - 328
IRCCS, Padua, Italy 329 150 Department of Genetics, Portuguese Oncology Institute, Porto, Portugal 330 151 Biomedical Sciences Institute (ICBAS), University of Porto, Portugal 331 152 Department of Genetics and Computational Biology, Queensland Institute of Medical 332
Research, Brisbane, Australia 333 153 Department of Surgery, Soonchunhyang University and Hospital, Seoul, Korea 334 154 Department of Preventive Medicine, Seoul National University College of Medicine 335
and Cancer Research Institute, Seoul National University, Seoul, Korea 336 155 Department of Surgery, Seoul National University, Bundang Hospital, Seongnam, 337
Korea 338
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156 Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, 339
USA 340 157 Department of Health Science Research, Mayo Clinic, Scottsdale, AZ, USA 341 158 Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA 342 159 Program in Cancer Genetics, Departments of Human Genetics and Oncology, McGill 343
University, Montreal, Quebec, Canada 344 160 Department of Medical Genetics, University of Cambridge, Cambridge, UK 345 161 Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer 346
Institute and MF MU, Brno, Czech Republic 347 162 Clinical Genetics Service, Cancer Biology and Genetics Program, Memorial Sloan-348
Kettering Cancer Center, New York, NY, USA 349 163 Clinical Genetics Service, Memorial Sloan-Kettering Cancer Center, New York, NY, 350
USA 351 164 Dept of OB/GYN and Comprehensive Cancer Center, Medical University of Vienna, 352
Vienna, Austria 353 165 Clinical Genetics Branch, Division of Cancer Epidemiology and Genetics, National 354
Cancer Institute, National Institutes of Health, Rockville, MD, USA 355 166 N.N. Petrov Institute of Oncology, St.-Petersburg, Russia 356 167 Divison of Human Cancer Genetics, Departments of Internal Medicine and Molecular 357
Virology, Immunology and Medical Genetics, Comprehensive Cancer Center, The Ohio 358
State University, Columbus, OH, USA 359 168 Divison of Human Genetics, Department of Internal Medicine, The Comprehensive 360
Cancer Center, The Ohio State University, Columbus, OH, USA 361 169 Department of Clinical Genetics, Vejle Hospital, Vejle, Denmark 362 170 Section of Molecular Diagnostics, Department of Clinical Biochemistry, Aalborg 363
University Hospital, Aalborg, Denmark 364 171 Department of Clinical Genetics, Aarhus University Hospital, Aarhus N, Denmark 365 172 Department of Clinical Genetics, Odense University Hospital, Odense C, Denmark 366 173 Section of Genetic Oncology, Department of Oncology, University and University 367
Hospital of Pisa, Pisa, Italy 368
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174 Cancer Research Initiatives Foundation, Sime Darby Medical Centre, Subang Jaya, 369
Malaysia 370 175 Department of Surgery, Faculty of Medicine, University Malaya Cancer Research 371
Institute, University Malaya, Kuala Lumpur, Malaysia 372 176 NorthShore University HealthSystem, Department of Medicine, Evanston, IL, United 373
States 374
375 376 Running Head: BRCA1/2 Mutation-Specific Cancer Risks 377 378 Corresponding Author: Timothy Rebbeck, Ph.D., Department of Biostatistics and Epidemiology, 379 Center for Clinical Epidemiology and Biostatistics, and Abramson Cancer Center, University of 380 Pennsylvania Perelman School of Medicine, 217 Blockley Hall, 423 Guardian Drive, 381 Philadelphia, PA 19104-6021, Tel: 215-898-1793. Email: [email protected] 382 383
384
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Abstract 385 Importance: Limited information about genotype-phenotype correlations in BRCA1 or BRCA2 386
(BRCA1/2) exists. 387
Objective: A comprehensive evaluation of mutations in BRCA1/2 to identify mutation-specific 388
cancer risks. 389
Design: Observational study of a multicenter cohort of women with disease-associated 390
BRCA1/2 mutations. 391
Setting: An international sample of women with BRCA1/2 mutations from fifty-five centers in 33 392
countries on six continents. 393
Participants: Among 19,581 BRCA1 mutation carriers, 9,052 (46%) were diagnosed with 394
breast cancer, 2,317 (12%) with ovarian cancer, 1,041 (5%) with breast and ovarian cancer, and 395
7,171 (37%) without cancer. Among 11,900 BRCA2 mutation carriers, 6,180 (52%) were 396
diagnosed with breast cancer, 682 (6%) with ovarian cancer, 272 (2%) with breast and ovarian 397
cancer, and 4,766 (40%) without cancer. 398
Interventions: We estimated hazard ratios for breast and ovarian cancer based on mutation 399
type, function, and nucleotide position. 400
Exposures: Exposures of interest were specific mutations with specific locations or effects. 401
Main Outcomes: Breast and ovarian cancer risks. 402
Results: In BRCA1, we identified an ovarian cancer cluster region (OCCR) from c.1380 to 403
c.4062 (approximately exon 11;) conferring a relative ratio of breast vs. ovarian cancer risk (R) 404
of R=0.62 (95%CI: 0.56-0.70; p=9x10-17). We also identified three breast cancer cluster regions 405
located at c.179-c.505 (BCCR1; R=1.46, 95%CI: 1.22-1.74 p=2x10-6), c.4328-c.5563 (BCCR2; 406
R=1.34, 95%CI: 1.01-1.78; p=0.042), and c. 5261-c.5563 (BCCR2’, R=1.38, 95%CI: 1.22-1.55; 407
p=6x10-9). In BRCA2, we identified three OCCRs: the first (OCCR1) spanning c.3249-c.5681 408
that was adjacent to c.5946delT (6174delT; R=0.51, 95%CI: 0.44-0.60; p=6x10-17). The second 409
OCCR spanning c.6645-c.7471 (OCCR2; R=0.57, 95%CI: 41-0.80; p=0.001). We observed 410
15
multiple BCCRs spanning c.1-c.596 (BCCR1; R=1.71, 95%CI: 1.06-2.78; p=0.028), c.772-411
c.1806 (BCCR1’; R=1.63, 95%CI: 1.10-2.40; p=0.014) and c.7394-c.8904 (BCCR2; R=2.31, 412
95%CI: 1.69-3.16 p=0.00002). Mutations that conferred nonsense-mediated decay were 413
associated with differential breast or ovarian cancer risks and conferred an earlier age of breast 414
cancer diagnosis for both BRCA1 and BRCA2. 415
Conclusions and Relevance: Breast and ovarian cancer risks vary by type and location of 416
BRCA1/2 mutations. With appropriate validation, these data may have implications for risk 417
assessment and cancer prevention decision-making in BRCA1/2 mutation carriers. 418
16
419
Introduction 420
Women who have inherited mutations in BRCA1 or BRCA2 (BRCA1/2) have an 421
increased risk of breast and ovarian cancers.1,2 Little is known about how cancer risks differ by 422
BRCA1/2 mutation. An “ovarian cancer cluster region” (OCCR) was reported in both BRCA1 423
and BRCA2 using small sample sets. For BRCA1, mutations 3’ of c.4200-c.4400 were 424
associated with a 20% lower ovarian cancer risk than mutations 5’ of c.4400.3 Thompson 425
reported an increased risk of ovarian vs. breast cancer associated with mutations in c.2282-426
c.4071.4 This effect was attributed to both a decrease in breast cancer risk and an increase in 427
ovarian cancer risk in this region. Mutations in exon 11 of BRCA2 have been suggested to 428
confer higher ovarian vs. breast cancer risk than in other regions of the gene.5 It was 429
hypothesized that this risk variation might be explained by the failure of BRCA1/2 exon 11 430
truncating mutations to trigger nonsense-mediated mRNA decay due to their extremely large 431
size, contrary to truncating mutations in smaller exons. However, this postulate was not 432
supported by the measures of the relative amounts of mRNA transcript encoded by BRCA1/2 433
alleles.6,7 Murine models of different mutations in BRCA1/2 also suggest that genotype-434
phenotype correlations exist,8,9 435
Since the description of the OCCR,a variety of functional domains have been reported in 436
both BRCA1 (Figure 1) and BRCA2 (Figure 2), including the RING, Coiled Coil, BRCA1 C-437
Terminal domains in BRCA1, and BRC repeats, DNA binding, oligonucleotide binding-folds, and 438
Tower domain in BRCA2 have been described.10-12 No studies have reported whether BRCA1/2 439
mutation type is associated with differences in breast and ovarian cancer risk. Thus, we 440
evaluated whether mutation type or location is associated with variation in breast and ovarian 441
cancer risk. 442
443
444
17
445
Methods 446
Study Sample 447
The Consortium of Investigators of Modifiers of BRCA (CIMBA) initiative is an 448
international collaboration of centers on six continents that has collected female carriers of 449
disease-associated BRCA1 and BRCA2 mutations with associated clinical, risk factor, and 450
genetic data. Details of the multicenter CIMBA initiative and information about the participating 451
centers can be found elsewhere.16 All carriers participated in clinical or research studies at the 452
host institutions after providing informed consent under IRB-approved protocols. Fifty-five 453
centers and multicenter consortia (Supplementary Table 1) submitted data that met the CIMBA 454
inclusion criteria.16 These centers represent 33 countries. Data were sent without personal 455
identifying information to the central data repository in accordance with approved data sharing 456
protocols at each contributing center. A total of 19,581 BRCA1 and 11,900 BRCA2 female 457
mutation carriers were eligible for inclusion in this study. The study eligibility criteria included 458
carriage of a disease-associated mutation (described below) and clinical data that could be 459
used to estimate hazard ratios (i.e., cancer diagnosis, ascertainment and follow-up dates). 460
Women were excluded if they carried both a BRCA1 and BRCA2 mutation (N=84, or <0.3% of 461
the total sample) to avoid the potential that the two mutations affect cancer risk in non-462
independent manner. 463
464
Mutation Classification 465
Only carriers with clearly pathogenic BRCA1/2 mutations were included in this 466
analysis. Pathogenic mutations were defined as: 1) mutations generating a premature 467
termination codon, except variants generating a premature termination codon in exon 27 after 468
codon 3,010 of BRCA217; 2) large in-frame deletions that span one or more exons; and 3) 469
deletions of transcription regulatory regions (promoter and/or first exon) expected to cause lack 470
18
of expression of mutant allele. We also included missense variants considered pathogenic by 471
the Breast Cancer Information Core (BIC) committee (http://research.nhgri.nih.gov/bic) and/or 472
published variants classified as pathogenic using multifactorial likelihood approaches.18,19 473
Mutations are described using the Human Genome Variation Society (HGVS) 474
nomenclature (http://www.hgvs.org/mutnomen) in which the nucleotide numbering is from the A 475
of the ATG translation initiator codon. For deletions or insertions the most 3' position possible is 476
arbitrarily assigned to have been changed. The description of mutations is given at genomic 477
level (using cDNA reference sequences NM_007294.3 / BRCA1 and NM_000059 / BRCA2). 478
BIC nomenclature also is presented for common variants that are familiar to many researchers 479
and clinicians by their BIC designation (http://research.nhgri.nih.gov/bic). For BIC 480
nomenclature, cDNA sequences are used as reference sequence (Genbank: U14680 / BRCA1 481
and NM_000059.1/ BRCA2). The nucleotide numbering begins at nucleotide 1 of the cDNA 482
sequence. For deletions or insertions the most 3' position possible was arbitrarily assigned to 483
represent the mutation position in this nomenclature. 484
485
Creation of Mutation Groups for Analysis 486
In order to evaluate mutation-specific effects on cancer risk, we created two sets of 487
mutational groupings defined by 1) “Bins” of mutations defined by base pair location, and 2) type 488
or putative functional domains. A schema of this workflow is shown in Figure 1. These groups 489
are defined in the following sections. 490
491
Mutation Bins 492
In order to identify segments across the intronic and exonic regions of the BRCA1 or 493
BRCA2 genes that may confer different breast vs. ovarian cancer risks, we created “bins” of 494
mutations by base pair location. In this analysis, we divided the genomic regions of both genes 495
to create bins of genomic sequence that contained all deleterious mutations regardless of 496
19
category or function. Bins were constructed by using an algorithm in which each bin contained 497
approximately equal numbers of participants with bin length defined by distance in base pairs. 498
We excluded large genomic rearrangements from this analysis as those mutations span multiple 499
bins, and also undertook a subset analysis with and without missense mutations. The resulting 500
bins are presented in Figure 2 and Supplementary Table 2 for BRCA1 and Figure 3 and 501
Supplementary Table 3 for BRCA2. 502
503
Mutation Type and Functional Domains 504
Mutations were also grouped by type and function. Mutation type was defined here as 505
frameshift, nonsense, missense, splice site, large genomic rearrangement, in-frame, and out-of-506
frame. Genomic rearrangements included all mutations leading to duplications and deletions 507
larger than a single exon. Mutations were also grouped based on potential biological 508
relevance. These groups included individuals who carried in-frame deletions, in-frame 509
deletions, non-splice out-of-frame deletions, and out-of-frame deletions. Missense mutations in 510
BRCA1 were grouped into those within the RING finger and BRCT domains. Based on the 511
