To evaluate the association between a previously published 313 variant–based breast cancer (BC) polygenic risk score (PRS313) and contralateral breast cancer (CBC) risk, in
We included women of European ancestry with a prevalent first primary invasive BC (
For
The PRS313 can be used to refine individual CBC risks for
These authors contributed equally: Inge M. M. Lakeman, Alexandra J. van den Broek.
Shared last authors: Antonis C. Antoniou, Mark Robson, Marjanka K. Schmidt.
Lists of authors and their affiliations appears at the end of the paper.
Heterozygotes of germline pathogenic variants in
Two important factors influencing contralateral breast cancer risk in
The most predictive, well validated PRS for breast cancer in the general population is based on 313 breast cancer–associated variants (PRS313); it showed an association with breast cancer in ten prospective studies with an odds ratio (OR) per standard deviation (SD) of 1.61 and an area under the receiver–operator characteristic curve of 0.630.
We used retrospective cohort data from heterozygotes participating in the Consortium of Investigators of Modifiers of
Women were eligible for this retrospective analysis if they developed an invasive primary breast tumor without metastatic disease at least 1 year before the baseline age. Women without information about metastatic disease were assumed to have no metastatic disease ( Characteristics of the participants. UBC, CBC, UBC, CBC, 5,189 1,402 3,561 647 Genotyping array iCOGS 895 (17) 200 (14) 383 (11) 80 (12) OncoArray 4,294 (83) 1,202 (86) 3,178 (89) 567 (88) Birth cohort <1920 25 (0.5) 8 (0.6) 23 (0.6) 9 (1) 1920–1929 143 (3) 46 (3) 121 (3) 30 (5) 1930–1939 392 (8) 130 (9) 341 (10) 99 (15) 1940–1949 1,060 (20) 386 (28) 793 (22) 172 (27) 1950–1959 1,540 (30) 452 (32) 1,104 (31) 202 (31) 1960–1969 1,354 (26) 298 (21) 822 (23) 115 (18) ≥1970 675 (13) 82 (6) 357 (10) 20 (3) Variant classa I 3,354 (65) 904 (64) 3,207 (90) 570 (88) II 1,345 (26) 374 (27) 125 (4) 25 (4) III 490 (9) 124 (9) 229 (6) 52 (8) BRRM 160 (3) 0 101 (3) 0 Deceased 44 (0.8) 12 (0.9) 19 (0.5) 2 (0.3) Family historyb No BC 583 (11) 175 (12) 289 (8) 78 (12) 1 BC 906 (17) 270 (19) 760 (21) 127 (20) ≥ 2 BC 1,250 (24) 363 (26) 1,120 (31) 210 (32) Unknown 2,450 (47) 594 (42) 1,392 (39) 232 (36) Age at diagnosis Mean 41.8 38.5 44.5 41.8 Range 19–82 19–68 18–85 21–75 ER status Positive 570 (11) 92 (7) 1,302 (37) 182 (28) Negative 1,738 (33) 402 (29) 424 (12) 61 (9) Unknown 2,881 (56) 908 (65) 1,835 (52) 404 (62) Node status Positive 797 (15) 182 (13) 781 (22) 119 (18) Negative 1,544 (30) 441 (31) 877 (25) 151 (23) Unknown 2,848 (55) 779 56) 1,903 (53) 377 (58) Tumor sizec T1 1,261 (24) 314 (22) 842 (24) 136 (21) T2 771 (15) 211 (15) 553 (16) 87 (13) T3 67 (13) 12 (0.9) 78 (2) 8 (1) T4 16 (0.5) 2 (0.1) 22 (0.6) 2 (0.3) Unknown 3,074 (59) 863 (62) 2,066 (58) 414 (64) Chemotherapyd Yes 1,099 (21) 236 (17) 821 (23) 123 (19) No 576 (11) 212 (15) 503 (14) 129 (20) Unknown 3,514 (68) 954 (68) 2,237 (63) 395 (61) Adjuvant hormone therapy Yes 493 (10) 125 (9) 795 (22) 111 (17) No 1,103 (21) 288 (21) 474 (13) 135 (21) Unknown 3,593 (69) 989 (71) 2,292 (64) 401 (62) Adjuvant trastuzumab therapy Yes 11 (0.2) 1 (0.1) 20 (0.6) 0 (0) No 1,161 (22) 351 (25) 983 (28) 218 (34) Unknown 4,017 (77) 1,050 (75) 2,558 (72) 429 (66) Radiotherapy Yes 1,090 (21) 277 (20) 797 (22) 158 (24) No 535 (10) 141 (10) 420 (12) 84 (13) Unknown 3,564 (69) 984 (70) 2,344 (66) 405 (63) Age at diagnosis Mean – 47.3 – 51.24 Range – 26–80.5 – 23.8–86 Invasiveness Invasive – 1,267 (90) – 545 (84) Noninvasive – 135 (10) – 102 (16) ER status Positive – 101 (7) – 197 (30) Negative – 446 (32) – 50 (8) Unknown – 855 (61) – 400 (62) Standardized PRS313 mean (SD) Overall BC 0.08 (1.01) 0.13 (1.01) 0.09 (1.02) 0.27 (1.04) ER-positive BC 0.07 (1.01) 0.09 (1.01) 0.08 (1.01) 0.27 (1.03) ER-negative BC 0.09 (1.00) 0.23 (0.99) 0.07 (1.02) 0.23 (1.07) aVariant class: I = unstable or no protein, II = stable mutant protein, III = consequence unknown. bFamily history was defined as the number of first- or second-degree relatives affected with BC, ranging from 0 to ≥2. cTumor size: T1 = ≤ 2 cm (≤0.79 inches), T2 = > 2cm-5cm (>0.79–1.97 inches), T3 = > 5 cm (>1.97 inches), T4 = any size, with direct extension to the chest wall or skin. dIncluding neoadjuvant and adjuvant chemotherapy.
For most of the participants, genotyping was performed with the Illumina OncoArray.
We used the 313 variant–based PRS for breast cancer developed in an independent study using data from the general population as described previously;
To assess the associations between the three PRS and contralateral breast cancer risk in
Analyses were stratified by country (Table
The influence of possible confounding variables on the observed associations was assessed using the PRS exhibiting the largest associations. Possible confounding variables included breast cancer family history, age at diagnosis of the first breast cancer, pathological characteristics, and treatment of the first breast cancer. Each variable was added to the model one by one and in addition, a full model that included all possible confounders together was fitted. If the addition of a variable resulted in a change of more than 10% in the log HR, the variable was retained as a covariate in the final Cox regression model. To avoid excluding many participants with missing data for one of these included variables (Table
Secondary analyses were performed for ER-positive and ER-negative cases only, based on the ER status of the contralateral breast cancer, after imputation as described above. The average number of ER-positive and ER-negative cases in the ten imputed data sets is shown in Table
The interaction between the PRS with the age at first breast cancer diagnosis was tested in the final model, treating the PRS as a continuous variable. Furthermore, the effect size of the PRS was evaluated for groups based on the age at first primary breast cancer diagnosis (<40 years; 40 to 50 years; ≥50 years).
Absolute contralateral breast cancer risks were calculated at percentiles of the best-performing continuous PRS for both
All statistical tests were performed with R version 3.5.0.
