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Germline mutations in BRCA1 and BRCA2 are associated with increased risks of breast and ovarian cancer. A genome-wide association study (GWAS) identified six alleles associated with risk of ovarian cancer for women in the general population. We evaluated four of these loci as potential modifiers of ovarian cancer risk for BRCA1 and BRCA2 mutation carriers. Four single-nucleotide polymorphisms (SNPs), rs10088218 (at 8q24), rs2665390 (at 3q25), rs717852 (at 2q31), and rs9303542 (at 17q21), were genotyped in 12,599 BRCA1 and 7,132 BRCA2 carriers, including 2,678 ovarian cancer cases. Associations were evaluated within a retrospective cohort approach. All four loci were associated with ovarian cancer risk in BRCA2 carriers; rs10088218 per-allele hazard ratio (HR) = 0.81 (95% CI: 0.67–0.98) P-trend = 0.033, rs2665390 HR = 1.48 (95% CI: 1.21–1.83) P-trend = 1.8 × 10−4, rs717852 HR = 1.25 (95% CI: 1.10–1.42) P-trend = 6.6 × 10−4, rs9303542 HR = 1.16 (95% CI: 1.02–1.33) P-trend = 0.026. Two loci were associated with ovarian cancer risk in BRCA1 carriers; rs10088218 per-allele HR = 0.89 (95% CI: 0.81–0.99) P-trend = 0.029, rs2665390 HR = 1.25 (95% CI: 1.10–1.42) P-trend = 6.1 × 10−4. The HR estimates for the remaining loci were consistent with odds ratio estimates for the general population. The identification of multiple loci modifying ovarian cancer risk may be useful for counseling women with BRCA1 and BRCA2 mutations regarding their risk of ovarian cancer.
Pathogenic mutations in the BRCA1 (MIM# 113705) and BRCA2 (MIM# 600185) genes confer high risks of ovarian and breast cancer [Miki et al., 1994; Wooster et al., 1995]. Breast cancer risks by age 70 have been estimated to range between 40% and 87% for BRCA1 and 40–84% for BRCA2 mutation carriers, whereas ovarian cancer risk estimates range between 16–68% and 11–27% for BRCA1 and BRCA2 mutation carriers, respectively [Antoniou et al., 2003; Antoniou et al., 2008; Begg et al., 2008; Chen et al., 2006; Ford et al., 1998; Hopper et al., 1999; Milne et al., 2008; Simchoni et al., 2006; Struewing et al., 1997; Thompson et al., 2001; Thompson et al., 2002]. Recent genome-wide association studies (GWAS) have identified common alleles associated with risk of breast, ovarian, and other cancers [reviewed Easton and Eeles, 2008; McCarthy and Hirschhorn, 2008; Song et al., 2009]. These common variants are plausible candidates for modifiers of disease risk for mutation carriers. The Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) has provided convincing evidence that variants identified through GWAS of breast cancer are also associated with the risk of developing breast cancer for BRCA1 and/or BRCA2 mutation carriers [Antoniou et al., 2008a; Antoniou et al., 2009; Antoniou et al., 2010b; Antoniou et al., 2011].
Similarly, CIMBA has investigated the influence of ovarian cancer GWAS variants on ovarian cancer risk in BRCA1 and BRCA2 carriers. The first ovarian cancer susceptibility locus identified by a GWAS was rs3814113 at 9p22.2. The minor C allele was associated with a decreased risk of ovarian cancer (odds ratio (OR) = 0.82, 95% confidence interval (CI): 0.79–0.86, P = 5.1 × 10−19) [Song et al., 2009]. A previous CIMBA study showed that the minor allele of rs3814113 was also associated with a reduced risk of ovarian cancer for both BRCA1 and BRCA2 carriers (HR = 0.78 for both BRCA1 and BRCA2 mutation carriers) [Ramus et al., 2011].