criteria outlined above, only 17 (0.1%) of BRCA2 carriers had missense mutations classified as 512
pathogenic; these were removed from the analysis, because the sample size was too small to 513
provide statistically meaningful inferences. Comparisons also were made of mutations 514
predicted not to lead to nonsense-mediated decay (NMD) vs. those that do lead to NMD. 515
Mutations predicted not to cause NMD were defined as those that lead to a stop codon within 50 516
nucleotides before or within the last exon.20 No truncating mutation was present within 50 517
nucleotides of the start codon, which also is predicted not to lead to NMD. In BRCA1, a sub-518
group including premature termination codons before c.297, presumed to allow re-initiation of 519
translation at the AUG at that site, was examined separately.21 Premature termination codons 520
refer to all mutations leading to a truncated open reading frame. Putative functional domains in 521
20
BRCA1 and BRCA2 were defined using the boundaries in the Pfam database 522
(http://pfam.sanger.ac.uk/). 523
In addition to the definition of bins and functional mutations, we also identified reported 524
domains in BRCA1 or BRCA2 that are involved in binding putative proteins. These domains 525
(and their putative or known binding partners) include domains in BRCA1 such as the RING 526
domain that interacts with BARD1; a region 3’ of the RING domain that interacts with BRCC36; 527
a region in exon 11 that interacts with CHEK2; the coiled coil domain that interacts with PALB2, 528
ATM, and CTiP; and the BRCT domain that interacts with BACH1 and CHK2. Domains and 529
their putative interacting proteins in BRCA2 include and a region in the 5’ region that interacts 530
with PALB2; the BRC domain that interacts with RAD51; the OB folds domain that also interacts 531
with RAD51; and the Tower domain that interacts with ssDNA. These domains and their 532
specific nucleotide localizations are described in Table 4, and are represented graphically in 533
Figures 2 and 3. 534
535
Statistical Analysis 536
The primary events of interest were diagnosis of ovarian cancer or breast cancer. For 537
ovarian cancer, observations were censored at the earliest of the following events: bilateral risk-538
reducing salpingo-oophorectomy, death, or having reached the end of follow-up without an 539
ovarian cancer or other censoring event. In women with both breast and ovarian cancer 540
diagnoses, prior breast cancer diagnoses were ignored in the analysis of ovarian cancer. Time 541
to event was computed from birth to age at first ovarian cancer diagnosis or age at censoring. 542
For the primary event of breast cancer, observations were censored at the earliest of the 543
following events: ovarian cancer, risk-reducing salpingo-oophorectomy, risk-reducing 544
mastectomy, death, or having reached the end of follow-up without a cancer or other censoring 545
event. Time to event was computed from birth to age at first cancer diagnosis or age at 546
censoring. To account for intra-cluster dependence due to multiple individuals from the same 547
21
family, a robust sandwich variance estimate was specified in our Cox proportional hazards 548
models using the method of Lin and Wei22. All analyses were undertaken in BRCA1 and 549
BRCA2 mutation carriers separately. Cox proportional hazards models were used to analyze 550
the data after the proportional hazards assumption underlying the Cox model was tested using 551
log (-log) plots and Schoenfeld residuals test. 552
Our analyses included three different approaches to assess the relationship of mutation 553
groups (i.e., bins, type, and function) with cancer risk. First, we used the mutation bins to 554
evaluate whether there is evidence to support the previous report of an “ovarian cancer cluster 555
region” (OCCR)3,5, and whether “breast cancer cluster regions” (BCCR) may exist. To assess 556
whether specific genomic regions of these genes confer greater breast vs. ovarian cancer risk, 557
we computed the hazard ratio of breast cancer, the hazard ratio of ovarian cancer, and the ratio 558
of breast vs. ovarian cancer hazard ratio estimates. We evaluated the presence of mutations 559
that conferred breast vs. ovarian cancer risk by comparing bins of mutations across the span of 560
BRCA1 or BRCA2 compared with all other mutations not contained in that bin. In order to 561
compare the effect of mutational bins on the diagnosis of breast versus ovarian cancer, we 562
estimated ratios of the hazard ratios of breast cancer versus ovarian cancer. To accomplish 563
this, we fitted a multiple correlated events model stratified by cancer site23. This approach 564
allowed us to achieve two goals: first, to estimate the correlation between ovarian and breast 565
cancer events within an individual; and second, to provide an estimate of the ratio of hazard 566
ratios (estimated via an interaction term between cancer site and mutation bin) with the correct 567
confidence interval using robust sandwich variance estimates to account for the correlation 568
between events within a woman. All analyses were adjusted for birth year, race, stratified by 569
center, and controlled for clustering within family. 570
Secondly, we compared each mutation type or functional group against a common 571
reference group. The use of a common reference group allowed us to compare hazard ratio 572
estimates across different mutation classes. For both BRCA1 and BRCA2, we chose exon 11 573
22
nonsense mutations as the common reference group. This choice was based on the fact that 574
this group is large and therefore provides optimal statistical power for all analyses, particularly 575
those stratified by mutation type or effect that resulted in relatively small groups. Additionally, 576
exon 11 nonsense mutations come from diverse ethnic backgrounds and all studied have been 577
demonstrated to have the same biological effect, leading to NMD24. Third, we considered a 578
limited number of direct comparisons between two mutually exclusive groups of mutations. 579
These comparisons provide different but complementary assessments of mutation-specific 580
risks. 581
Approximate cancer penetrances to age 70 were estimated to compare two groups: 1) 582
the overall cancer penetrance among all carriers, as specified by the meta analysis of Chen and 583
Parmigiani 25, and 2) the alternative penetrances as computed for a mutation-specific group. 584
For BRCA1, Chen and Parmigiani estimated lifetime breast cancer penetrance as 57% and 585
ovarian cancer penetrance as 40%. For BRCA2, breast cancer penetrance was 49% and 586
ovarian cancer penetrance was 18%. We let p(X=0) be the prevalence of the overall risk group 587
and p(X=1) be the prevalence of the mutation-specific risk group and RR(X) be the relative risk 588
(as estimated here by the hazard ratio) with X=0 representing the overall relative risk. We 589
approximated the mutation-specific penetrance as: 590
Penetrance(X=0) = Penetrance / [RR(X) p(X=1) + p(X=0) 591
Penetrance(X=1) = Penetrance / [p(X=1+ p(X=0)/RR(X)] 592
Statistical tests were considered to be significant based on two-sided hypothesis tests 593
with p< 0.05. For all analyses, we present p-values corrected for multiple hypothesis testing 594
using the Benjamini-Hochberg method.26 95% confidence intervals (CI) are also presented in 595
some analyses, but corrected p-values were the basis for all inferences. Multiple testing 596
corrections were applied within each table of results presented below. All analyses were 597
conducted in SAS version 9 (SAS Institute Inc., Cary, NC) or R version 2.7.2 (R Foundation for 598
Statistical Computing, Vienna, Austria). 599
23
600
Results 601
Study Sample 602
Table 1 reports the distribution of dates of ascertainment to the study as well as time 603
from ascertainment to cancer diagnosis or censoring, as used in the survival analysis models 604
reported below. Median age of breast cancer diagnosis was 39.9 years in BRCA1 and 42.8 605
years in BRCA2. Median age of ovarian cancer diagnosis was 50.0 years in BRCA1 and 54.5 606
years in BRCA2. 607
608
BRCA1: Breast and Ovarian Cancer Cluster Regions 609
Consistent with prior reports, we observed an OCCR bounded by c.1380-c.4062 (Figure 610
1) suggesting a 37% relative decrease in breast cancer risk relative to ovarian cancer risk (ratio 611
of hazard ratios (R)=0.62, 95% CI: 0.56-0.70, false-discovery rate (FDR)-corrected p-612
value=9x10-17). Note that any inference of an elevated ovarian cancer will correspond to a value 613
of R<1. This estimate is a summary estimate obtained by considering all mutations across 614
multiple bins spanning the OCCR. Statistically significant evidence for a relatively higher 615
ovarian vs. breast cancer risk among carriers of mutations was observed in bins 9, 11-13, 15-16 616
and 23 (Figure 2). Elevated ratios suggesting higher ovarian vs. breast cancer risk were also 617
observed in many intervening bins between 9 and 23, but were not statistically significant. The 618
OCCR is explained by both a relative decrease in breast cancer risk and a relative increase in 619
ovarian cancer risk (Supplementary Table 2). The putative OCCR extends further 5’ of the 620
previously reported OCCR, which was defined by the interval c.2282-c.4071.3 Of note, the 621
putative OCCR is entirely contained within exon 11 (c.670-c.4096) with flanking bins (6 and 23) 622
approximately co-incident with the boundaries of the exon. 623
We also observed a relative increase in breast cancer risk and a relative decrease in 624
ovarian cancer risk for mutations occurring in the 5’ and 3’ regions of BRCA1, potentially 625
24
defining two ‘Breast Cancer Cluster Regions’ (Figure 2). The putative BCCR1 mutations within 626
bins 4-5 (c.179-c.505) conferred significantly excess risks of breast vs. ovarian cancer 627
(Supplementary Table 2), and lie within and 3’ of the RING domain (c.72-c.192, Figure 2). 628
Mutations in the BCCR1 confer a 46% relative increase in breast cancer risk relative to ovarian 629
cancer risk; R=1.46 (95% CI: 1.22-1.74, FDR-corrected p-value=2x10-6). When all mutations in 630
the RING domain were considered together as compared with all others, they associated with a 631
significant increase in breast cancer risk (HR=1.13, 95%CI: 1.02-1.26; Table 4) and a significant 632
decrease in ovarian cancer risk (HR=0.81, 95%CI: 0.67-0.97). Bin 2, which contains only the 633
founder mutation BRCA1 c.68_69delAG (185delAG), did not provide statistically significant 634
evidence for elevated breast vs. ovarian cancer risks, suggesting that this mutation may confer 635
relatively equivalent risks of both cancers. 636
Mutations in bins 26 and 29-30 in the 3’ region of BRCA1 also provided evidence for 637
additional BCCRs. BCCR2 conferred a 34% increase in breast cancer relative to ovarian 638
cancer risk (R=1.34, 95% CI: 1.01-1.78, p-value=0.042) bounded by c.4328-c.4945. The 639
second segment of this BCCR (denoted BCCR2’) includes the BRCT domains (c.4926-c.5169 640
and c.5268-c.5526) and was associated with a 38% relative excess of breast vs. ovarian 641
cancers (HR=1.38, 95%CI: 1.22-1.55; p-value=6x10-9; Figure 2 and Table 4). In the BRCT 642
domains, the preponderance of mutations was missense, not expected to trigger NMD. This 643
region also includes bin 29, which contains only the BRCA1 c.5266dupC (5382insC) mutation, 644
which also is not predicted to lead to NMD as it introduces a premature termination codon in the 645
last exon.6 BRCA1 c.5277+1G>A, a splice site mutation, was a frequent mutation in bin 30. 646
This mutation is commonly observed in the Netherlands and also is not expected to lead to 647
NMD. 648
To complement the prior set of analyses, we also present associations of breast and 649
ovarian cancers among groups of BRCA1 mutation carriers defined by known DNA binding 650
domains (Table 4). We compared breast and ovarian cancer risks between women who had a 651
25
mutation in a specified domain compared with all other women who did not have mutations in 652
that domain. As above, mutations in the RING domain conferred higher breast cancer risks and 653
statistically non-significant lower ovarian cancer risks than mutations not occurring in the RING 654
domain after false discovery rate p-value correction. These results are consistent with the 655
colocation of the BCCR1 (Figure 1) and RING domain. Mutations in the BRCT domains 656
conferred higher breast cancer risk; ovarian cancer risk was not statistically significantly lower. 657
These results persisted even when we limited the analyses to mutation subsets (Table 4). 658
When analyses were limited to mutations conferring NMD, breast cancer risk became 659
significantly associated with mutations in the Coiled Coil domain. 660
661
BRCA1: Risks by Category and Function 662
Table 2 presents associations of breast and ovarian cancers among groups of BRCA1 663
mutation carriers that were defined to evaluate the role of specific mutations by category and 664
function. We observed variability in breast and ovarian cancer risks by mutation class. For 665
BRCA1-associated breast cancer, most risk groups conferred higher breast cancer risk than the 666
exon 11 nonsense mutation reference group. This result is consistent with the data shown in 667