In the analyses, 6,591
Results of the association analyses between the PRS and contralateral breast cancer risk are shown in Table Results of association analyses between the PRS313 and contralateral breast cancer risk. UBC cases, CBC cases, HRa 95% CI UBC cases, CBC cases, HRa 95% CI PRS continuous All CBC 5,189 1,402 1.12 1.06–1.18 5.98×10-5 3,561 647 1.15 1.07–1.25 1.94×10-4 Invasive CBC 5,324 1,267 1.13 1.07–1.20 3.15×10-5 3,663 545 1.15 1.06–1.25 6.02×10-4 Categorical PRS percentiles 0–5 260 48 0.81 0.59–1.11 0.188 166 28 1.06 0.71–1.58 0.782 5–10 259 54 0.77 0.57–1.03 0.082 198 26 0.68 0.44–1.04 0.074 10–20 519 131 0.94 0.76–1.15 0.544 355 51 0.91 0.66–1.25 0.554 20–40 1,038 230 0.83 0.70–0.98 0.031 697 108 0.87 0.68–1.13 0.295 40–60 (reference) 1,037 282 1.00 695 123 1.00 60–80 1,038 313 1.04 0.88–1.22 0.664 734 128 0.96 0.75–1.23 0.748 80–90 519 170 1.11 0.92–1.34 0.255 358 90 1.35 1.03–1.77 0.030 90–95 259 82 1.18 0.92–1.51 0.185 178 46 1.35 0.96–1.90 0.082 95–100 260 92 1.24 0.98–1.56 0.074 180 47 1.31 0.94–1.82 0.116 PRS*age BC1 continuous Main effect 5,189 1,402 1.48 1.15–1.89 2.03×10-3 3,561 647 1.53 1.11–2.12 0.010 Interaction effect 0.99 0.99–1.00 0.025 0.99 0.99–1.00 0.089 PRS effect per age group <40 2,339 815 1.22 1.14–1.31 4.79×10-8 1,238 268 1.23 1.09–1.38 5.78×10-4 40–50 1,821 456 0.99 0.90–1.09 0.785 1,306 261 1.19 1.05–1.34 6.91×10-3 ≥50 1,029 131 1.03 0.86–1.24 0.715 1,017 118 0.97 0.81–1.15 0.698 Variant classb Class I 3,354 904 1.11 1.03–1.18 4.32×10-3 3,207 570 1.16 1.07–1.26 1.99×10-4 Class II 1,345 374 1.15 1.04–1.28 4.75×10-3 125 25 0.91 0.65–1.28 0.594 aHRs for association with breast cancer and the continuous PRS313 are reported per standard deviation of the PRS in population-based controls. bClass I pathogenic variants result in an unstable or no protein. Class II pathogenic variants yield stable mutant proteins. Effect size of the association between contralateral breast cancer and the three different PRS313 after testing for covariates for the following selections: all contralateral breast cancer, invasive contralateral breast cancer only, ER-negative contralateral breast cancer, and ER-positive contralateral breast cancer. The numbers of unilateral and contralateral breast cancer cases and effect sizes are shown in Table
For
Neither sequential inclusion of possible confounders nor including all these confounders in one model changed the log HR estimate for the ER-negative PRS313 association more than 10% when compared with the model with no confounders (Table
Considering only invasive contralateral breast cancer as the event of interest resulted in a similar association with the ER-negative PRS313, HR per SD = 1.13, 95% CI (1.07–1.20),
Censoring at distant metastasis relapse, if applicable, did not change the effect size of the ER-negative PRS313, HR per SD = 1.12, 95% CI (1.06–1.18),
The HR estimates for association with contralateral breast cancer for different quantiles of the ER-negative PRS313, were consistent with the predicted HRs from the model using the continuous ER-negative PRS313 (Table HRs and 95% CI for percentiles of the ER-negative PRS313 for
For ER-positive contralateral breast cancer as event, the PRS313 showed the largest association, HR per SD = 1.32, 95% CI (1.12–1.56),
For
Neither sequential inclusion of possible confounders, nor including all these confounders in one model, changed the log HR estimate for the ER-positive PRS313 association more than 10% when compared with the model with no confounders (Table
Considering only invasive contralateral breast cancer as the event of interest resulted in a similar association, HR per SD for the ER-positive PRS313 = 1.15, 95% CI (1.06–1.25),
Censoring at distant metastasis relapse, if applicable, did not change the effect size of the ER-positive PRS313, HR per SD = 1.15, 95% CI (1.07–1.24),
The HR estimates for association with contralateral breast cancer for different quantiles of the ER-positive PRS313, were consistent with the predicted estimates using the continuous PRS313 (Table
The ER-positive PRS313 showed the largest association with ER-positive contralateral breast cancer for
A significant interaction between the age at first breast cancer diagnosis and the ER-negative PRS313 was found for
Categorizing age at first breast cancer diagnosis for
For
Estimate cumulative contralateral breast cancer risks, by categories of age at diagnosis of the first breast cancer are shown in Fig. Predicted absolute contralateral breast cancer risks by percentile of the continuous ER-negative PRS313 for
In this study we investigated the associations between an established PRS based on 313 variants for primary first breast cancer and contralateral breast cancer risks among
For both
Although we found clear associations between the PRS and contralateral breast cancer risk, the magnitude of these associations (expressed in terms of HRs) were smaller than previously reported for the first breast cancers. For
A limitation of this study is that participants were recruited through clinical genetic centers, resulting in ascertainment bias, as individuals are more likely to have a strong family of breast cancer and/or be affected at a young age to be referred for testing. This was a historical cohort in which follow-up was prior to entry into CIMBA, so that all cases are prevalent. Therefore, the breast cancer patients included in the analyses are likely to be at higher contralateral breast cancer risk when compared with the general
Although the relative risks of the PRS for contralateral breast cancer were modest, differences in the PRS may still have an important effect on the absolute risk, which is high.