A breast cancer GWAS in BRCA1 mutation carriers found that locus 19p13 is associated with breast cancer risk for BRCA1 mutation carriers. Two alleles on 19p13, rs8170C>T and rs2363956G>T, showed independent associations with breast cancer risk [Antoniou et al., 2010a]. Analysis of the associations of these SNPs with ovarian cancer risk in 843 ovarian cancer cases showed no evidence that this locus modifies ovarian cancer risk for BRCA1 mutation carriers. However, the same two alleles were identified at the same time as ovarian cancer susceptibility alleles in a population-based ovarian cancer GWAS - rs8170 (OR = 1.12, 95% CI: 1.07–1.17, P-trend = 3.6 × 10−6, serous OR = 1.18, 95% CI: 1.12–1.25, P-trend = 2.7 × 10−9) and rs2363956 (OR = 1.1, 95% CI: 1.06–1.15, P-trend = 1.2 ×10−7, serous OR = 1.16, 95% CI: 1.11–1.21, P-trend = 3.8 × 10−11) [Bolton et al., 2010]. Subsequent genotyping of SNPs rs8170 and rs67397200 (an SNP correlated with both rs8170 and rs2363956 and identified via imputation), in a larger series of BRCA1 and BRCA2 mutation carriers from CIMBA, confirmed that both SNPs are associated with breast cancer risk. This analysis, which included 1,399 BRCA1 ovarian cancer cases and 428 BRCA2 ovarian cancer cases, also found that the 19p13 SNPs were associated with ovarian cancer risk in both BRCA1 and BRCA2 carriers in an analysis of the simultaneous breast and ovarian cancer associations in BRCA1 carriers [Couch et al., in press].
Four additional ovarian cancer susceptibility loci were identified in a GWAS of more than 10,000 cases and 17,000 controls: rs2072590G>T (2q31) OR = 1.16 (95% CI: 1.12–1.21) P-trend = 4.5 × 10−14, rs2665390T>C (3q25) OR = 1.19 (95% CI: 1.11–1.27) P-trend = 3.2 × 10−7, rs10088218G>A (8q24) OR = 0.84 (95% CI: 0.80–0.89) P-trend = 3.2 × 10−9, and rs9303542A>G (17q21) OR = 1.11 (95% CI: 1.06–1.16) P-trend = 1.4 × 10−6 [Goode et al., 2010]. All these associations were stronger for serous ovarian cancer, the most common histology observed in BRCA-related ovarian cancer, than for all histologies. To investigate whether these SNPs are associated with risk of ovarian and breast cancer for mutation carriers, we genotyped these SNPs (or, in the case of rs2072590, a surrogate SNP, rs717852A>G, r2 = 0.96) for 12,599 BRCA1 and 7,132 BRCA2 mutation carriers from 40 studies that were part of CIMBA.
All subjects were female carriers of pathogenic mutations in BRCA1 or BRCA2 from 40 studies from Europe, North America, South Africa, and Australia (Supp. Table S1). Pathogenic mutations were defined as protein-truncating mutations or mutations listed on the Breast Cancer Information Core (BIC) http://research.nhgri.nih.gov/bic/ as described previously [Antoniou et al., 2007]. All subjects were 18 years or older at recruitment. The majority of carriers (>97%) were recruited through cancer genetics clinics offering genetic testing, and enrolled into national or regional studies. Some carriers were identified by population-based sampling of cases, and some by community recruitment. Only women of self-reported white, European ancestry were included in the analysis. Subjects were excluded if they were from a country other than the country in which the study is conducted, or if they carried mutations in both genes. If a woman was enrolled in two different studies, only one of the samples was included in the analysis. These duplicate samples were identified by dates of birth and diagnosis and from available genotyping data. Subject information included year of birth; age at last follow-up; ages at breast and/or ovarian cancer diagnosis; and age at bilateral prophylactic mastectomy or oophorectomy. Related subjects were identified through a unique family identifier. BRCA1 mutations were classified based on their predicted functional consequence. Class 1 was comprised of loss of function mutations subject to nonsense-mediated decay whereas class 2 mutations were those expected to generate a stable protein (details described previously [Antoniou et al., 2008a]). Subjects participated in clinical or research studies at the host institutions under ethically-approved protocols. Further details about CIMBA are described elsewhere [Chenevix-Trench et al., 2007].