Figure 1 and Supplementary Table 2 that demonstrate that mutations in exon 11 confer 668
generally lower breast and higher ovarian cancer risks, as it essentially is congruent with the 669
OCCR. Groups with elevated breast cancer risk include all premature termination codon 670
mutations, except for exon 11 nonsense mutations (Group 2; HR=1.25, 95%CI: 1.12-1.38), 671
frameshift and nonsense mutations occurring 5’ of c.297 that are predicted to lead to NMD and 672
re-initiation (Group 3; HR=1.40, 95%CI: 1.12-1.74), and non-premature termination codon 673
mutations (Group 4; HR=1.51, 95%CI: 1.34-1.70); all founder mutations (Group 5; HR=1.41, 674
95%CI: 1.23-1.61) as well as c.68_69delAG (Group 5a; HR=1.14, 95%CI: 0.94-1.38) and 675
c.5266dupC (Group 5b; HR=1.63, 95%CI: 1.41-1.89); missense mutations in the RING domain 676
(Group 6.1; HR=1.56, 95%CI: 1.32-1.84), missense mutations in the RING domain (Group 6.1; 677
26
HR=1.56, 95%CI: 1.32-1.84), missense mutations and in-frame deletions (Group 7; HR=1.42, 678
95%CI: 1.22-1.66); all in-frame deletions (Group 8; HR=2.41, 95%CI: 1.41-4.11), and premature 679
termination codon mutations not leading to NMD (Group 9; HR=1.58; 95%CI: 1.38-1.80). Since 680
the majority of the last group is comprised of c.5266dupC (83%), the similar increased breast 681
cancer risk is expected. For BRCA1-associated ovarian cancer (Table 2), mutations associated 682
with significantly lower ovarian cancer risks compared with the reference group included all 683
groups except for mutations 5’ of c.297 and missense mutations in the BRCT domain. 684
When comparing mean age differences among women with or without a specific 685
mutation category or function, we found small but statistically significant differences. In BRCA1, 686
exon 11 mutations were associated with earlier ages at breast and ovarian cancer diagnosis. 687
Mutations conferring NMD or premature termination codon were associated with a later age at 688
breast cancer diagnosis. Conversely, an earlier age at breast cancer diagnosis was associated 689
with non-premature termination codon mutations, the founder mutation c.5266dupC, and all 690
premature termination codon mutations not leading to NMD (Table 3). 691
692
BRCA2: Breast and Ovarian Cancer Cluster Regions 693
We observed an OCCR (denoted OCCR1) bounded by c.3249-c.5681, containing 694
c.5946delT (6174delT), with statistically significant evidence for a relatively higher ovarian 695
cancer vs. breast cancer risk among carriers of mutations in bins 6-9 and 11 (Figure 3). The 696
OCCR conferred a 49% increase in ovarian cancer relative to breast cancer risk (R=0.51, 95% 697
CI: 0.44-0.60, p-value=6x10-17). The OCCR1 is explained by both a relative decrease in breast 698
cancer risk and a relative increase in ovarian cancer risk (Supplementary Table 3). The 699
putative OCCR1 lies within the previously reported OCCR, but covers a narrower region of 700
BRCA2 than previously reported.3 The putative OCCR1 is entirely contained within exon 11 and 701
approximately co-localized with the BRC repeats. A second putative OCCR (OCCR2) outside 702
of the original OCCR boundaries also was observed. The OCCR2 was defined by bin 14 703
27
(c.6645-c.7471). OCCR2 conferred a 43% increase in ovarian cancer relative to breast cancer 704
risk (R=0.57, 95% CI: 0.41-0.80, p-value=0.001). 705
We also observed a relative increase in breast cancer risk and a relative decrease in 706
ovarian cancer risk for mutations occurring in the 5’ and 3’ regions of BRCA2, potentially 707
defining multiple ‘Breast Cancer Cluster Regions‘ (i.e., BCCR1, BCCR1' and BCCR2; Figure 1). 708
These three regions conferred relatively increased breast cancer relative to ovarian cancer risk 709
with R=1.71 (95% CI: 1.06-2.78, p-value=0.028), R=1.63 (95% CI: 1.10-2.40, p-value=0.014) 710
and R=2.31 (95% CI: 1.69-3.16, p-value=0.00002), respectively. These regions were 711
associated with both increased breast cancer risk and decreased ovarian cancer risk 712
(Supplementary Table 3). 713
We also observed small but statistically significant differences in the mean age at 714
diagnosis associated with some of these regions. The mean age of breast cancer diagnosis 715
was greater for mutations in OCCR vs. mutations not in OCCR (45.0 vs. 43.9 years, p<0.0001), 716
lower for mutations in BCCR1 vs. mutations not in BCCR1 (42.6 vs. 44.3 years; p=0.004), and 717
lower for mutations in BCCR2 vs. mutations not in BCCR2 (43.5 vs. 44.3 years, p=0.036). 718
There was no difference in mean age of ovarian cancer diagnosis for BCCR1, BCCR2, or 719
OCCR. 720
To complement the prior set of analyses, we also present associations of breast and 721
ovarian cancers among groups of BRCA2 mutation carriers defined by known DNA binding 722
domains (Table 4). We compared breast and ovarian cancer risks between women who had a 723
mutation in a specific domain compared with all other women who did not have mutations in that 724
domain. Mutations in the BRC repeats conferred lower breast cancer risks and higher ovarian 725
cancer risks than those mutations not occurring in the BRC repeats. These results are 726
consistent with the co-location of the OCCR1 (Figure 2) and BRC repeats. These results 727
persisted even when we limited the analyses to mutation subsets, such as only those that 728
confer NMD (Table 4). 729
28
730
BRCA2: Risks by Category and Function 731
For BRCA2-associated cancer, the reference exon 11 mutation group was associated 732
with decreased breast cancer risk compared to most other mutation classes (Table 3), 733
consistent with its location in OCCR1. Compared with the reference group, ovarian cancer risks 734
were even further reduced among women who carried premature truncation codons (HR=0.27, 735
95%CI: 0.11-0.66). We observed an earlier age at breast cancer diagnosis with exon 11 736
mutations and earlier mean age at breast cancer diagnosis for mutations not conferring NMD 737
(Table 3). 738
739
Cancer Penetrance 740
Using the relative risks, as estimated by the hazard ratio, we present approximate penetrances 741
that represent the range of statistically significant changes observed in Tables 2-3. We present 742
these approximate penetrance estimates so that readers can compare the changes we observe 743
to published penetrance estimates. However, the penetrances presented here do not represent 744
absolute risk estimates that would be required in a genetic counseling setting, as they do not 745
account for non-cancer events that may influence a woman’s life expectancy. Using the 746
baseline lifetime risks for breast and ovarian cancer of Chen and Parmigiani25 shown in Table 5, 747
we computed the mutation-specific lifetime risk that would be applicable to women who carry 748
the specific mutation. Also in Table 5, the overall lifetime breast cancer risk for BRCA1 749
mutation carriers is 57%. This risk would increase to 69% in women who carry a missense 750
mutation, Jewish founder mutation, or a mutation that undergoes NMD with re-initiation. Lifetime 751
ovarian cancer risk in BRCA1 mutation carriers is estimated to be 40% overall, but would 752
decrease to half that value (20%) in women who carry an in-frame deletion. Similarly, the 753
lifetime risk of ovarian cancer would change from 18% in BRCA2 mutation carriers to 6% in 754
women with BRCA2 mutations that do not result in protein truncating codons. 755
29
756
Discussion 757
We have identified mutations in BRCA1 or BRCA2 that are associated with significantly 758
different risks of breast vs. ovarian cancers. These mutation-specific risks coincide with known 759
or hypothesized functional domains, and provide a basis around which precise risk estimates 760
can be generated for women who have inherited a particular BRCA1/2 mutation. 761
Our analyses have confirmed the existence of OCCRs that confer relatively increased 762
ovarian cancer risks accompanied by relatively lower breast cancer risks. We also report the 763
existence of BCCRs that confer relatively high breast cancer risks and relatively lower ovarian 764
cancer. These results are consistent with prior reports of OCCRs in both BRCA1 and BRCA2, 765
although the regions defined here differ from those described previously.3 NMD is triggered by 766
premature termination codons in exons 11,7 so difference in the ability to trigger NMD is unlikely 767
to be the explanation for the observation of the OCCRs. NMD eliminates aberrant mRNAs that 768
would result in truncated proteins and therefore leads to haploinsufficiency of the protein. 27,28 769
mRNAs that do not undergo NMD may lead to proteins with a deleterious dominant negative 770
gain of function effects, which in many diseases results in a more severe phenotype than 771
haploinsufficency.29,30 Mutations in exon 11 would potentially be consistent with the production 772
of the exon 11 (in-frame) splice variant despite NMD of the full length version of BRCA1,6 773
whereas mutations outside of exon 11 would cause NMD of both the full length and exon 11 774
splice variant. Murine embryos carrying the exon 11-deleted isoform survive longer than those 775
that are BRCA1 null, and BRCA1-delta11 appears to retain partial function.31 Thus, it is 776
possible that individuals carrying mutations within exon 11 may have a different phenotype than 777
those with mutations outside exon 11. However, further studies, including experimental 778
validation, need to be done to determine if this postulate is correct. 779
In BRCA2, we have identified a region defined by BRCA2 c.3249-c.5946, which may 780
extend out to c.6645-c.7471, associated with a relatively elevated ovarian cancer risk and lower 781
30
breast cancer risk. This result is consistent with prior reports of an OCCR.5,32,33 This region 782
also coincides with the eight BRC repeats in BRCA2. Mutations in the region containing the 783
BRC repeats appear to be associated with NMD, so persistence of truncated proteins in this 784
region cannot explain the genotype-phenotype correlations observed in the OCCR.7 The 785
BRCA2 BRC repeats interact with RAD51, which has been consistently shown to be a modifier 786
of BRCA2-associated breast and ovarian cancer risk15. It is possible that there is persistence of 787
an alternatively spliced variant of BRCA2, without exon 11 (as for BRCA1). This mutation would 788
be in-frame. Without the BRC repeats, BRCA2 might differ in interactions with RAD51 and lead 789
to genotype-phenotype variation. However, the OCCR does not extend throughout all of exon 790
11, arguing against this hypothesis. Thus, the functional basis of the OCCR in BRCA2 remains 791
unknown. 792
In BRCA2, putative BCCR regions defined by c.1-c.596, c.772-c.1806, and c.7394-793
c.8904 were observed. The 3’ BCCR coincides approximately with mutations occurring in the 794
oligonucleotide binding fold domains (c.8010-c.8400 and c.9156-c.9570), and the Tower domain 795
(BRCA2 c.8443-c.8616). When examined independently, both of these domains also confer 796
relatively elevated breast cancer risk and relatively lower ovarian cancer risk. These mutations 797
in BRCA2 would be predicted to undergo NMD; however, it has been demonstrated 798
experimentally for only a few mutations.7 Therefore, the functional basis for this difference in 799
risk is unknown. 800
We have also identified a decreased risk of ovarian cancer associated with all types of 801
mutations predicted not to lead to NMD in BRCA2, however the HR was only significant for all 802
mutations together and those mutations leading to in-frame splice site or frameshift mutations 803
(Table 3). These mutations are all after nucleotide 7000, so in the in the C-terminus of BRCA2, 804
which includes the DNA binding domains, Tower domains and OB folds are associated with 805
localization of BRCA2 to sites of double stranded DNA breaks to accomplish repair.34 These 806
31
data suggest that intact protein may be protective when it comes to ovarian cancer risk 807
However, the number of individuals is small; replication is required in other studies. 808
The strengths of this report include the large sample size that reflects a geographically 809
and racially/ethnically diverse set of BRCA1/2 mutation carriers. The mutations have been 810
consistently evaluated for pathogenicity and coded according to a common protocol. In 811
addition, while the sample set studied here may not represent the general population, it 812
represents those women who are most likely to undergo genetic testing and risk assessment. 813
Nonetheless, the sample is over-enriched for women of European descent, and additional study 814
of non-Caucasian populations is warranted. 815
A number of limitations of this research may influence the generalizability and 816
translational potential of this research. Despite the very large sample size, we were not able to 817
investigate some mutation and risk groups with adequate statistical power. BRCA2 mutation 818
carriers comprised a smaller sample set; in particular, we were limited by the number of women 819
with BRCA2-associated ovarian cancers. Although all women with a documented disease-820
associated mutation in the CIMBA database were included in this analysis, some mutations may 821
not have been ascertained in populations that use screening for founder mutations as a primary 822
