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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Breast Cancer Res Treat. Author manuscript; available in PMC 2010 September 1.
Published in final edited form as:
PMCID: PMC2728174

No evidence that GATA3 rs570613 SNP modifies breast cancer risk


GATA-binding protein 3 (GATA3) is a transcription factor that is crucial to mammary gland morphogenesis and differentiation of progenitor cells, and has been suggested to have a tumor suppressor function. The rs570613 single nucleotide polymorphism (SNP) in intron 4 of GATA3 was previously found to be associated with a reduction in breast cancer risk in the Cancer Genetic Markers of Susceptibility project and in pooled analysis of two case-control studies from Norway and Poland (Ptrend =0.004), with some evidence for a stronger association with estrogen receptor (ER) negative tumours [1]. We genotyped GATA3 rs570613 in 6,388 cases and 4,995 controls from the Breast Cancer Association Consortium (BCAC) and 5,617 BRCA1 and BRCA2 carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). We found no association between this SNP and breast cancer risk in BCAC cases overall (ORper-allele = 1.00, 95% CI 0.94 − 1.05), in ER negative BCAC cases (ORper-allele = 1.02, 95% CI 0.91−1.13), in BRCA1 mutation carriers RRper-allele = 0.99, 95% CI 0.90−1.09) or BRCA2 mutation carriers (RRper-allele = 0.93, 95% CI 0.80−1.07). We conclude that there is no evidence that either GATA3 rs570613, or any variant in strong linkage disequilibrium with it, is associated with breast cancer risk in women.

Keywords: GATA3, breast cancer, polymorphism, BRCA1 and BRCA2, risk


The GATA-binding protein 3 (GATA3) transcription factor is crucial to mammary gland morphogenesis and differentiation of progenitor cells, and continues to be expressed in normal breast luminal epithelial cells throughout puberty and pregnancy [2-4]. Gene expression profiling aimed at correlating genotypic and phenotypic characteristics of breast tumors has implicated GATA3 in tumorigenesis of luminal A subtypes which are associated with more favourable survival than other subtypes [5-7]. GATA3 expression is strongly correlated with ER expression [8,9], and its utility in predicting clinical outcome in ER-positive tumors has also been reported [10,11]. GATA3 somatic mutations have been identified in a subset of ER-positive breast tumors, and cells transfected with these GATA3 mutants show increased proliferation compared with wild-type transfectants, suggesting a tumor suppressor function [12]. Analysis of association between breast cancer and GATA3 single nucleotide polymorphisms (SNPs) in two European studies suggested that rs570613, in intron 4, was associated with a 15−18% overall reduction in breast cancer risk (Ptrend =0.004), with some evidence for a stronger association with ER-negative tumors [1]. To test this association, we analysed this SNP in case-control studies and BRCA1 and BRCA2 carriers from two large consortia.

Materials and Methods

Analysis of breast cancer risk was based on genotype data from 6,388 cases (largely population-based) and 4,995 controls identified through five European and Australian studies (ABCFS, GENICA, HEBCS, SASBAC and kConFab; Table 1) in the Breast Cancer Association Consortium (BCAC; ref. 13), and 5,617 BRCA1 and BRCA2 mutation carriers from 11 studies from Europe, Australia and North America (EMBRACE, DNA-HEBON, kConFab, SWE-BRCA, MUV, UPENN, MAYO, HEBCS, FCCC, PBCS and Georgetown; ref. 14,15) in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). The design, for both consortia, genotyping methods and quality control procedures have been reported elsewhere [14,15]. All statistical tests were two sided, and analyses were carried out using the S-Plus (Insightful Corp.) software system and STATA v. 9.0 (Stata Corp.). Statistical significance was based on a nominal P-value less than 0.05.

Table 1
Risk of breast cancer associated with the GATA3 rs570613 genotypes overall, and stratified by ER status, from five BCAC case-control studies

For the BCAC study, odds ratios (ORs) for heterozygotes and homozygotes, relative to the common homozygotes, were estimated using logistic regression, adjusted for age and study, together with per allele ORs (estimated by fitting the number of rare alleles carried as a continuous covariate). Similar methods were used to obtain risk estimates according to ER status where data were available.