To summarize, we have investigated the associations between PRS based on 313 variants with contralateral breast cancer risk in a large international series of
We acknowledge all the families, clinicians, family doctors, researchers, research nurses, research assistants, and technicians who contribute to the individual studies from which we used the data for this research and paper.
Conceptualization: A.C.C., M.R., M.K.S. Formal analysis: I.M.M.L., A.J.v.d.B., J.A.M.V., D.R.B. Resources: All authors. Supervision: A.C.C., M.R., M.K.S. Writing—original draft: I.M.M.L., A.C.C., M.R., M.K.S. Writing—review & editing: All authors.
This work was supported by the Alpe d’HuZes/Dutch Cancer Society (KWF Kankerbestrijding) project 6253 and Dutch Cancer Society (KWF Kankerbestrijding) project UL2014-7473. CIMBA: The CIMBA data management and data analysis were supported by Cancer Research–UK grants C12292/A20861, C12292/A11174. G.C.T. and A.B.S. are NHMRC Research Fellows. iCOGS: the European Community’s Seventh Framework Programme under grant agreement number 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 CA148065 and 1U19 CA148112–the GAME-ON initiative), the Department of Defence (W81XWH-10-1-0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer (CRN-87521), and the Ministry of Economic Development, Innovation and Export Trade (PSR-SIIRI-701), Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. OncoArray: the PERSPECTIVE and PERSPECTIVE I&I projects funded by the Government of Canada through Genome Canada and the Canadian Institutes of Health Research, the Ministère de l’Économie, de la Science et de l’Innovation du Québec through Genome Québec, and the Quebec Breast Cancer Foundation; the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) initiative and Discovery, Biology and Risk of Inherited Variants in Breast Cancer (DRIVE) project (NIH grants U19 CA148065 and X01HG007492); and Cancer Research UK (C1287/A10118 and C1287/A16563). BCFR: UM1 CA164920 from the National Cancer Institute. The content of this paper does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the Breast Cancer Family Registry (BCFR), nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR. BFBOCC: Lithuania (BFBOCC-LT): Research Council of Lithuania grant SEN-18/2015. BIDMC: Breast Cancer Research Foundation. BMBSA: Cancer Association of South Africa (PI Elizabeth J. van Rensburg). BRI-COH: S.L.N. is partially supported by the Morris and Horowitz Families Professorship. CNIO: Spanish Ministry of Health PI16/00440 supported by FEDER funds, the Spanish Ministry of Economy and Competitiveness (MINECO) SAF2014-57680-R and the Spanish Research Network on Rare diseases (CIBERER). COH-CCGCRN: Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under grant number R25CA112486, and RC4CA153828 (PI: J. Weitzel) from the National Cancer Institute and the Office of the Director, National Institutes of Health. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. CONSIT TEAM: Associazione Italiana Ricerca sul Cancro (AIRC; IG2015 number 16732) to P. Peterlongo. DEMOKRITOS: European Union (European Social Fund–ESF) and Greek national funds through the Operational Program “Education and Lifelong Learning” of the National Strategic Reference Framework (NSRF)–Research Funding Program of the General Secretariat for Research & Technology: SYN11_10_19 NBCA. Investing in knowledge society through the European Social Fund. DFKZ: German Cancer Research Center. EMBRACE: Cancer Research UK Grants C1287/A10118 and C1287/A11990. D.G.E. and F.L. are supported by an NIHR grant to the Biomedical Research Centre, Manchester. The Investigators at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust are supported by an NIHR grant to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. R.E. and E.B. are supported by Cancer Research UK Grant C5047/A8385. R.E. is also supported by NIHR support to the Biomedical Research Centre at The Institute of Cancer Research and The Royal Marsden NHS Foundation Trust. FCCC: A.K.G. was in part funded by the