method of mutation detection. For example, many women of Jewish ancestry are tested by a 823
mutation panel including only the three known Jewish founder mutations. This testing strategy 824
may lead to under-reporting of non-founder mutations in Jewish women. As such, some bias in 825
the ascertainment of the full spectrum of mutations could have occurred. The ascertainment 826
strategy generally followed clinical and research protocols that were similar across all centers. 827
However, we did not correct for ascertainment explicitly in the present analysis. Thus, bias due 828
to ascertainment may have affected some variables (e.g., age at diagnosis), and thus these 829
should be interpreted with caution. Furthermore, the mutation testing was performed using 830
methods acceptable for clinical practice at each center, which was not uniform across all 831
centers. The present sample set does not reflect the general population of all mutation carriers, 832
32
but reflects the population of women who have undergone genetic testing for BRCA1/2 833
mutations. Thus, the sample set studied here reflects a relevant population of inference (i.e., 834
those who received genetic testing). 835
We have presented the mutations in terms of category or effect, but these designations 836
are in some cases extrapolated based on experimental evidence for similar mutations. An 837
example is the designation of NMD inferred from mutation location, which is based on 838
experimental validation of only a small number of mutations.6,7 Similarly, inference of protein 839
truncation based on predicted protein truncating mutations without experimental verification may 840
lead to erroneous classification24. Finally, the present report of >32,000 mutation carriers could 841
include some of those individuals who were included in the 1995 and 1997 papers that originally 842
reported the OCCR3. It is not possible at this time to know if any of the 32 BRCA1 mutation 843
carrying families or 25 BRCA2 families originally reported also are included in the present 844
sample. However, it is highly unlikely that the small sample of individuals represented in the 845
original reports would outweigh a potential null effect in the >32,000 individuals studied here. 846
This study is the first step in defining differences in risk associated with location and type 847
of BRCA1 and BRCA2 mutations. Pending additional mechanistic insights into the observed 848
associations, knowledge of mutation-specific risks could provide important information for 849
clinical risk assessment in BRCA1/2 mutation carriers. We report that lifetime cancer 850
penetrance may vary depending on the mutation that a woman has inherited. For example, the 851
overall lifetime ovarian cancer penetrance is 18% in BRCA2 mutation carriers 25. However, this 852
risk decreases to 6% in women with mutations that do not result in protein truncating codons. It 853
is not currently understood what level of absolute risk change will influence decision-making in 854
women with these mutations, but it is well known that use of preventive surgery can reduce 855
cancer risk and mortality in this population.36 Additional research will be required to better 856
understand what level of risk difference will change decision-making and standards of care for 857
BRCA1 and BRCA2 mutation carriers. With further validation and generation of formal absolute 858
33
risk estimates, it may be possible to personalize the timing of preventive strategies, maximize 859
fertility, diminish potential consequences of surgical menopause, and decrease cancer risk and 860
mortality by using information about the specific risks conferred by each woman’s mutation. 861
862
Conclusion 863
We found heterogeneity in risk associated with BRCA1 or BRCA2 mutations. We confirm and 864
refine the previously defined ovarian cancer cluster region, and define breast cancer cluster 865
regions in both BRCA1 and BRCA2. Despite statistically significant differences, given the 866
relatively small differences in age of diagnosis of cancers, the results should be used with 867
caution to guide clinical decision-making at this time. However, this study does lay the 868
groundwork for future research, which may better personalize risk based on mutational type and 869
location. 870
34
Role of Sponsor 871
The sponsors of this research had no role in the design and conduct of the study; collection, 872
management, analysis, and interpretation of the data; and preparation, review, or approval of 873
the manuscript. 874
875
Acknowledgments 876 ACA, HAP and the CIMBA data management are funded by Cancer Research – UK. DFE is a 877 Principal Research Fellow of Cancer Research - UK. TRR is supported by R01-CA083855 and 878 R01-CA102776 and P50-CA083638. TRR, KLN, TF, and SMD are supported by the Basser 879 Research Center at the University of Pennsylvania. KLN is supported by the Breast Cancer 880 Research Foundation. SMD and KLN are supported by the Rooney Family Foundation. BP is 881 supported by R01-CA112520. Cancer Research - UK provided financial support for this work. 882 ACA is a Senior Cancer Research UK Cancer Research Fellow. DFE is Cancer Research – UK 883 Principal Research Fellow. KAP is a National Breast Cancer Foundation (Australia) Practitioner 884 Fellow. The authors wish to thank Dr. Jinbo Chen for her valuable input regarding appropriate 885 statistical methods. There are no conflicts of interest for any of the authors. TRR is independent 886 of any commercial funder, had full access to all the data in the study and takes responsibility for 887 the integrity of the data and the accuracy of the data analysis. 888 889 Funding Acknowledgements, by center: 890 891 BCFR (all) 892 The BCFR is funded by grant UM1 CA164920 from the National Cancer Institute. The content of 893 this manuscript does not necessarily reflect the views or policies of the National Cancer Institute 894 or any of the collaborating centers in the BCFR, nor does mention of trade names, commercial 895 products, or organizations imply endorsement by the US Government or the BCFR. 896 BCFR (New York) 897 This research was funded by NCI U01CA069398. 898 BRBOCC 899 BFBOCC is partly supported by: Lithuania (BFBOCC-LT): Research Council of Lithuania grant 900 LIG-07/2012 and Hereditary Cancer Association (Paveldimo vėžio asociacija); Latvia (BFBOCC-901 LV) is partly supported by LSC grant 10.0010.08 and in part by a grant from the ESF 902 Nr.2009/0220/1DP/1.1.1.2.0/09/APIA/VIAA/016 and Liepaja's municipal council. 903 BIDMC 904 BIDMC acknowledges Breast Cancer Research Foundation (BCRF). 905 BMBSA 906 BRCA-gene mutations and breast cancer in South African women (BMBSA) was supported by 907 grants from the Cancer Association of South Africa (CANSA) to Elizabeth J. van Rensburg. 908 BRICOH 909 NIH R01CA74415 and P30 CA033752. SLN was partially supported by the Morris and Horowitz 910 Families Endowed Professorship. 911 CBCS 912 This work was supported by the NEYE Foundation. 913 CNIO 914
35
This work was partially supported by Spanish Association against Cancer (AECC08), RTICC 915 06/0020/1060, FISPI08/1120, Mutua Madrileña Foundation (FMMA) and SAF2010-20493 916 COH-CCGCRN 917 The City of Hope Clinical Cancer Genetics Community Research Network is supported by 918 Award Number RC4A153828 (PI: J. Weitzel) from the National Cancer Institute and the Office of 919 the Director, National Institutes of Health, and by Grant# RSGT-09-263-01-CCE from the 920 American Cancer Society. 921 CONSIT TEAM 922 The members CONSIT TEAM were funded by grants from the Italian Association for Cancer 923 Research (AIRC) to GG, PP and PR; Italian Ministry of Education, Universities and Research to 924 GG; FiorGen Foundation for Pharmacogenomics to MG; Fondazione Internazionale di Ricerca 925 in Medicina Sperimentale (FIRMS) and Carla Ratti's project on breast cancer genetics to BP; 926 and by funds from Italian citizens who allocated the 5x1000 share of their tax payment in 927 support of the Fondazione IRCCS Istituto Nazionale Tumori, according to Italian laws (INT-928 Institutional strategic projects ‘5x1000’) to PP and SM. 929 CORE 930 The CIMBA data management and data analysis were supported by Cancer Research – UK 931 grants C12292/A11174 and C1287/A10118.SH is supported by an NHMRC Program Grant to 932 GCT. ACA is a Cancer Research -UK Senior Cancer Research Fellow. GCT and ABS are 933 NHMRC Senior Research Fellows. 934 DEMOKRITOS 935 This research has been co-financed by the European Union (European Social Fund – ESF) and 936 Greek national funds through the Operational Program "Education and Lifelong Learning" of the 937 National Strategic Reference Framework (NSRF) - Research Funding Program of the General 938 Secretariat for Research & Technology: ARISTEIA-39. Investing in knowledge society through 939 the European Social Fund. 940 DKFZ 941 The DKFZ study was supported by the DKFZ, Heidelberg, Germany, the Shaukat Khanum 942 Memorial Cancer Hospital and Research Centre, Lahore, Pakistan and the Pontificia 943 Universidad Javeriana, Bogota, Colombia. 944 EMBRACE 945 EMBRACE is supported by Cancer Research UK Grants C1287/A10118 and C1287/A11990. D. 946 Gareth Evans and Fiona Lalloo are supported by an NIHR grant to the Biomedical Research 947 Centre, Manchester. The Investigators at The Institute of Cancer Research and The Royal 948 Marsden NHS Foundation Trust are supported by an NIHR grant to the Biomedical Research 949 Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. 950 Ros Eeles and Elizabeth Bancroft are supported by Cancer Research UK Grant C5047/A8385. 951 FCCC 952 The authors acknowledge support from the Fox Chase Cancer Center and The University of 953 Kansas Cancer Center and the Kansas Bioscience Authority Eminent Scholar Program. A.K.G. 954 was funded by 5U01CA113916, R01CA140323, P30 CA168524 and by the Chancellors 955 Distinguished Chair in Biomedical Sciences Professorship. M.B.D. and E.A.R. were funded by 956 P50 CA083638, P30 CA06920 and 3U01 CA69631. 957 GC-HBOC 958 The German Consortium of Hereditary Breast and Ovarian Cancer (GC-HBOC) is supported by 959 the German Cancer Aid (grant no 109076, Rita K. Schmutzler) and by the Center for Molecular 960 Medicine Cologne (CMMC). This study was kindly supported by the German Cancer Aid to R. K. 961 Schmutzler (grant no 109076) and by the Center for Molecular Medicine Cologne (CMMC). 962 GEMO 963
36
The study was supported by the Ligue National Contre le Cancer; the Association “Le cancer du 964 sein, parlons-en!” Award; and the Canadian Institutes of Health Research for the "CIHR Team in 965 Familial Risks of Breast Cancer" program. 966 Georgetown 967 The study was supported by the Fisher Center for Familial Cancer Research, the Familial 968 Cancer Registry at Georgetown University (NIH/NCI grant P30-CA051008), and Swing Fore the 969 Cure. 970 GOG 971 This study was supported by National Cancer Institute grants to the Gynecologic Oncology 972 Group (GOG) Administrative Office and Tissue Bank (CA 27469), the GOG Statistical and Data 973 Center (CA 37517), and GOG's Cancer Prevention and Control Committee (CA 101165). 974 HCSC 975 This research was supported by Spanish Ministry of Economy and Competitivity, grants 976 PI12/oo539 and RD12/0036/0006 (ISCIII). 977 HEBCS 978 The HEBCS was financially supported by the Helsinki University Central Hospital Research 979 Fund, the Sigrid Juselius Foundation, the Finnish Cancer Society, and the Academy of Finland 980 (132473). 981 HEBON 982 The HEBON study is supported by the Dutch Cancer Society grants NKI1998-1854, NKI2004-983 3088, NKI2007-3756, the Netherlands Organization of Scientific Research grant NWO 984 91109024, the Pink Ribbon grant 110005 and the BBMRI grant NWO 184.021.007/CP46. 985 HRBCP 986 HRBCP is supported by The Hong Kong Hereditary Breast Cancer Family Registry and the Dr. 987 Ellen Li Charitable Foundation, Hong Kong. 988 HUNBOCS 989 Hungarian Breast and Ovarian Cancer Study was supported by Hungarian Research Grant 990 KTIA-OTKA CK-80745 and the Norwegian EEA Financial Mechanism HU0115/NA/2008-3/ÖP-991 9. 992 ICO 993 Contract grant sponsor: Asociación Española Contra el Cáncer, Spanish Health Research 994 Fund; Carlos III Health Institute; Catalan Health Institute and Autonomous Government of 995 Catalonia. Contract grant numbers: ISCIIIRETIC RD06/0020/1051, PI10/01422, PI10/00748 and 996 2009SGR290. 997 IHCC 998 Katarzyna Jaworska is a fellow of International PhD program, Postgraduate School of Molecular 999 Medicine, Warsaw Medical University, supported by the Polish Foundation of Science. 1000 ILUH 1001 The ILUH group was supported by the Icelandic Association “Walking for Breast Cancer 1002 Research” and by the Landspitali University Hospital Research Fund. 1003 INHERIT 1004 This work was supported by the Canadian Institutes of Health Research for the “CIHR Team in 1005 Familial Risks of Breast Cancer” program, the Canadian Breast Cancer Research Alliance-grant 1006 #019511 and the Ministry of Economic Development, Innovation and Export Trade – grant # 1007 PSR-SIIRI-701. J.S. is Chairholder of the Canada Research Chair in Oncogenetics. 1008 IOVHBOCS 1009 The study was supported by Ministero dell'Istruzione, dell'Università e della Ricerca and 1010 Ministero della Salute. 1011 kConFab 1012 kConFab is supported by grants from the National Breast Cancer Foundation, the National 1013 Health and Medical Research Council (NHMRC) and by the Queensland Cancer Fund, the 1014