For the CIMBA study, the associations between breast cancer risk and GATA3 rs570613 genotypes for BRCA1 and BRCA2 mutation carriers were estimated using Cox proportional hazards regression analysis with breast cancer as the outcome and age as the time-to-event variable [16]. Subjects were followed from birth until breast cancer, bilateral prophylactic mastectomy, ovarian cancer, age at last contact, or age 80. A weighted cohort approach was used to adjust estimates for the potential over-sampling of affected individuals [17]. Rate ratios (RR) and 95% CIs were estimated for all carriers combined, and for BRCA1 and BRCA2 mutation carriers separately, for heterozygotes and rare homozygotes compared with common homozygotes, and per allele. To allow for the fact that the CIMBA cohort includes related individuals we used a robust variance approach to compute the variance of the RRs [18]. Additional analyses were conducted by adjusting for oophorectomy status as a time dependent covariate and by excluding affected individuals who were recruited more than five years after breast cancer diagnosis.


All contributing studies met genotyping quality control criteria [14,15]. In BCAC controls the combined mean age at interview was 53.1 (SD 14.2) and in cases the age at diagnosis was 54.6 (SD 12.5). Table 1 shows genotype frequencies for cases and controls for each BCAC study, together with study-specific and pooled ORs and 95% CIs for association between the GATA3 rs570613 SNP and breast cancer, both overall and stratified on ER status. GATA3 genotypes were not associated with breast cancer risk for either the combined analysis, or for any of the five individual studies. Similar analyses stratified by ER status also showed no association between GATA3 genotypes and risk of either ER-positive or ER-negative tumors.

In the CIMBA study, there was no evidence of an association between risk of breast cancer and rs570613 genotypes, in BRCA1 and BRCA2 carriers pooled, or when BRCA1 and BRCA2 carriers were analysed separately (Table 2). Analyses adjusting for oophorectomy status, or restricted to cases ascertained within five years of diagnosis, likewise showed no association (Table 2).

Table 2
RR estimates for the association between GATA3 rs570613 genotypes and risk of breast cancer for BRCA1 and BRCA2 carriers from CIMBA


Our study comprehensively evaluated the GATA3 rs570613 SNP for association with risk of breast cancer, but failed to replicate the previous report of an association with risk. The BCAC analysis had ~99% power to detect an OR of the magnitudes previously reported (0.82−0.85), and the 95% CI for the per-allele OR (0.94−1.05) shows that we can exclude all but very small associations. Likewise, GATA3 rs570613 genotypes were not associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers. Results remained similar when analyses were adjusted for oophorectomy status in a time-dependent manner or when cases diagnosed more than five years before recruitment were excluded to account for possible survival bias. There was no evidence of an association with ER status in BCAC studies but the number of ER-negative cases was limited to 868, and hence the 95% CI was wider (0.91−1.13). However, most BRCA1-associated tumors are ER-negative [19], so the absence of any association in BRCA1 carriers is consistent with the lack of an association with ER-negative disease. The potential for variation in study-specific estimates is inherent in consortium analyses involving multiple studies. However, all BCAC studies selected controls from the same source population as cases, participants being predominantly Caucasian. There was no evidence of heterogeneity in risk estimates from either consortiium analysis (PHeterogeneity ≥0.3). In summary, the role of GATA3 in breast tumor biology and prognosis has been well documented [20] and the hypothesis that variants in GATA3 might influence breast cancer risk is appealing. However, our data demonstrate convincingly that neither rs570613, nor any SNP in significant linkage disequilibrium with it, is likely to have a major influence on breast cancer risk.


We wish to thank Claudine Isaacs for the samples from Georgetown; Heather Thorne, Eveline Niedermayr, all the kConFab research nurses and staff, the heads and staff of the Family Cancer Clinics, and the Clinical Follow Up Study (funded by NHMRC grants 145684, 288704 and 454508) for their contributions to this resourcekConFab; the AOCS Management Group (D Bowtell, G Chenevix-Trench, A deFazio, D Gertig, A Green, P Webb), all the clinical and scientific collaborators of AOCS (, the project staff, and collaborating institutions; Maggie Angelakos, Judi Maskiell and Gillian Dite (ABCFS); RN Hanna Jäntti for help with the patient data and the Finnish Cancer registry for the cancer data (HEBCS); Anne-Catherine Spiess and Georg Pfeiler (MUV); Betsy Bove, Mary Daly, John Malick, Beth Stearman, JoEllen Weaver (FCCC); Gisella Lombardi (PBCS); Beate Pesch, Volker Harth and Thomas Brüning for recruitment of GENICA study subjects and collection of epidemiological data.