NCI (R01 CA214545), The University of Kansas Cancer Center Support Grant (P30 CA168524), The Kansas Institute for Precision Medicine (P20 GM130423), and the Kansas Bioscience Authority Eminent Scholar Program. A.K.G. is the Chancellors Distinguished Chair in Biomedical Sciences Professorship. FPGMX: A. Vega is supported by the Spanish Health Research Foundation, Instituto de Salud Carlos III (ISCIII), partially supported by FEDER funds through Research Activity Intensification Program (contract grant numbers: INT15/00070, INT16/00154, INT17/00133), and through Centro de Investigación Biomédica en Red de Enferemdades Raras CIBERER (ACCI 2016: ER17P1AC7112/2018); Autonomous Government of Galicia (Consolidation and structuring program: IN607B), and by the Fundación Mutua Madrileña. The German Consortium for Hereditary Breast and Ovarian Cancer (GC-HBOC) is funded by the German Cancer Aid (110837, 70111850, coordinator: Rita K. Schmutzler, Cologne) and the Ministry for Innovation, Science and Research of the State of North Rhine-Westphalia (#323-8.0302.16.02-132142). GEMO: initially funded by the French National Institute of Cancer (INCa, PHRC Ile de France, grant AOR 01 082, 2001-2003, grant 2013-1-BCB-01-ICH-1), the Association “Le cancer du sein, parlons-en!” Award (2004), the Association for International Cancer Research (2008-2010), and the Foundation ARC pour la recherche sur le cancer (grant PJA 20151203365). It also received support from the Canadian Institute of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program (2008–2013), and the European commission FP7, Project «Collaborative Ovarian, breast and prostate Gene-environment Study (COGS), Large-scale integrating project» (2009–2013). GEMO is currently supported by the INCa grant SHS-E-SP 18-015. GEORGETOWN: The Survey, Recruitment, and Biospecimen Collection Shared Resource at Georgetown University (NIH/NCI grant P30-CA051008), the Fisher Center for Hereditary Cancer and Clinical Genomics Research, and the Nina Hyde Center for Breast Cancer Research. G-FAST: Bruce Poppe is a senior clinical investigator of FWO. Mattias Van Heetvelde obtained funding from IWT. HCSC: Spanish Ministry of Health PI15/00059, PI16/01292, and CB-161200301 CIBERONC from ISCIII (Spain), partially supported by European Regional Development FEDER funds. HEBCS: Helsinki University Hospital Research Fund, the Finnish Cancer Society and the Sigrid Juselius Foundation. The HEBON study is supported by the Dutch Cancer Society grants NKI1998-1854, NKI2004-3088, NKI2007-3756, the Netherlands Organisation of Scientific Research grant NWO 91109024, the Pink Ribbon grants 110005 and 2014-187.WO76, the BBMRI grant NWO 184.021.007/CP46 and the Transcan grant JTC 2012 Cancer 12-054. HRBCP: Hong Kong Sanatorium and Hospital, Dr Ellen Li Charitable Foundation, The Kerry Group Kuok Foundation, National Institute of Health1R 03CA130065, and North California Cancer Center. HUNBOCS: Hungarian Research Grants KTIA-OTKA CK-80745, NKFI_OTKA K-112228 and TUDFO/51757/2019-ITM. ICO: Contract grant sponsor: Supported by the Carlos III National Health Institute funded by FEDER funds–a way to build Europe–(PI16/00563, PI19/00553 and CIBERONC); the Government of Catalonia (Pla estratègic de recerca i innovació en salut (PERIS) Project MedPerCan, 2017SGR1282 and 2017SGR496); and CERCA program.IHCC: supported by grant PBZ_KBN_122/P05/2004 and the program of the Minister of Science and Higher Education under the name “Regional Initiative of Excellence” in 2019–2022 project number 002/RID/2018/19 amount of financing 12 000 000 PLN. ILUH: Icelandic Association “Walking for Breast Cancer Research” and by the Landspitali University Hospital Research Fund. INHERIT: Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program–grant CRN-87521 and the Ministry of Economic Development, Innovation and Export Trade–grant # PSR-SIIRI-701. IOVHBOCS: Ministero della Salute and “5×1000” Istituto Oncologico Veneto grant. IPOBCS: Liga Portuguesa Contra o Cancro. kConFab: The National Breast Cancer Foundation, and