37
Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer 1015 Foundation of Western Australia. The Clinical Follow Up Study has received funding from the 1016 NHMRC, the National Breast Cancer Foundation, Cancer Australia and the National Institute of 1017 Health) GCT and ABS is an NHMRC Senior Research Fellow. GCT and ABS are Fellows of the 1018 National Health and Medical Research Council. 1019 KOHBRA 1020 KOHBRA is supported by a grant from the National R&D Program for Cancer Control, Ministry 1021 for Health, Welfare and Family Affairs, Republic of Korea (1020350). 1022 MAYO 1023 MAYO is supported by NIH grants CA128978 and CA116167, an NCI Specialized Program of 1024 Research Excellence (SPORE) in Breast Cancer (CA116201), a U.S. Department of Defense 1025 Ovarian Cancer Idea award (W81XWH-10-1-0341) and a grant from the Breast Cancer 1026 Research Foundation. 1027 MCGILL 1028 This research was funded by the Jewish General Hospital Weekend to End Breast Cancer, 1029 Quebec Ministry of Economic Development, Innovation and Export Trade. 1030 MSKCC 1031 MSKCC was supported by the Sharon Levine Corzine Fund, Breast Cancer Research 1032 Foundation, Niehaus Clinical Cancer Genetics Initiative, Andrew Sabin Family Foundation and 1033 Lymphoma Foundation. 1034 NCI 1035 The research of Drs. MH Greene, and PL Mai was supported by the Intramural Research 1036 Program of the US National Cancer Institute, NIH, and by support services contracts NO2-CP-1037 11019-50 and N02-CP-65504 with Westat, Inc, Rockville, MD. 1038 NNPIO 1039 This work has been supported by the Russian Federation for Basic Research (grants 11-04-1040 00227, 12-04-00928 and 12-04-01490). 1041 OSUCCG 1042 OSUCCG is supported by the Ohio State University Comprehensive Cancer Center. 1043 SEABASS 1044 Ministry of Science, Technology and Innovation, Ministry of Higher Education 1045 (UM.C/HlR/MOHE/06) and Cancer Research Initiatives Foundation. 1046 The Malaysian Breast Cancer Genetic Study is funded by research grants from the Malaysian 1047 Ministry of Science, Technology and Innovation, Ministry of Higher Education 1048 (UM.C/HIR/MOHE/06) and charitable funding from Cancer Research Initiatives Foundation. 1049 SMC 1050 This project was partially funded through a grant by the Israel cancer association and the 1051 funding for the Israeli Inherited breast cancer consortium. 1052 SWE-BRCA 1053 SWE-BRCA collaborators are supported by the Swedish Cancer Society. 1054 UCHICAGO 1055 UCHICAGO is supported by NCI Specialized Program of Research Excellence (SPORE) in 1056 Breast Cancer (CA125183), R01 CA142996, 1U01CA161032 and by the Ralph and Marion Falk 1057 Medical Research Trust, the Entertainment Industry Fund National Women's Cancer Research 1058 Alliance and the Breast Cancer research Foundation. OIO is an ACS Clinical Research 1059 Professor. 1060 UCLA 1061 This research was funded by the Jonsson Comprehensive Cancer Center Foundation; Breast 1062 Cancer Research Foundation. 1063 UCSF 1064 UCSF Cancer Risk Program and Helen Diller Family Comprehensive Cancer Center. 1065
38
UPENN 1066 This research was funded by the National Institutes of Health (NIH) (R01-CA102776 and R01-1067 CA083855; Breast Cancer Research Foundation; Rooney Family Foundation; Susan G. Komen 1068 Foundation for the Cure, Macdonald Family Foundation and Basser Center for BRCA Research. 1069 UKFOCR 1070 UK and Gilda Radner Familial Ovarian Cancer Registries (UKGRFOCR)UKFOCR was 1071 supported by a project grant from CRUK to Paul Pharoah. 1072 VFCTG 1073 Victorian Cancer Agency, Cancer Australia, National Breast Cancer Foundation. 1074 WCP 1075 The Women's Cancer Program (WCP) at the Samuel Oschin Comprehensive Cancer Institute is 1076 funded by the American Cancer Society Early Detection Professorship (SIOP-06-258-01-1077 COUN). 1078 1079 Acknowledgements, by center: 1080 1081 BCFR (Australia) 1082 The BCFR – Australia would like to thank Maggie Angelakos, Judi Maskiell, Gillian Dite, and 1083 Helen Tsimiklis. 1084 BCFR (New York) 1085 We wish to thank members and participants in the New York site of the Breast Cancer Family 1086 Registry for their contributions to the study. 1087 BCFR (Ontario) 1088 We wish to thank members and participants in the New York site of the Breast Cancer Family 1089 Registry for their contributions to the study. 1090 BFBOCC 1091 BFBOCC-LT: we acknowledge Vilius Rudaitis and Laimonas Griškevičius. BFBOCC-LV: we 1092 acknowledge Drs Janis Eglitis, Anna Krilova and Aivars Stengrevics. 1093 BMBSA 1094 We wish to thank the families who contribute to the BMBSA study. 1095 BRICOH 1096 We wish to thank Yuan Chun Ding, Greg Wilhoite, and Marie Pinto for their work in participant 1097 enrollment and biospecimen and data management. 1098 CNIO 1099 We thank Alicia Barroso, Rosario Alonso and Guillermo Pita for their assistance. 1100 CONSIT TEAM 1101 We would like to thank Alessandra Viel and Lara della Puppa of the Centro di Riferimento 1102 Oncologico, IRCCS, Aviano (PN), Italy; Laura Papi of the University of Florence, Florence, Italy; 1103 Monica Barile of the Istituto Europeo di Oncologia, Milan, Italy; Liliana Varesco of the IRCCS 1104 AOU San Martino - IST Istituto Nazionale per la Ricerca sul Cancro, Genoa, Italy; Stefania 1105 Tommasi, Brunella Pilato and Rossana Lambo of the Istituto Nazionale Tumori "Giovanni Paolo 1106 II" - Bari, Italy; Aline Martayan of the Istituto Nazionale Tumori Regina Elena, Rome, Italy ; 1107 Maria Grazia Tibiletti of the Ospedale di Circolo-Università dell'Insubria, Varese, Italy; and the 1108 personnel of the Cogentech Cancer Genetic Test Laboratory, Milan, Italy. 1109 DKFZ 1110 We are grateful to all the patients for their participation. We thank the physicians and other 1111 hospital staff, scientists, research assistants and study stuff who contributed to the patient 1112 recruitment, data collection, sample preparation and molecular analyses. 1113 EMBRACE 1114 Epidemiological study of BRCA1 & BRCA2 mutation carriers (EMBRACE): Douglas F. Easton 1115 is the PI of the study. EMBRACE Collaborating Centres are: Coordinating Centre, Cambridge: 1116
39
Debra Frost, Steve Ellis, Elena Fineberg, Radka Platte. North of Scotland Regional Genetics 1117 Service, Aberdeen: Zosia Miedzybrodzka, Helen Gregory. Northern Ireland Regional Genetics 1118 Service, Belfast: Patrick Morrison, Lisa Jeffers. West Midlands Regional Clinical Genetics 1119 Service, Birmingham: Trevor Cole, Jonathan Hoffman. South West Regional Genetics Service, 1120 Bristol: Alan Donaldson, Margaret James. East Anglian Regional Genetics Service, Cambridge: 1121 Marc Tischkowitz, Joan Paterson, Sarah Downing, Amy Taylor. Medical Genetics Services for 1122 Wales, Cardiff: Alexandra Murray, Mark T. Rogers, Emma McCann. St James’s Hospital, Dublin 1123 & National Centre for Medical Genetics, Dublin: M. John Kennedy, David Barton. South East of 1124 Scotland Regional Genetics Service, Edinburgh: Mary Porteous, Sarah Drummond. Peninsula 1125 Clinical Genetics Service, Exeter: Carole Brewer, Emma Kivuva, Anne Searle, Selina Goodman, 1126 Kathryn Hill. West of Scotland Regional Genetics Service, Glasgow: Rosemarie Davidson, 1127 Victoria Murday, Nicola Bradshaw, Lesley Snadden, Mark Longmuir, Catherine Watt, Sarah 1128 Gibson, Eshika Haque, Ed Tobias, Alexis Duncan. South East Thames Regional Genetics 1129 Service, Guy’s Hospital London: Louise Izatt, Chris Jacobs, Caroline Langman. North West 1130 Thames Regional Genetics Service, Harrow: Huw Dorkins. Leicestershire Clinical Genetics 1131 Service, Leicester: Julian Barwell. Yorkshire Regional Genetics Service, Leeds: Julian Adlard, 1132 Gemma Serra-Feliu. Cheshire & Merseyside Clinical Genetics Service, Liverpool: Ian Ellis, 1133 Catherine Houghton. Manchester Regional Genetics Service, Manchester: D Gareth Evans, 1134 Fiona Lalloo, Jane Taylor. North East Thames Regional Genetics Service, NE Thames, London: 1135 Lucy Side, Alison Male, Cheryl Berlin. Nottingham Centre for Medical Genetics, Nottingham: 1136 Jacqueline Eason, Rebecca Collier. Northern Clinical Genetics Service, Newcastle: Fiona 1137 Douglas, Oonagh Claber, Irene Jobson. Oxford Regional Genetics Service, Oxford: Lisa 1138 Walker, Diane McLeod, Dorothy Halliday, Sarah Durell, Barbara Stayner. The Institute of 1139 Cancer Research and Royal Marsden NHS Foundation Trust: Ros Eeles, Susan Shanley, 1140 Nazneen Rahman, Richard Houlston, Elizabeth Bancroft, Elizabeth Page, Audrey Ardern-1141 Jones, Kelly Kohut, Jennifer Wiggins, Elena Castro, Anita Mitra. North Trent Clinical Genetics 1142 Service, Sheffield: Jackie Cook, Oliver Quarrell, Cathryn Bardsley. South West Thames 1143 Regional Genetics Service, London: Shirley Hodgson, Sheila Goff, Glen Brice, Lizzie 1144 Winchester, Charlotte Eddy, Vishakha Tripathi, Virginia Attard. Wessex Clinical Genetics 1145 Service, Princess Anne Hospital, Southampton: Diana Eccles, Anneke Lucassen, Gillian 1146 Crawford, Donna McBride, Sarah Smalley. 1147 FCCC 1148 We thank Ms. JoEllen Weaver and Dr. Betsy Bove for their technical support. 1149 GC-HBOC 1150 We are very thankful to all family members who participated in this study, Dieter Schäfer, Center 1151 Frankfurt, for providing DNA samples and Juliane Köhler for excellent technical assistance. 1152 GEMO 1153 Genetic Modifiers of Cancer Risk in BRCA1/2 Mutation Carriers (GEMO) study : National 1154 Cancer Genetics Network «UNICANCER Genetic Group», France. We wish to thank all the 1155 GEMO collaborating groups for their contribution to this study. GEMO Collaborating Centers 1156 are: Coordinating Centres, Unité Mixte de Génétique Constitutionnelle des Cancers Fréquents, 1157 Hospices Civils de Lyon - Centre Léon Bérard, & Equipe «Génétique du cancer du sein», 1158 Centre de Recherche en Cancérologie de Lyon: Olga Sinilnikova, Sylvie Mazoyer, Francesca 1159 Damiola, Laure Barjhoux, Carole Verny-Pierre, Sophie Giraud, Mélanie Léone; and Service de 1160 Génétique Oncologique, Institut Curie, Paris: Dominique Stoppa-Lyonnet, Marion Gauthier-1161 Villars, Bruno Buecher, Claude Houdayer, Virginie Moncoutier, Muriel Belotti, Carole Tirapo, 1162 Antoine de Pauw. Institut Gustave Roussy, Villejuif: Brigitte Bressac-de-Paillerets, Olivier Caron. 1163 Centre Jean Perrin, Clermont–Ferrand: Yves-Jean Bignon, Nancy Uhrhammer. Centre Léon 1164 Bérard, Lyon: Christine Lasset, Valérie Bonadona, Sandrine Handallou. Centre François 1165 Baclesse, Caen: Agnès Hardouin, Pascaline Berthet. Institut Paoli Calmettes, Marseille: Hagay 1166 Sobol, Violaine Bourdon, Tetsuro Noguchi, Audrey Remenieras, François Eisinger. CHU 1167
40
Arnaud-de-Villeneuve, Montpellier: Isabelle Coupier, Pascal Pujol. Centre Oscar Lambret, Lille: 1168 Jean-Philippe Peyrat, Joëlle Fournier, Françoise Révillion, Philippe Vennin, Claude Adenis. 1169 Hôpital René Huguenin/Institut Curie, St Cloud: Etienne Rouleau, Rosette Lidereau, Liliane 1170 Demange, Catherine Nogues. Centre Paul Strauss, Strasbourg: Danièle Muller, Jean-Pierre 1171 Fricker. Institut Bergonié, Bordeaux: Emmanuelle Barouk-Simonet, Françoise Bonnet, Virginie 1172 Bubien, Nicolas Sevenet, Michel Longy. Institut Claudius Regaud, Toulouse: Christine Toulas, 1173 Rosine Guimbaud, Laurence Gladieff, Viviane Feillel. CHU Grenoble: Dominique Leroux, 1174 Hélène Dreyfus, Christine Rebischung, Magalie Peysselon. CHU Dijon: Fanny Coron, Laurence 1175 Faivre. CHU St-Etienne: Fabienne Prieur, Marine Lebrun, Caroline Kientz. Hôtel Dieu Centre 1176 Hospitalier, Chambéry: Sandra Fert Ferrer. Centre Antoine Lacassagne, Nice: Marc Frénay. 1177 CHU Limoges: Laurence Vénat-Bouvet. CHU Nantes: Capucine Delnatte. CHU Bretonneau, 1178 Tours: Isabelle Mortemousque. Groupe Hospitalier Pitié-Salpétrière, Paris: Florence Coulet, 1179 Chrystelle Colas, Florent Soubrier. CHU Vandoeuvre-les-Nancy : Johanna Sokolowska, Myriam 1180 Bronner. Creighton University, Omaha, USA: Henry T.Lynch, Carrie L.Snyder. 1181 G-FAST 1182 We acknowledge the contribution of Bruce Poppe and Anne De Paepe. We wish to thank the 1183 technical support of Ilse Coene and Brecht Crombez. 1184 HCSC 1185 We acknowledge Pedro Perz Segura for his clinical assistance. 1186 HEBCS 1187 HEBCS would like to thank Drs. Kristiina Aittomäki, Carl Blomqvist and Kirsimari Aaltonen and 1188 Taru A. Muranen and RN Irja Erkkilä for their help with the HEBCS data and samples. 1189 HEBON 1190 The Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON) consists of 1191 the following Collaborating Centers: Coordinating center: Netherlands Cancer Institute, 1192 Amsterdam, NL: M.A. Rookus, F.B.L. Hogervorst, F.E. van Leeuwen, S. Verhoef, M.K. Schmidt, 1193 J.L. de Lange; Erasmus Medical Center, Rotterdam, NL: J.M. Collée, A.M.W. van den 1194 Ouweland, M.J. Hooning, C. Seynaeve, C.H.M. van Deurzen, I.M. Obdeijn; Leiden University 1195 Medical Center, NL: C.J. van Asperen, J.T. Wijnen, R.A.E.M. Tollenaar, P. Devilee, T.C.T.E.F. 1196 van Cronenburg; Radboud University Nijmegen Medical Center, NL: C.M. Kets, A.R. 1197 Mensenkamp; University Medical Center Utrecht, NL: M.G.E.M. Ausems, R.B. van der Luijt; 1198 Amsterdam Medical Center, NL: C.M. Aalfs, T.A.M. van Os; VU University Medical Center, 1199 Amsterdam, NL: J.J.P. Gille, Q. Waisfisz, H.E.J. Meijers-Heijboer; University Hospital 1200 Maastricht, NL: E.B. Gómez-Garcia, M.J. Blok; University Medical Center Groningen, NL: J.C. 1201 Oosterwijk, A.H. van der Hout, M.J. Mourits, G.H. de Bock. The Netherlands Foundation for the 1202 detection of hereditary tumours, Leiden, NL: H.F. Vasen. 1203 HRBCP 1204 We wish to thank Hong Kong Sanatoriuma and Hospital for their continual support. 1205 HUNBOCS 1206 We wish to thank to Hungarian Breast and Ovarian Cancer Study Group members (Janos Papp, 1207 Aniko Bozsik, Kristof Arvai, Judit Franko, Maria Balogh, Gabriella Varga, Judit Ferenczi, 1208 Department of Molecular Genetics, National Institute of Oncology, Budapest, Hungary) and the 1209 clinicians and patients for their contributions to this study. 1210 IOC 1211 We wish to thank the ICO Hereditary Cancer Program team led by Dr. Gabriel Capella. 1212 INHERIT 1213 We would like to thank Dr Martine Dumont, Martine Tranchant for sample management and 1214 skillful technical assistance. 1215 IPOBCS 1216 We would like to thank Dr. Patrícia Rocha and Dr. Catarina Santos for their contribution for 1217 BRCA1/BRCA2 genetic testing in IPOBCS. 1218