The Epidemiological study of BRCA1 & BRCA2 mutation carriers (EMBRACE) collaborating centres are: Coordinating Centre, Cambridge (Dr Susan Peock; Mrs Margaret Cook); North of Scotland Regional Genetics Service, Aberdeen (Prof Neva Haites: Dr Helen Gregory); Northern Ireland Regional Genetics Service, Belfast (Prof Patrick Morrison); West Midlands Regional Clinical Genetics Service, Birmingham (Dr Trevor Cole; Dr Carole McKeown, Lucy Burgess); South West Regional Genetics Service, Bristol (Dr Alan Donaldson); East Anglian Regional Genetics Service, Cambridge (Dr Joan Paterson); Medical Genetics Services for Wales, Cardiff (Dr Alexandra Murray; Dr Mark Rogers; Dr Emma McCann); Dublin and National Centre for Medical Genetics, Dublin (Dr John Kennedy; Prof Peter Daly; Dr David Barton); St. James's Hospital, South East of Scotland Regional Genetics Service, Edinburgh (Dr Mary Porteous; Prof Michael Steel); Peninsula Clinical Genetics Service, Exeter (Dr Carole Brewer; Dr Julia Rankin) West of Scotland Regional Genetics Service, Glasgow (Dr Rosemarie Davidson; Dr Victoria Murday, Nicola Bradshaw, Catherine Watt, Lesley Snadden, Mark Longmuir); South East Thames Regional Genetics Service, Guys Hospital London (Dr Louise Izatt; Dr Gabriella Pichert, Caroline Langman); North West Thames Regional Genetics Service, Harrow (Dr Huw Dorkins); Leicestershire Clinical Genetics Service, Leicester (Dr Julian Barwell); Yorkshire Regional Genetics Service, Leeds (Prof Timothy Bishop; Dr Carol Chu); Merseyside and Cheshire Clinical Genetics Service, Liverpool (Dr Ian Ellis); Manchester Regional Genetics Service, Manchester (Prof Gareth Evans, Dr Fiona Lalloo; Mr Andrew Shenton); North East Thames Regional Genetics Service, NE Thames (Dr Alison Male; Dr Anne Robinson); Nottingham Centre for Medical Genetics, Nottingham (Dr Carol Gardiner); Northern Clinical Genetics Service, Newcastle (Dr Fiona Douglas; Prof John Burn); Oxford Regional Genetics Service, Oxford (Dr Lucy Side; Dr Lisa Walker; Ms Sarah Durell); Cancer Genetics Unit, Royal Marsden NHS Foundation Trust (Dr Ros Eeles, Dr Susan Shanley, Prof Naz Rahman, Prof Richard Houlston, Elizabeth Bancroft, Lucia D'Mello, Audrey Ardern-Jones); North Trent Clinical Genetics Service, Sheffield (Dr Jackie Cook; Dr Oliver Quarrell); South West Thames Regional Genetics Service, London (Prof Shirley Hodgson, Sheila Goff); Wessex Clinical Genetics Service, Southampton (Prof Diana Eccles; Dr Anneke Lucassen);. DFE is the PI of the study.

The Swedish BRCA1 and BRCA2 study (SWE-BRCA) collaborators are Per Karlsson, Margareta Nordling, Annika Bergman, and Zakaria Einbeigi, Gothenburg, Sahlgrenska University Hospital; Marie Stenmark-Askmalm and Sigrun Liedgren, Linkoping University Hospital; Ake Borg, Niklas Loman, Hakan Olsson, Ulf Kristoffersson, Helena Jernstrom, and Katja Backenhorn, Lund University Hospital; Annika Lindblom, Brita Arver, Anna von Wachenfeldt, Annelie Liljegren, Gisela Barbany-Bustinza, and Johanna Rantala, Stockholm, Karolinska University Hospital; Henrik Gronberg, Eva-Lena Stattin, and Monica Emanuelsson, Umea University Hospital; Hans Bostrom, Richard Rosenquist Brandell, and Niklas Dahl, Uppsala University Hospital.