previously by the National Health and Medical Research Council (NHMRC), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. KOHBRA: the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), and the National R&D Program for Cancer Control, Ministry of Health & Welfare, Republic of Korea (HI16C1127; 1020350; 1420190). KUMC: NIGMS P20 GM130423 (to A.K.G.). MAYO: NIH grants CA116167, CA192393 and CA176785, an NCI Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA116201), and a grant from the Breast Cancer Research Foundation. MCGILL: Jewish General Hospital Weekend to End Breast Cancer, Quebec Ministry of Economic Development, Innovation and Export Trade. Marc Tischkowitz is supported by the funded by the European Union Seventh Framework Program (2007Y2013)/European Research Council (Grant No. 310018). MODSQUAD: MH CZ–DRO (MMCI, 00209805) and LM2018125, MEYS–NPS I–LO1413 to LF, and by Charles University in Prague project UNCE204024 (MZ). MSKCC: the Breast Cancer Research Foundation, the Robert and Kate Niehaus Clinical Cancer Genetics Initiative, the Andrew Sabin Research Fund and a Cancer Center Support Grant/Core Grant (P30 CA008748). NAROD: 1R01 CA149429-01. NCI: the Intramural Research Program of the US National Cancer Institute, NIH, and by support services contracts NO2-CP-11019-50, N02-CP-21013-63 and N02-CP-65504 with Westat, Inc, Rockville, MD. NICCC: Clalit Health Services in Israel, the Israel Cancer Association and the Breast Cancer Research Foundation (BCRF), NY. NNPIO: the Russian Foundation for Basic Research (grants 17-00-00171, 18-515-45012 and 19-515-25001). NRG Oncology: U10 CA180868, NRG SDMC grant U10 CA180822, NRG Administrative Office and the NRG Tissue Bank (CA 27469), the NRG Statistical and Data Center (CA 37517) and the Intramural Research Program, NCI. OSUCCG: Ohio State University Comprehensive Cancer Center. PBCS: supported by the “Fondazione Pisa per la Scienza, project nr. 127/2016. Maria A Caligo was supported by the grant: “n. 127/16 Caratterizzazione delle varianti missenso nei geni BRCA1/2 per la valutazione del rischio di tumore al seno” by Fondazione Pisa, Pisa, Italy; SEABASS: Ministry of Science, Technology and Innovation, Ministry of Higher Education (UM.C/HlR/MOHE/06) and Cancer Research Initiatives Foundation. SMC: the Israeli Cancer Association. SWE-BRCA: the Swedish Cancer Society. UCHICAGO: NCI Specialized Program of Research Excellence (SPORE) in Breast Cancer (CA125183), R01 CA142996, 1U01CA161032 and by the Ralph and Marion Falk Medical Research Trust, the Entertainment Industry Fund National Women’s Cancer Research Alliance and the Breast Cancer research Foundation. O.I.O. is an ACS Clinical Research Professor. UCLA: Jonsson Comprehensive Cancer Center Foundation; Breast Cancer Research Foundation. UCSF: UCSF Cancer Risk Program and Helen Diller Family Comprehensive Cancer Center. UKFOCR: Cancer Research h UK. UPENN: Breast Cancer Research Foundation; Susan G. Komen Foundation for the cure, Basser Research Center for BRCA. UPITT/MWH: Hackers for Hope Pittsburgh. VFCTG: Victorian Cancer Agency, Cancer Australia, National Breast Cancer Foundation. WCP: B.Y.K. is funded by the American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN) and the National Center for Advancing Translational Sciences (NCATS), grant UL1TR000124.
CIMBA data is available on request. To receive access to the data, a concept form must be submitted, which will then be reviewed by the CIMBA Data Access Coordination Committee (DACC). Please contact Lesley McGuffog (email: ljm26@medschl.cam.ac.uk) to get access to these concept forms (
All participants were recruited by the host institutions under protocols approved by local ethics review boards and provided written informed consent.
C. Isaacs is consultant to Astra Zeneca, Novartis, Pfizer, Genentech, PUMA, Seattle Genetics, and received research support from Tesaro. The other authors declare no competing interests.
Supplementary information Supplementary table S2
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