41
KCONFAB 1219 We wish to thank Heather Thorne, Eveline Niedermayr, all the kConFab research nurses and 1220 staff, the heads and staff of the Family Cancer Clinics, and the many families who contribute to 1221 kConFab. 1222 MOD SQUAD 1223 The Czech Republic investigators were supported by MH CZ-DRO (MMCI, 00209805), the 1224 European Regional Development Fund, and the State Buget of the Czech Republic (RECAMO, 1225 CZ1.05/2.1.00/03.0101. 1226 OSU CCG 1227 Kevin Sweet, Caroline Craven and Michelle O'Conor were instrumental in accrual of study 1228 participants, ascertainment of medical records and database management. Samples were 1229 processed by the OSU Human Genetics Sample Bank. 1230 SEABASS 1231 We would like to thank Yip Cheng Har, Nur Aishah Mohd Taib, Phuah Sze Yee, Norhashimah 1232 Hassan and all the research nurses, research assistants and doctors involved in the MyBrCa 1233 Study for assistance in patient recruitment, data collection and sample preparation. In addition, 1234 we thank Philip Iau, Sng Jen-Hwei and Sharifah Nor Akmal for contributing samples from the 1235 Singapore Breast Cancer Study and the HUKM-HKL Study respectively. 1236 SMC 1237 SMC team wishes to acknowledge the assistance of the Meirav Comprehensive breast cancer 1238 center team at the Sheba Medical Center for assistance in this study. 1239 SWE-BRCA 1240 Swedish scientists participating as SWE-BRCA collaborators are: from Lund University and 1241 University Hospital: Åke Borg, Håkan Olsson, Helena Jernström, Karin Henriksson, Katja 1242 Harbst, Maria Soller, Niklas Loman, Ulf Kristoffersson; from Gothenburg Sahlgrenska University 1243 Hospital: Anna Öfverholm, Margareta Nordling, Per Karlsson, Zakaria Einbeigi; from Stockholm 1244 and Karolinska University Hospital: Anna von Wachenfeldt, Annelie Liljegren, Annika Lindblom, 1245 Brita Arver, Gisela Barbany Bustinza, Johanna Rantala; from Umeå University Hospital: 1246 Beatrice Melin, Christina Edwinsdotter Ardnor, Monica Emanuelsson; from Uppsala University: 1247 Hans Ehrencrona, Maritta Hellström Pigg, Richard Rosenquist; from Linköping University 1248 Hospital: Marie Stenmark-Askmalm, Sigrun Liedgren. 1249 UCHICAGO 1250 We wish to thank Cecilia Zvocec, Qun Niu, physicians, genetic counselors, research nurses and 1251 staff of the Cancer Risk Clinic for their contributions to this resource, and the many families who 1252 contribute to our program. 1253 UCLA 1254 We thank Lorna Kwan, MPH for assembling the data for this study. 1255 UCSF 1256 We would like to thank Dr. Robert Nussbaum and the following genetic counselors for 1257 participant recruitment: Beth Crawford, Kate Loranger, Julie Mak, Nicola Stewart, Robin Lee, 1258 Amie Blanco and Peggy Conrad. And thanks to Ms. Salina Chan for her data management. 1259 UKFOCR 1260 We thank Paul Pharoah, Susan Ramus, Carole Pye, Patricia Harrington and Eva Wozniak for 1261 their contributions towards the UKFOCR. We acknowledge the Roswell Park Alliance 1262 Foundation for their continued support of the Gilda Radner Ovarian Family Cancer Registry. 1263 GRFOCR would like to acknowledge Kirsten Moysich and Lara Sucheston (Department of 1264 Cancer Prevention and Control). 1265 UPENN 1266 We would like acknowledge our genetic counselors,Jessica Long, Jacquelyn Powers and Jill 1267 Stopfer for participant recruitment, our laboratory and database managers, Kurt D’Andrea, and 1268
42
Jessica Tigges-Cardwell for their contributions to this work, as well as the rest of the staff of the 1269 McDonald Cancer Risk Evaluation Program and the Basser Center for BRCA. 1270 VFCTG 1271 Paul James, Geoffrey Lindeman, Marion Harris, Martin Delatycki of the Victorian Familial 1272 Cancer Trials Group. We thank Sarah Sawyer and Rebecca Driessen for assembling this data. 1273
43
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3. Gayther SA, Warren W, Mazoyer S, et al. Germline mutations of the BRCA1 gene in 1281 breast and ovarian cancer families provide evidence for a genotype-phenotype 1282 correlation. Nature Genetics. 1995;11(4):428-433. 1283
4. Thompson D, Easton D. Variation in BRCA1 cancer risks by mutation position. Cancer 1284 Epidemiol Biomarkers Prev. 2002;11(4):329-336. 1285
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6. Perrin-Vidoz L, Sinilnikova OM, Stoppa-Lyonnet D, Lenoir GM, Mazoyer S. The 1289 nonsense-mediated mRNA decay pathway triggers degradation of most BRCA1 mRNAs 1290 bearing premature termination codons. Human Molecular Genetics. 2002;11(23):2805-1291 2814. 1292
7. Ware MD, DeSilva D, Sinilnikova OM, Stoppa-Lyonnet D, Tavtigian SV, Mazoyer S. 1293 Does nonsense-mediated mRNA decay explain the ovarian cancer cluster region of the 1294 BRCA2 gene? Oncogene. 2006;25(2):323-328. 1295
8. Dine J, Deng CX. Mouse models of BRCA1 and their application to breast cancer 1296 research. Cancer Metastasis Rev. 2013;32(1-2):25-37. 1297
9. Evers B, Jonkers J. Mouse models of BRCA1 and BRCA2 deficiency: past lessons, 1298 current understanding and future prospects. Oncogene. 2006;25(43):5885-5897. 1299
10. Wu LC, Wang ZW, Tsan JT, et al. Identification of a RING protein that can interact in 1300 vivo with the BRCA1 gene product. Nature Genetics. 1996;14(4):430-440. 1301
11. Li ML, Greenberg RA. Links between genome integrity and BRCA1 tumor suppression. 1302 Trends Biochem Sci. 2012;37(10):418-424. 1303
12. Shamoo Y. Structural insights into BRCA2 function. Current Opinion in Structural 1304 Biology. 2003;13(2):206-211. 1305
13. Rebbeck TR, Mitra N, Domchek SM, et al. Modification of ovarian cancer risk by 1306 BRCA1/2-interacting genes in a multicenter cohort of BRCA1/2 mutation carriers. 1307 Cancer Res. 2009;69(14):5801-5810. 1308
14. Rebbeck TR, Mitra N, Domchek SM, et al. Modification of BRCA1-Associated Breast 1309 and Ovarian Cancer Risk by BRCA1-Interacting Genes. Cancer Res. 2011;71(17):5792-1310 5805. 1311
15. Antoniou AC, Sinilnikova OM, Simard J, et al. RAD51 135G-->C modifies breast cancer 1312 risk among BRCA2 mutation carriers: results from a combined analysis of 19 studies. 1313 Am J Hum Genet. 2007;81(6):1186-1200. 1314
16. Chenevix-Trench G, Milne RL, Antoniou AC, Couch FJ, Easton DF, Goldgar DE. An 1315 international initiative to identify genetic modifiers of cancer risk in BRCA1 and BRCA2 1316 mutation carriers: the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 1317 (CIMBA). Breast Cancer Res. 2007;9(2):104. 1318
17. Claes K, Poppe B, Machackova E, et al. Differentiating pathogenic mutations from 1319 polymorphic alterations in the splice sites of BRCA1 and BRCA2. Genes, Chromosomes 1320 & Cancer. 2003;37(3):314-320. 1321
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18. Goldgar DE, Easton DF, Deffenbaugh AM, Monteiro AN, Tavtigian SV, Couch FJ. 1322 Integrated evaluation of DNA sequence variants of unknown clinical significance: 1323 application to BRCA1 and BRCA2. Am J Hum Genet. 2004;75(4):535-544. 1324
19. Chenevix-Trench G, Healey S, Lakhani S, et al. Genetic and histopathologic evaluation 1325 of BRCA1 and BRCA2 DNA sequence variants of unknown clinical significance. Cancer 1326 Res. 2006;66(4):2019-2027. 1327
20. Palacios IM. Nonsense-mediated mRNA decay: from mechanistic insights to impacts on 1328 human health. Brief Funct Genomics. 2013;12(1):25-36. 1329
21. Buisson M, Anczukow O, Zetoune AB, Ware MD, Mazoyer S. The 185delAG mutation 1330 (c.68_69delAG) in the BRCA1 gene triggers translation reinitiation at a downstream 1331 AUG codon. Hum Mutat. 2006;27(10):1024-1029. 1332
22. Lin DY, Wei LJ. The robust inference for the Cox proportional hazards model. JASA. 1333 1989;84:1074-1078. 1334
23. Therneau T, Grambsch P. Modeling Survival Data: Extending the Cox Model. New York: 1335 Springer Verlag; 2000:169-229. 1336
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25. Chen S, Parmigiani G. Meta-analysis of BRCA1 and BRCA2 penetrance. J Clin Oncol. 1340 2007;25(11):1329-1333. 1341
26. Benjamini Y, Hochberg Y. Controlling the false discovery rate: A practical and powerful 1342 approach to multiple testing. . J R Stat Soc B. 1995;57:289-300. 1343
27. Chen X, Truong TT, Weaver J, et al. Intronic alterations in BRCA1 and BRCA2: effect on 1344 mRNA splicing fidelity and expression. Hum Mutat. 2006;27(5):427-435. 1345
28. Chen X, Weaver J, Bove BA, et al. Allelic imbalance in BRCA1 and BRCA2 gene 1346 expression is associated with an increased breast cancer risk. Hum Mol Genet. 1347 2008;17(9):1336-1348. 1348
29. Bhuvanagiri M, Schlitter AM, Hentze MW, Kulozik AE. NMD: RNA biology meets human 1349 genetic medicine. Biochem J. 2010;430(3):365-377. 1350
30. Silva AL, Romao L. The mammalian nonsense-mediated mRNA decay pathway: to 1351 decay or not to decay! Which players make the decision? FEBS Lett. 2009;583(3):499-1352 505. 1353
31. Ludwig T, Fisher P, Ganesan S, Efstratiadis A. Tumorigenesis in mice carrying a 1354 truncating BRCA1 mutation. Genes & Development. 2001;15(10):1188-1193. 1355
32. Thompson D, Easton D, Breast Cancer Linkage C. Variation in cancer risks, by mutation 1356 position, in BRCA2 mutation carriers. American Journal of Human Genetics. 1357 2001;68(2):410-419. 1358
33. Lubinski J, Phelan CM, Ghadirian P, et al. Cancer variation associated with the position 1359 of the mutation in the BRCA2 gene. Fam Cancer. 2004;3(1):1-10. 1360
34. Yang H, Jeffrey PD, Miller J, et al. BRCA2 function in DNA binding and recombination 1361 from a BRCA2-DSS1-ssDNA structure. Science. 2002;297(5588):1837-1848. 1362
35. Welch EM, Barton ER, Zhuo J, et al. PTC124 targets genetic disorders caused by 1363 nonsense mutations. Nature. 2007;447(7140):87-91. 1364
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1368 1369
45
Figure Legends Figure 1: Analysis Workflow: This figure represents the analyses that were undertaken in the order in which they are presented in the text.
Figure 2: Hazard Ratio of Breast Cancer Relative to the Hazard Ratio of Ovarian Cancer by BRCA1 Nucleotide Position (Supplementary Table 2).
Black lines denote the magnitude of the ratio of hazard ratios that are significantly different from a ratio of 1.0; Grey lines denote ratios of hazard
ratios that are not significantly different than a value of 1.0. These black and grey lines represent the bins defined across the span of the BRCA1
gene and their vertical position represents the size of effect of the ratio of hazard ratio (R). The dotted lines indicate the regions inferred to be
ovarian cancer cluster region (OCCR) or breast cancer cluster region (BCCR). The dashed line indicates the hazard ratio effect of the functional
domains highlighted in grey. Proteins that physically interact with putative functional domains (i.e., binding partners) are shown in ovals. These
domains (and their putative or known binding partners) include the RING domain that interacts with BARD1; a region 3’ of the RING domain that
interacts with BRCC36; a region in exon 11 that interacts with CHEK2; the coiled coil domain that interacts with PALB2, ATM, and CTiP; and the
BRCT domain that interacts with BACH1 and CHK2.
Figure 3: Hazard Ratio of Breast Cancer Relative to the Hazard Ratio of Ovarian Cancer by BRCA2 Nucleotide Position (Supplementary Table 3).
Black lines denote the magnitude of the ratio of hazard ratios that are significantly different from a ratio of 1.0; Grey lines denote ratios of hazard
ratios that are not significantly different than a value of 1.0. These black and grey lines represent the bins defined across the span of the BRCA2
gene. and their vertical position represents the size of effect of the ratio of hazard ratio (R). The dotted lines indicate the regions inferred to be
ovarian cancer cluster region (OCCR) or breast cancer cluster region (BCCR). The dashed line indicates the hazard ratio effect of the functional
domains highlighted in grey. Proteins that physically interact with putative functional domains (i.e., binding partners) are shown in ovals. Domains
include and a region in the 5’ region that interacts with PALB2; the BRC domain that interacts with RAD51; the OB folds domain that also interacts
with RAD51; and the Tower domain that interacts with ssDNA.