The Hereditary Breast and Ovarian Cancer Working Group Netherlands (HEBON) collaborating centres are: Netherlands Cancer Institute, Amsterdam: Frans Hogervorst, Anouk Pijpe, Senno Verhoef, Flora van Leeuwen, Laura van ‘t Veer, Matti Rookus; Erasmus University Medical Centre, Rotterdam: Ans van den Ouweland, Mieke Schutte, Margriet Collée, Agnes Jager, Maartje Hooning, Caroline Seynaeve; Leiden University Medical Centre, Leiden: Juul Wijnen, Christi van Asperen, Peter Devilee; Radboud University Nijmegen Medical Centre, Nijmegen: Marjolijn Ligtenberg, Nicoline Hoogerbrugge; University Medical Centre Utrecht, Utrecht: Rob van der Luijt, Margreet Ausems; Amsterdam Medical Centre: Cora Aalfs, Theo van Os; VU University Medical Centre, Amsterdam: Hans Gille, Hanne Meijers-Heijboer; University Hospital Maastricht, Maastricht: Rien Blok, Encarna Gomez-Garcia.

FJC, ZF and RT and the MAYO study were supported in part by U.S. National Institutes of Health grants CA122340 and CA128978 and an award from the Breast Cancer Research Foundation. kConFab is supported by grants from the National Breast Cancer Foundation, the National Health and Medical Research Council (NHMRC) and by the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, and the Cancer Foundation of Western Australia. AOCS was funded by U.S. Army Medical Research and Materiel Command under DAMD17-01-1-0729, the Cancer Council Tasmania and Cancer Foundation of Western Australia (AOCS study). The ABCFS was supported by the National Health and Medical Research Council (NHMRC) of Australia (#145604), the U.S. National Institutes of Health (RO1 CA102740-01A2) and by the National Cancer Institute, National Institutes of Health under RFA # CA-95-011 through cooperative agreements with members of the Breast Cancer Family Registry (Breast CFR) and PIs ”Cancer Care Ontario (UO1 CA69467)”, ”Columbia University (U01 CA69398)”, ”Fox Chase Cancer Center (U01 CA69631)”, ”Huntsman Cancer Institute (U01 CA69446)”, ”Northern California Cancer Center (U01 CA69417)”, ”University of Melbourne (U01 CA69638)”. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of collaborating centers in the Breast CFR, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the Breast CFR. The Australian Breast Cancer Family Study was initially supported by the National Health and Medical Research Council of Australia, the New South Wales Cancer Council, the Victorian Health Promotion Foundation. SWE-BRCA is supported by grants from the Swedish Cancer Society and Swedish County Council. The HEBCS study has been financially supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (110663), Finnish Cancer Society and the Sigrid Juselius Foundation; This work was supported in part by the Fox Chase Cancer Center Ovarian Cancer SPORE, P50 CA83638, and the Eileen Stein-Jacoby Fund. CIMBA data management” is funded by CR-UK. PBCS is supported by Fondazione Cassa di Risparmio. The GENICA study was supported by the German Human Genome Project and funded by the Federal Ministry of Education and Research (BMBF) Germany grants 01KW9975/5, 01KW9976/8, 01KW9977/0 and 01KW0114. Genotyping analysis was supported by the Robert Bosch Foundation of Medical Research, Stuttgart, Germany. The HEBON study and Anouk Pijpe are funded by the Dutch Cancer Society grant NKI2004-3088, NKI 2007−3756. GCT, JLH, MS and PW are supported by the NHMRC. Antonis Antoniou, Lesley McGuffog, Margaret Cook, Susan Peock and EMBRACE are funded by Cancer Research–UK.

We would also like to thank the 17,100 women who participated in these studies.


1. Garcia-Closas M, Troester MA, Qi Y, Langerod A, Yeager M, Lissowska J, Brinton L, Welch R, Peplonska B, Gerhard DS, Gram IT, Kristensen V, Borresen-Dale AL, Chanock S, Perou CM. Common genetic variation in GATA-binding protein 3 and differential susceptibility to breast cancer by estrogen receptor alpha tumor status. Cancer Epidemiol Biomarkers Prev. 2007;16:2269–75. [PubMed]
2. Patient RK, McGhee JD. The GATA family (vertebrates and invertebrates). Curr Opin Genet Dev. 2002;12:416–22. [PubMed]
3. Kouros-Mehr H, Slorach EM, Sternlicht MD, Werb Z. GATA-3 maintains the differentiation of the luminal cell fate in the mammary gland. Cell. 2006;127:1041–55. [PMC free article] [PubMed]
4. Asselin-Labat ML, Sutherland KD, Barker H, Thomas R, Shackleton M, Forrest NC, Hartley L, Robb L, Grosveld FG, van der Wees J, Lindeman GJ, Visvader JE. Gata-3 is an essential regulator of mammary-gland morphogenesis and luminal-cell differentiation. Nat Cell Biol. 2007;9:201–9. [PubMed]
5. Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, Pollack JR, Ross DT, Johnsen H, Akslen LA, Fluge O, Pergamenschikov A, Williams C, Zhu SX, Lonning PE, Borresen-Dale AL, Brown PO, Botstein D. Molecular portraits of human breast tumours. Nature. 2000;406:747–52. [PubMed]
6. Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, Hastie T, Eisen MB, van de Rijn M, Jeffrey SS, Thorsen T, Quist H, Matese JC, Brown PO, Botstein D, Eystein Lonning P, Borresen-Dale AL. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A. 2001;98:10869–74. [PubMed]
7. Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A, Martiat P, Fox SB, Harris AL, Liu ET. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci U S A. 2003;100:10393–8. [PubMed]
8. Hoch RV, Thompson DA, Baker RJ, Weigel RJ. GATA-3 is expressed in association with estrogen receptor in breast cancer. Int J Cancer. 1999;84:122–8. [PubMed]
9. van de Rijn M, Perou CM, Tibshirani R, Haas P, Kallioniemi O, Kononen J, Torhorst J, Sauter G, Zuber M, Kochli OR, Mross F, Dieterich H, Seitz R, Ross D, Botstein D, Brown P. Expression of Cytokeratins 17 and 5 Identifies a Group of Breast Carcinomas with Poor Clinical Outcome. Am J Pathol. 2002;161:1991–1996. [PubMed]
10. Mehra R, Varambally S, Ding L, Shen R, Sabel MS, Ghosh D, Chinnaiyan AM, Kleer CG. Identification of GATA3 as a breast cancer prognostic marker by global gene expression meta-analysis. Cancer Res. 2005;65:11259–64. [PubMed]
11. Parikh P, Palazzo JP, Rose LJ, Daskalakis C, Weigel RJ. GATA-3 expression as a predictor of hormone response in breast cancer. J Am Coll Surg. 2005;200:705–10. [PubMed]
12. Usary J, Llaca V, Karaca G, Presswala S, Karaca M, He X, Langerod A, Karesen R, Oh DS, Dressler LG, Lonning PE, Strausberg RL, Chanock S, Borresen-Dale AL, Perou CM. Mutation of GATA3 in human breast tumors. Oncogene. 2004;23:7669–78. [PubMed]
13. Garcia-Closas M, Hall P, Nevanlinna H, Pooley K, Morrison J, Richesson DA, Bojesen SE, Nordestgaard BG, Axelsson CK, Arias JI, Milne RL, Ribas G, Gonzalez-Neira A, Benitez J, Zamora P, Brauch H, Justenhoven C, Hamann U, Ko YD, Bruening T, Haas S, Dork T, Schurmann P, Hillemanns P, Bogdanova N, Bremer M, Karstens JH, Fagerholm R, Aaltonen K, Aittomaki K, von Smitten K, Blomqvist C, Mannermaa A, Uusitupa M, Eskelinen M, Tengstrom M, Kosma VM, Kataja V, Chenevix-Trench G, Spurdle AB, Beesley J, Chen X, Australian Ovarian Cancer Management, G. Kathleen Cuningham Foundation Consortium For Research Into Familial Breast, C. Devilee P, van Asperen CJ, Jacobi CE, Tollenaar RA, Huijts PE, Klijn JG, Chang-Claude J, Kropp S, Slanger