46
Table 1: Characteristics of Study Sample: Ascertainment, Diagnosis, Demographics, and Risk Factors
BRCA1 BRCA2
Variable N Median Range
(Standard Deviation)
N Median Range
(Standard Deviation)
Women with Breast Cancer 10,093 6,452
Year of Breast Cancer Diagnosis 1999 1942-2011 1999 1937-2011 Mean Age of Breast Cancer Diagnosis (years) 39.9 (9.2) 42.8 (9.8)
Women without Breast Cancer 9,488 5,488 Mean Age of Women with No Breast Cancer Diagnosis (years) 41.0 (12.0) 42.6 (13.1)
Women with Ovarian Cancer 3,358 954
Year of Ovarian Cancer Diagnosis 2001 1949-2011 2001 1967-2010 Mean Age of Ovarian Cancer Diagnosis (years) 50.0 (9.5) 54.5 (9.9)
Women without Ovarian Cancer 16,223 10,946 Mean Age of Women with No Ovarian Cancer Diagnosis (years) 42.0 (12.0) 45.4 (12.6)
Demographic and Risk Factors
Ethnicity
Caucasian 16,481 10,014
African/African American 176 87
Asian 392 404
Hispanic 333 175
Jewish 1,800 971
Other 399 249
Parity 2.0 0-14 (1.4) 2.0 0-14 (1.4)
Age at Menarche 13.0 8-23 (1.5) 13.0 7-22 (1.6)
Age at Natural or Surgical Menopause 44.0 16-68 (6.3) 46.0 14-68 (6.6)
47
Table 2: Mutation-Specific Risk Groups: Risks Relative to Non-Insertion/deletion Exon 11 Mutations, BRCA1 (N=19,581)
HR (95%CI) [N] Mean Age at Diagnosis (FDR p-value)
Group Description Mutation
Types Included
Function/ Effect NMD Protein Coding
Region
N with
Muta-tion
% Breast Cancer
Ovarian Cancer
Breast Cancer With Without
Mutation Mutation
Ovarian Cancer With Without
Mutation Mutation
a Exon 11
Nonsense Mutations
NS Yes No 1770 9.0 [ref] [796]
[ref] [336]
40.4 42.4 (<0.001)
50.2 52.5 (<0.001)
1 Nonsense Mediated
Decay
FS, NS, OF-GR, OF-SP Yes No 11027 56.3
1.20 (1.08-1.33)
[5469]
0.94 (0.80-1.11)
[2038]
41.2 40.1 (<0.001)
50.8 50.3 (0.317)
2 All premature termination mutations
FS, NS, OF-GR, OF-SP
premature termination
codon Yes No 14453 73.8
1.25 (1.12-1.38)
[7318]
0.93 (0.79-1.09)
[2524]
41.2 40.4 (0.001)
51.2 50.2 (0.057)
3
Mutations before c.297
ATG presumed transcription re-
initiation
FS, NS Re-initiation No No < c.297 2763 14.1
1.40 (1.12-1.74)
[250]
0.66 (0.46-0.95)
[74]
40.7 39.4 (0.067)
50.5 52.2 (0.294)
4 Not premature termination
MS, IF, GR, IF-SP, FS No Yes 5398 27.6%
1.51 (1.34-1.70)
[2986]
0.73 (0.61-0.88)
[781]
40.5 41.1 (0.006)
50.6 50.0 (0.317)
5 All Founder Mutations FS 5375 27.5%
1.41 [1.23-1.61]
(2698)
0.72 [0.60-0.88]
(850)
40.2 41.1 (<0.001)
50.27 51.11
(0.0325)
5a Founder Mutation
c.68_69delAG FS No 2324 11.9%
1.14
[0.94-1.38] (1033)
0.67 [0.51-0.87]
(391)
40.43 42.41 (<0.001)
50.22 52.49 (<0.001)
5b Founder Mutation
c.5266dupC FS Yes 3051 15.6%
1.63 (1.41-1.89)
[1665]
0.73 (0.57-0.92)
[459]
40.5 41.5 (<0.001)
50.6 50.0 (0.342)
6 All missense mutations MS Yes 1620 8.3%
1.40 (1.20-1.64)
[899]
0.73 (0.57-0.92)
[241]
40.6 49.8 (0.600)
50.5 49.8 (0.589)
6a Missense
mutations in RING domain
MS Yes c.72-192 1213 6.2%
1.56 (1.32-1.84)
[681]
0.73 (0.56-0.96)
[171]
40.6 41.1 (0.396)
50.6 49.3 (0.317)
6b Missense
mutations in BRCT domain
MS Yes c.4866-5325 372 1.9%
1.09 (0.82-1.45)
[202]
0.72 (0.48-1.09)
[64]
40.7 40.2 (0.600)
50.5 51.2 (0.589)
48
HR (95%CI) [N] Mean Age at Diagnosis (FDR p-value)
Group Description Mutation
Types Included
Function/ Effect NMD Protein Coding
Region
N with
Muta-tion
% Breast Cancer
Ovarian Cancer
Breast Cancer With Without
Mutation Mutation
Ovarian Cancer With Without
Mutation Mutation
7
Missense Mutations and
in-frame deletions
MS+IF, IF-SP, IF-GR
Yes 1658 8.5% 1.42
(1.22-1.66) [925]
0.71 (0.56-0.91)
[249]
40.6 40.9 (0.600)
50.6 49.8 (0.342)
8
In-frame deletions
(splice, single codon, large
deletion)
IF, IF-SP, IF-GR IFD Yes 38 0.2%
2.41 (1.41-4.11)
[26]
0.51 (0.15-1.76)
[8]
40.6 41.8 (0.600)
50.5 48.4 (0.589)
9
All premature termination codons not
leading to NMD
FS, NS, OF-SP, OF-GR
premature termination
codon No Yes 3663 18.7%
1.58 (1.38-1.80)
[2000]
0.74 (0.60-0.91)
[520]
40.5 41.1 (0.015)
50.6 50.1 (0.336)
a Reference Group. NS: Nonsense; FS: Frame Shift; IF: In-frame; MS: Missense; SP: Splicing; GR: Genomic Rearrangement; OF: Out of Frame; NMD: Nonsense Mediated Decay
49
Table 3: Mutation-Specific Risk Groups: Risks Relative to Non-Insertion/deletion Exon 11 mutations, BRCA2 (N=11,900)
HR (95%CI) [N] Mean Age at Diagnosis (FDR p-value)
Group Description Mutation
Types Included
NMD Protein N with Mutation % Breast
Cancer Ovarian Cancer
Breast Cancer With Without
Mutation Mutation
Ovarian Cancer With Without
Mutation Mutation
a Exon 11
Nonsense Mutations
NS Yes No 1001 8.4 [ref] [534]
[ref] [155]
43.3 45.8 (<0.001)
56.5 56.9 (0.831)
1 Nonsense Mediated
Decay
FS, NS, OF-GR, OF-SP
Yes No 9961 83.7 1.10
(0.95 -1.27) [5383]
0.78 (0.56-1.08)
[803]
44.5 43.4 (0.008)
56.7 56.5 (0.934)
2 Not premature
termination codon
IF-S, IF-FS, NS No Yes 203 1.7
1.35 (0.92-1.97)
[118]
0.34 (0.13-0.88)
[12]
42.4 43.6 (0.423)
55.7 55.6 (0.936)
3
In-frame deletions (splice,
frameshift)
IF-FS, IF-S No Yes 117 1.0
1.41 (0.85-2.35)
[76]
0.26 (0.08-0.88)
[9]
42.4 43.6 (0.423)
56.3 56.5 (0.936)
4
Premature termination
codons in last exon not leading to
NMD
FS, NS No Yes 86 0.7 1.32
(0.79-2.19) [42]
0.51 (0.13-2.09)
[3]
42.4 43.6 (0.500)
53.0 56.5 (0.936)
5 Founder Mutation
c.5946delT 1341 11.3 0.79
[0.60-1.03] (579)
0.77 [0.46-1.32]
(155)
43.33 45.83 (<0.001)
56.47 56.88 (0.650)
a Reference Group NS: Nonsense; FS: Frame Shift; IF: In-frame; MS: Missense; SP: Splicing; GR: Genomic Rearrangement; OF: Out of Frame; NMD: Nonsense Mediated Decay. NE: Not estimable
50
Table 4: Risks Associated with Specific Binding Domains: Comparison of mutations not in the domain (i.e., the reference group) vs. those within the domain.
Breast Cancer Ovarian Cancer
Gene Domain Binding Partner Region N* HR (95%CI) FDR
P-value N* HR (95%CI)
FDR P-value
BRCA1 RING BARD1 c.72-192 781 / 595
1.13 (1.02-1.26)a,e 0.036 205 /
1171 0.81
(0.67-0.97) 0.073
Coiled Coil PALB2 c.3759-3819 or c.4191-4272 122 / 90
1.20 (0.93-1.54)f 0.157 39 /
173 0.97
(0.062-1.50) 0.879
BRCT BACH1 c.4926-5169 or c.5268-5526 1203 / 832
1.26 (1.15-1.38)b,g <0.001 298 /
1737 0.86
(0.74-1.01) 0.099
BRCA2 BRC RAD51
c.3006-3108, c.3636-3738, c.4263-4365, c.4551-4653, c.4992-5094, c.5511-5613,
c.5913-6015, or c.6153-6255
810 / 992
0.67 (0.56-0.79)c,h <0.001 205 /
1597 1.09
(0.78-1.53) 0.767
DNA Binding c.7437-8001 464 / 336
1.17 (0.99-1.38) 0.083 63 /
737 1.06
(0.71-1.59) 0.767
OB Folds ssDNA c.8010-8400 or c.9156-9570 512 / 364
1.18 (1.01-1.37)d,h 0.069 50 /
826 0.57
(0.39-0.84) 0.018
Tower
Domain RAD51 c.8443-8616 193 / 154
1.20 (0.92-1.56) 0.186 18 /
329 0.42
(0.18-1.00)i 0.103 * Denotes number of cancer cases with and without the mutation, from among 19,581 BRCA1 mutation carriers and 11,900 BRCA2 mutation
carriers. a MS Mutations only: HR=1.42, 95%CI: 1.06-1.90 b premature termination codon Mutations only: HR=1.31, 95%CI: 1.17-1.47 c premature termination codon Mutations only contributed to this estimate d premature termination codon Mutations only: HR=1.26, 95%CI: 1.07-1.48 e Mutations conferring NMD only: HR=2.56, 95%CI: 1.03-6.34 f Mutations conferring NMD only: HR=1.35, 95%CI: 1.05-1.72 g Mutations conferring NMD only: HR=1.38, 95%CI: 1.20-1.59 h Mutations conferring NMD only: HR=1.26, 95%CI: 1.07-1.48 i Mutations conferring NMD only: HR=0.31, 95%CI: 0.13-0.77
51
Table 5: Representative Cancer Penetrances by Age 70: Baseline Risk and Modified Risk in Mutation Group
Gene Cancer Site
Statistically Significant Mutation-Specific
Relative Risk
Mutation groups corresponding to
these relative risks, Tables 2-3 (Group Number)
Overall Penetrance to
Age 70 (Chen and Parmigiani25)
Mutation-Specific Penetrance to
Age 70
BRCA1 Breast 1.4 All MS (6), All Founder (5),
NMD/Re-Init (3) 57% 69%
Ovary 0.7 Not PTC (4), All Founder (5) 40% 33%
Ovary 0.5 IFD (8) 40% 20%
BRCA2 Breast 0.7
Truncating mutations within
the BRC Domains (Table 4)
49% 35%
Ovary 0.3 Not PTC (2) 18% 6%
Figure 1: Analysis Workflow
Female BRCA1 (N=19,581) and BRCA2 (N=11,900) Mutation Carriers (Table 1)
1) Analysis of Ovarian and Breast Cancer Cluster Regions: Risk Groups: Mutations in bins across the nucleotide span of each gene.
Reference Group: Mutations outside of that bin. (BRCA1: Figure 1 and Supplementary Table 2; BRCA2: Figure 2 and Supplementary Table 3)
2) Analysis of Mutation Type and Function: Risk Groups: Carriers of nonsense, frame shift, in-frame, missense,
premature termination codons, or nonsense mediated decay mutations. Reference group: Non-insertion/deletion exon 11 mutations
(BRCA1: Table 2; BRCA2: Table 3)
3) Analysis of Functional Domains: Risk Group: All types of mutations within the domain. Reference Group: Mutations outside of the domain.
Domains: BRCA1: RING, Coiled Coil, BRCT Domains
BRCA2: BRC, DNA Binding, OB Folds, Tower Domains (Table 4)
1
CHK2
BRCT (c.4926-5169, c.5268-5526)
1
Putative OCCR
8 7
1000
3
Putative BCCR1
4
5
14
15 16
17 18
20 21
22
23
24
26 28 29
30
25 19
13 c.68_69delAG
c.5266dupC
Original OCCR (c.2282-c.4071)
RING (c.72-192)
2
6
9
10
11 12
c.4017 c.179 c.505
Putative BCCR2
c.5261 c.5563
Rat
io o
f Haz
ard
Rat
ios
(Bre
ast C
ance
r : O
varia
n C
ance
r)
Coiled Coil (c.3759-3819, c.4191-4272)
200
0 30
00
4000
50
00
Figure 2.
BARD1 PALB2 BACH1
27
c.4062
Exon 11
c.2686 c.3254 c.1380 c.2475 c.1674 c.1893 c.4328 c.4945
CHK2 CtIP ATM BRCC36
Putative BCCR2’
bp
Upper and Lower 95%CI
1
1
2
3
5
6
8 9
10
11
12
13
14
15
16
17
7
4
18
19
Original OCCR (Narrow: c.3847-6275)
Original OCCR (Broad: c.2831-6401)
c.5946delT
Putative OCCR1
c.3249 c.5681
Putative BCCR2
c.7394 c.8904
Rat
io o
f Haz
ard
Rat
ios
(B
reas
t Can
cer :
Ova
rian
Can
cer)
BRC Domains (8 domains: c.3006-6255)
2000
4
000
6000
8000
1000
0
DNA Binding (c.7437-8001)
OB Folds (c.8010-8400, c.9156-9570)
Tower (c.8443-8616)
Figure 3.