T, Flesch-Janys D, Mutschelknauss E, Salazar R, Wang-Gohrke S, Couch F, Goode EL, Olson JE, Vachon C, Fredericksen ZS, Giles GG, Baglietto L, Severi G, Hopper JL, English DR, Southey MC, Haiman CA, Henderson BE, Kolonel LN, Le Marchand L, Stram DO, Hunter DJ, Hankinson SE, Cox DG, Tamimi R, Kraft P, Sherman ME, Chanock SJ, Lissowska J, Brinton LA, Peplonska B, Klijn JG, Hooning MJ, Meijers-Heijboer H, Collee JM, van den Ouweland A, Uitterlinden AG, Liu J, Lin LY, Yuqing L, Humphreys K, Czene K, Cox A, Balasubramanian SP, Cross SS, Reed MW, Blows F, Driver K, Dunning A, Tyrer J, Ponder BA, Sangrajrang S, Brennan P, McKay J, Odefrey F, Gabrieau V, Sigurdson A, Doody M, Struewing JP, Alexander B, Easton DF, Pharoah PD. Heterogeneity of breast cancer associations with five susceptibility loci by clinical and pathological characteristics. PLoS Genet. 2008;4:e1000054. [PMC free article] [PubMed]
14. Breast Cancer Association, C. Commonly studied single-nucleotide polymorphisms and breast cancer: results from the Breast Cancer Association Consortium. J Natl Cancer Inst. 2006;98:1382–96. [PubMed]
15. Antoniou AC, Spurdle AB, Sinilnikova OM, Healey S, Pooley KA, Schmutzler RK, Versmold B, Engel C, Meindl A, Arnold N, Hofmann W, Sutter C, Niederacher D, Deissler H, Caldes T, Kampjarvi K, Nevanlinna H, Simard J, Beesley J, Chen X, Neuhausen SL, Rebbeck TR, Wagner T, Lynch HT, Isaacs C, Weitzel J, Ganz PA, Daly MB, Tomlinson G, Olopade OI, Blum JL, Couch FJ, Peterlongo P, Manoukian S, Barile M, Radice P, Szabo CI, Pereira LH, Greene MH, Rennert G, Lejbkowicz F, Barnett-Griness O, Andrulis IL, Ozcelik H, Gerdes AM, Caligo MA, Laitman Y, Kaufman B, Milgrom R, Friedman E, Domchek SM, Nathanson KL, Osorio A, Llort G, Milne RL, Benitez J, Hamann U, Hogervorst FB, Manders P, Ligtenberg MJ, van den Ouweland AM, Peock S, Cook M, Platte R, Evans DG, Eeles R, Pichert G, Chu C, Eccles D, Davidson R, Douglas F, Godwin AK, Barjhoux L, Mazoyer S, Sobol H, Bourdon V, Eisinger F, Chompret A, Capoulade C, Bressac-de Paillerets B, Lenoir GM, Gauthier-Villars M, Houdayer C, Stoppa-Lyonnet D, Chenevix-Trench G, Easton DF. Common breast cancer-predisposition alleles are associated with breast cancer risk in BRCA1 and BRCA2 mutation carriers. Am J Hum Genet. 2008;82:937–48. [PubMed]
16. Korn EL, Graubard BI, Midthune D. Time-to-event analysis of longitudinal follow-up of a survey: choice of the time-scale. Am J Epidemiol. 1997;145:72–80. [PubMed]
17. Antoniou AC, Goldgar DE, Andrieu N, Chang-Claude J, Brohet R, Rookus MA, Easton DF. A weighted cohort approach for analysing factors modifying disease risks in carriers of high-risk susceptibility genes. Genet Epidemiol. 2005;29:1–11. [PubMed]
18. Lin DY, Wei LJ. The Robust Inference for the Cox Proportional Hazards Model. Journal of the American Statistical Association. 1989;84:1074–1078.
19. Lakhani SR, Reis-Filho JS, Fulford L, Penault-Llorca F, van der Vijver M, Parry S, Bishop T, Benitez J, Rivas C, Bignon YJ, Chang-Claude J, Hamann U, Cornelisse CJ, Devilee P, Beckmann MW, Nestle-Kramling C, Daly PA, Haites N, Varley J, Lalloo F, Evans G, Maugard C, Meijers-Heijboer H, Klijn JG, Olah E, Gusterson BA, Pilotti S, Radice P, Scherneck S, Sobol H, Jacquemier J, Wagner T, Peto J, Stratton MR, McGuffog L, Easton DF. Prediction of BRCA1 status in patients with breast cancer using estrogen receptor and basal phenotype. Clin Cancer Res. 2005;11:5175–80. [PubMed]
20. Kouros-Mehr H, Kim JW, Bechis SK, Werb Z. GATA-3 and the regulation of the mammary luminal cell fate. Curr Opin Cell Biol. 2008;20:164–70. [PMC free article] [PubMed]