Putative OCCR2
c.6645 c.7471
ssDNA
RAD51 RAD51
Exon 11
Putative BCCR1
c.1 c.596
Putative BCCR1'
c.772 c.1806 c.5946
PALB2
bp
Upper and Lower 95%CI
1
Supplementary Table 1: Study Sample: Numbers of Individuals with BRCA1 or BRCA2 Mutations by Center and Cancer Status
BRCA1 BRCA2
Center ID Study Name Country
Breast Cancer
Only
Ovarian Cancer
Only
Breast and
Ovarian Cancer
No Cancer
Total BRCA1
Breast Cancer
Only
Ovarian Cancer
Only
Breast and
Ovarian Cancer
No Cancer
Total BRCA2 TOTAL
BCFR Breast Cancer Family Registry
USA/Canada/ Australia
383 35 29 221 668 295 13 9 213 530 1,198
BFBOCC
Baltic Familial Breast Ovarian Cancer Consortium
Latvia/ Lithuania 87 91 18 52 248 7 2 0 1 10 258
BIDMC Beth Israel Deaconess Medical Center
USA 32 4 0 1 37 22 3 0 28 53 90
BMBSA
BRCA-gene mutations and breast cancer in South African women
South Africa 43 8 8 17 76 98 12 3 43 156 232
BRICOH Beckman Research Institute of the City of Hope
USA 80 28 7 140 255 53 9 4 90 156 411
CBCS Rigshospitalet Denmark 121 62 19 33 235 82 14 3 19 118 353
CNIO Spanish National Cancer Centre Spain 122 28 28 100 278 189 20 7 143 359 637
COH City of Hope Cancer Center USA 125 17 12 81 235 121 5 2 54 182 417
CONSIT TEAM
CONsorzio Studi ITaliani sui Tumori Ereditari Alla Mammella
Italy 372 165 86 258 881 348 33 28 160 569 1,450
DEMO-KRITOS
National Center for Scientific Research "Demokritos"
Greece 115 39 14 26 194 14 0 0 3 17 211
DFCI Dana Farber Cancer Institute USA 66 11 8 78 163 54 4 2 79 139 302
DKFZ German Cancer Research Center
Germany Pakistan/ Colombia
148 15 7 85 255 41 5 2 35 83 338
2
BRCA1 BRCA2
Center ID Study Name Country
Breast Cancer
Only
Ovarian Cancer
Only
Breast and
Ovarian Cancer
No Cancer
Total BRCA1
Breast Cancer
Only
Ovarian Cancer
Only
Breast and
Ovarian Cancer
No Cancer
Total BRCA2 TOTAL
DNA HEBON
Genen Omgeving studie van de werkgroep Hereditiair Borstkanker Onderzoek Nederland
Nether-lands 553 99 47 621 1,320 280 40 20 501 841 2,161
EMBRACE Epidemiological Study of Familial Breast Cancer
UK 529 90 64 539 1,222 445 55 21 520 1,041 2,263
FCCC Fox Chase Cancer Center USA 50 16 6 51 123 45 13 4 50 112 235
GC-HBOC German Familial Breast Group Germany 1,030 200 108 468 1,806 579 47 26 312 964 2,770
GEMO
Genetic Modifiers of cancer risk in BRCA1/2 mutation carriers
France/ USA 895 223 141 559 1,818 684 56 23 274 1,037 2,855
GEORGE-TOWN
Georgetown University USA 27 3 2 19 51 17 3 0 21 41 92
GOG Gynecologic Oncology Group USA 227 0 0 240 467 161 0 0 160 321 788
HCSC Hospital Clinico San Carlos Spain 66 21 12 78 177 77 9 3 74 163 340
HEBCS Helsinki Breast Cancer Study Finland 47 10 11 28 96 64 6 7 51 128 224
HRBCP
Study of Genetic Mutations in Breast and Ovarian Cancer patients in Hong Kong and Asia
Hong Kong 21 5 5 13 44 41 0 1 19 61 105
HUNBOCS
Molecular Genetic Studies of Breast- and Ovarian Cancer in Hungary
Hungary 105 23 6 54 188 36 5 0 21 62 250
HVH University Hospital Vall d'Hebron Spain 34 6 4 26 70 39 3 1 25 68 138
ICO Institut Català d'Oncologia Spain 81 27 11 72 191 118 16 9 91 234 425
IHCC International Hereditary Cancer Centre
Poland 638 143 28 673 1,482 14 8 1 12 35 1,517
3
BRCA1 BRCA2
Center ID Study Name Country
Breast Cancer
Only
Ovarian Cancer
Only
Breast and
Ovarian Cancer
No Cancer
Total BRCA1
Breast Cancer
Only
Ovarian Cancer
Only
Breast and
Ovarian Cancer
No Cancer
Total BRCA2 TOTAL
ILUH Iceland Landspitali - University Hospital
Iceland 5 0 3 0 8 145 2 10 33 190 198
INHERIT
INterdisciplinary HEalth Research Internal Team BReast CAncer susceptibility
Canada (Quebec) 48 13 4 53 118 51 5 3 58 117 235
IOVHBOCS Istituto Oncologico Veneto Italy 70 50 17 28 165 98 14 8 31 151 316
IPOBCS
Portuguese Oncology Institute-Porto Breast Cancer Study
Portugal 28 14 5 50 97 66 2 2 53 123 220
KCONFAB
Kathleen Cuningham Consortium for Research into Familial Breast Cancer
Australia/New Zealand
363 44 29 290 726 301 21 9 253 584 1,310
KOHBRA Korean Hereditary Breast Cancer Study
Korea 99 1 6 26 132 153 1 2 62 218 350
MAGIC Modifiers and Genetics in Cancer
USA 35 11 2 66 114 32 4 1 52 89 203
MAYO Mayo Clinic USA 159 33 16 160 368 100 14 5 88 207 575
MCGILL McGill University Canada (Quebec) 25 2 2 30 59 17 1 0 25 43 102
MDAND MD Anderson Cancer Center USA 103 22 5 54 184 0 0 0 0 0 184
MOD-SQUAD
Modifier Study of Quantitative Effects on Disease
Czech Republic/Belgium
185 43 23 45 296 93 10 5 35 143 439
MSKCC Memorial Sloane Kettering Cancer Center
USA 201 29 15 117 362 148 23 2 86 259 621
MUV General Hospital Vienna Austria 214 37 28 185 464 126 6 7 86 225 689
NCI National Cancer Institute USA 40 10 4 98 152 18 5 1 51 75 227
4
BRCA1 BRCA2
Center ID Study Name Country
Breast Cancer
Only
Ovarian Cancer
Only
Breast and
Ovarian Cancer
No Cancer
Total BRCA1
Breast Cancer
Only
Ovarian Cancer
Only
Breast and
Ovarian Cancer
No Cancer
Total BRCA2 TOTAL
NNPIO N.N. Petrov Institute of Oncology
Russia 89 20 6 14 129 3 0 0 0 3 132
OCGN Ontario Cancer Genetics Network Canada 73 33 14 115 235 69 21 1 90 181 416
OSU CCG
The Ohio State University Comprehensive Cancer Center
USA 66 8 7 47 128 55 11 2 37 105 233
OUH Odense University Hospital Denmark 147 60 18 201 426 134 16 7 164 321 747
PBCS Università di Pisa Italy 47 16 12 23 98 42 2 0 14 58 156
SEABASS South East Asian Breast Cancer Association Study
Malaysia/Singa-pore
41 7 3 6 57 32 0 1 4 37 94
SMC Sheba Medical Centre Israel 301 133 21 340 795 167 42 7 179 395 1,190
SWE-BRCA Swedish Breast Cancer Study Sweden 215 97 43 212 567 85 20 2 68 175 742
UCHICAGO University of Chicago USA 36 3 6 44 89 39 6 1 22 68 157
UCLA University of California Los Angeles
USA 42 6 3 59 110 26 3 0 45 74 184
UCSF University of California San Francisco
USA 44 24 3 49 120 46 7 3 38 94 214
UKGRFOCR
UK and Gilda Radner Familial Ovarian Cancer Registries
UK/USA 25 103 11 45 184 4 21 2 12 39 223
UPENN University of Pennsylvania USA 229 47 30 148 454 147 16 9 123 295 749
VFCTG Victorian Familial Cancer Trials Group
Australia 71 20 11 6 108 42 12 2 13 69 177
WCP
Women's Cancer Program at Cedars-Sinai Medical Center
USA 54 62 13 127 256 17 16 4 45 82 338
TOTAL 9,052 2,317 1,041 7,171 19,581 6,180 682 272 4,766 11,900 31,481
1
Supplementary Table 2: Bins and Risks Used to Define Ovarian and Breast Cancer Cluster Regions (Depicted in Figure 1): BRCA1
Bin Putative Region*
Bin Starting
Nucleotide
Bin Ending Nucleotide N
N (Breast Cancer)
HR, 95% CI (Breast Cancer)
N (Ovarian Cancer)
HR, 95%CI (Ovarian Cancer)
Ratio (HR-Breast: HR-Ovarian) (95%CI)
P-Value
1 1 67 151 84 1.17 (0.93,1.48) 23 0.90 (0.60,1.33) 1.31 (0.82-2.09) 0.265 2 68 69 2328 1036 0.89 (0.82,0.96) 392 0.94 (0.83,1.07) 0.94 (0.81-1.10) 0.456 3 70 178 243 146 1.24 (1.04,1.48) 54 0.97 (0.73,1.27) 1.28 (0.94-1.75) 0.116 4 BCCR1 179 181 984 546 1.11 (1.01,1.22) 118 0.74 (0.61,0.89) 1.50 (1.21-1.85) <0.001 5 BCCR1 182 505 403 239 1.17 (1.03,1.34) 62 0.87 (0.67,1.12) 1.35 (1.00-1.82) 0.048 6 506 927 407 218 0.98 (0.85,1.13) 75 0.94 (0.75,1.18) 1.05 (0.80-1.38) 0.750 7 928 1116 398 198 0.89 (0.77,1.02) 81 0.96 (0.77,1.20) 0.92 (0.70-1.22) 0.573 8 1117 1379 370 167 1.00 (0.86,1.17) 55 1.07 (0.82,1.40) 0.94 (0.68-1.29) 0.686 9 OCCR 1380 1674 377 165 0.81 (0.69,0.95) 82 1.31 (1.05,1.63) 0.62 (0.47-0.82) 0.001
10 1675 1892 399 208 0.91 (0.80,1.05) 90 1.10 (0.89,1.36) 0.83 (0.64-1.08) 0.172 11 OCCR 1893 2071 390 168 0.84 (0.72,0.99) 76 1.20 (0.94,1.54) 0.70 (0.52-0.94) 0.019 12 OCCR 2072 2338 396 180 0.78 (0.67,0.91) 70 1.04 (0.81,1.33) 0.75 (0.56-0.99) 0.049 13 OCCR 2339 2475 450 210 0.88 (0.77,1.00) 94 1.21 (1.00,1.48) 0.72 (0.56-0.93) 0.010 14 2476 2685 448 208 0.89 (0.77,1.03) 73 1.05 (0.83,1.33) 0.85 (0.64-1.13) 0.251 15 OCCR 2686 3013 399 175 0.84 (0.73,0.98) 91 1.30 (1.05,1.61) 0.65 (0.50-0.85) 0.001 16 OCCR 3014 3254 378 164 0.79 (0.68,0.92) 96 1.23 (1.00,1.52) 0.64 (0.48-0.85) 0.002 17 3255 3331 393 180 0.90 (0.77,1.05) 78 1.12 (0.89,1.41) 0.80 (0.61-1.07) 0.131 18 3332 3482 373 179 0.86 (0.75,1.00) 84 1.13 (0.90,1.42) 0.76 (0.58-1.01) 0.059 19 3483 3661 398 196 0.85 (0.74,0.98) 62 0.84 (0.64,1.10) 1.02 (0.74-1.40) 0.910 20 3662 3753 384 187 0.93 (0.80,1.07) 68 1.13 (0.91,1.41) 0.82 (0.63-1.08) 0.152 21 3754 3770 406 210 1.00 (0.87,1.15) 88 1.14 (0.93,1.41) 0.88 (0.67-1.14) 0.326 22 3771 4016 350 148 0.93 (0.79,1.11) 67 0.95 (0.73,1.25) 0.98 (0.70-1.36) 0.892 23 OCCR 4017 4062 321 118 0.65 (0.53,0.78) 101 1.11 (0.87,1.41) 0.58 (0.42-0.81) 0.001 24 4063 4167 419 217 1.20 (1.04,1.38) 67 1.15 (0.92,1.43) 1.04 (0.79-1.37) 0.761 25 4168 4327 513 281 1.18 (1.04,1.34) 82 0.99 (0.79,1.24) 1.20 (0.92-1.56) 0.186 26 BCCR2 4328 4945 417 252 1.16 (1.02,1.32) 67 0.86 (0.68,1.11) 1.34 (1.01-1.78) 0.042 27 4946 5123 486 270 1.00 (0.88,1.13) 90 0.93 (0.75,1.16) 1.07 (0.83-1.39) 0.605 28 5124 5260 361 224 1.17 (1.02,1.34) 67 0.90 (0.70,1.16) 1.30 (0.97-1.74) 0.076 29 BCCR2 5261 5266 3052 1666 1.20 (1.13,1.27) 459 0.92 (0.83,1.02) 1.30 (1.14-1.48) <0.001 30 BCCR2 5267 5563 482 289 1.30 (1.15,1.47) 65 0.79 (0.62,1.01) 1.65 (1.25-2.17) <0.001
*BCCR: breast cancer cluster region, OCCR: ovarian cancer cluster region
1
Supplementary Table 3: Bins and Risks Used to Define Ovarian and Breast Cancer Cluster Regions (Depicted in Figure 2): BRCA2
Bin Putative Region*
Bin Starting
Nucleotide
Bin Ending
Nucleotide N
N (Breast Cancer)
HR, 95%CI (Breast Cancer)
N (Ovarian Cancer)
HR, 95% CI (Ovarian Cancer)
Ratio (HR-Breast: HR-Ovarian)
P-Value
1 BCCR1 1 596 663 391 1.17 (1.04,1.32) 33 0.68 (0.43,1.08) 1.72 (1.06-2.78) 0.028 2 597 771 586 381 1.11 (0.96,1.29) 43 1.13 (0.76,1.68) 0.98 (0.64-1.51) 0.931 3 BCCR1' 772 1806 623 364 1.08 (0.97,1.20) 31 0.66 (0.46,0.96) 1.63 (1.11-2.40) 0.014 4 1807 2786 573 310 0.96 (0.85,1.08) 39 0.83 (0.60,1.14) 1.16 (0.82-1.66) 0.399 5 2787 3248 611 332 0.98 (0.88,1.10) 42 0.88 (0.64,1.21) 1.12 (0.79-1.59) 0.524 6 OCCR1 3249 3847 590 285 0.78 (0.69,0.88) 61 1.38 (1.07,1.78) 0.57 (0.42-0.76) 0.000 7 OCCR1 3848 4478 535 264 0.91 (0.80,1.03) 57 1.38 (1.05,1.80) 0.66 (0.49-0.89) 0.007 8 OCCR1 4479 5238 555 251 0.80 (0.70,0.90) 57 1.19 (0.89,1.59) 0.67 (0.48-0.93) 0.017 9 OCCR1 5239 5681 523 280 0.98 (0.87,1.10) 56 1.54 (1.15,2.04) 0.64 (0.47-0.87) 0.005
10 5682 5945 611 357 1.09 (0.98,1.22) 43 0.87 (0.63,1.20) 1.26 (0.89-1.77) 0.188 11 OCCR1 5946 5946 1341 579 0.74 (0.64,0.86) 155 1.27 (0.99,1.63) 0.58 (0.45-0.76) 0.000 12 5947 6275 612 322 1.07 (0.96,1.20) 41 0.80 (0.58,1.09) 1.35 (0.96-1.90) 0.090 13 6276 6644 542 301 0.95 (0.85,1.07) 43 0.99 (0.73,1.34) 0.97 (0.69-1.35) 0.841 14 OCCR2 6645 7471 582 302 0.85 (0.74,0.97) 64 1.49 (1.12,1.97) 0.57 (0.41-0.80) 0.001 15 7472 7933 571 320 1.09 (0.96,1.23) 47 1.03 (0.73,1.45) 1.06 (0.74-1.52) 0.759 16 BCCR2 7934 8535 752 455 1.19 (1.07,1.33) 43 0.50 (0.34,0.74) 2.37 (1.56-3.59) 0.000 17 BCCR2 8536 8904 507 302 1.27 (1.11,1.44) 31 0.60 (0.39,0.92) 2.12 (1.34-3.35) 0.001 18 8905 9118 565 345 1.22 (1.08,1.39) 34 0.93 (0.60,1.46) 1.31 (0.82-2.11) 0.264 19 9119 9925 558 311 1.07 (0.96,1.20) 34 0.73 (0.52,1.04) 1.46 (0.99-2.14) 0.054