The DNA samples from 12,599 BRCA1 and 7,132 BRCA2 carriers from 40 studies were genotyped for SNPs rs10088218 (8q24), rs2665390 (3q25), rs717852 (2q31), and rs9303542 (17q21) using the iPLEX (Sequenom, San Diego, CA) Mass Array platform (Supp. Table S1) at four genotyping centers. We used a correlated SNP (r2 = 0.96), rs717852, to replace a failed assay for rs2072590. All genotyping data were subjected to a standard set of quality control criteria. Samples from affected and unaffected subjects were randomly arrayed within plates. No template controls were included on every 384-well plate and at least 2% of the samples were tested in duplicate. Samples were excluded if they consistently failed genotyping, defined as a pass rate of < 80% for all SNPs in this genotyping round. For a study to be included in the analysis, the genotype data were required to attain or exceed a call-rate threshold of 95% and a concordance between duplicates of 98%. We also evaluated the deviation from Hardy-Weinberg equilibrium (HWE) for unrelated subjects. For none of these studies was HWE rejected at a predefined threshold of P = 0.001. An additional quality control criterion was consistent results for 95 DNA samples from a standard test plate (Coriell Institute, Camden, NJ) genotyped at all centers. If the genotyping was inconsistent for more than one sample in the test plate, the study was excluded. A total of 19,731 carriers with genotype data were eligible for inclusion in the analysis (12,599 BRCA1 and 7,132 BRCA2 carriers) (Supp. Table S1). Three studies failed quality control for rs717852 and one for rs2665390.
The primary aim of this study was to evaluate the association between each genotype and ovarian cancer risk. The primary endpoint was therefore the age at diagnosis of ovarian cancer. For this purpose, individuals were censored at the age of the ovarian cancer diagnosis, or risk-reducing salpingo-oophorectomy (RRSO) or the age at last observation. Breast cancer was not considered as a censoring event in this analysis, and mutation carriers who developed ovarian cancer after a breast cancer diagnosis were considered as affected in the ovarian cancer analysis. To address the fact that mutation carriers were not sampled at random with respect to their disease phenotype, analysis was conducted by modeling the retrospective likelihood of the observed genotypes conditional on the disease phenotypes as previously described [Antoniou et al., 2007; Barnes et al., In Press]. This method has been shown to provide unbiased estimates of the risk ratios within the present sampling frame [Barnes et al., In Press]. The effect of each SNP was modeled either as a per-allele hazard ratio (HR) (multiplicative model) or as separate HRs for heterozygotes and homozygotes, and these were estimated on the logarithmic scale. The HRs were assumed to be independent of age (i.e., we used a Cox proportional-hazards model). The assumption of proportional hazards was tested by adding a “genotype × age” interaction term to the model in order to fit models in which the HR changed with age. Analyses were carried out with the pedigree-analysis software MENDEL [Lange et al., 1988] and details of this approach have been described previously [Antoniou et al., 2007; Barnes et al., In Press]. We examined between study/country heterogeneity by comparing the models that allowed for study-specific log HRs against models in which the same log HR was assumed to apply to all studies.
To investigate whether our results were influenced by any of our assumptions, we performed additional sensitivity analyses. If any of the SNPs were associated with disease survival, the inclusion of prevalent cases may influence the HR estimates. We therefore repeated our analysis by excluding mutation carriers diagnosed more than 5 years prior to the age at recruitment into the study. We also examined whether SNP associations differed by type of BRCA1 mutations as described above.
The associations of these SNPs with breast cancer risk were assessed within a competing risk analysis framework [Barnes et al., In Press; Ramus et al., 2011] by estimating HRs simultaneously for breast and ovarian cancers. In this model, each individual was at risk of developing either breast or ovarian cancer, and the probabilities of developing each disease were assumed to be independent conditional on the underlying genotype. A different censoring process was used in this case, whereby individuals were followed up to the age of the first breast or ovarian cancer diagnosis and were considered to have developed the corresponding disease. No follow-up was considered after the first cancer diagnosis. Individuals were censored for breast cancer at the age of bilateral prophylactic mastectomy and for ovarian cancer at the age of bilateral oophorectomy and in such circumstances were assumed to be unaffected for the corresponding disease. The remaining individuals were censored at the age at last observation and were assumed to be unaffected for both diseases.
To ensure a sufficiently large number of mutation carriers within each stratum, we grouped studies from the same country. All analyses were stratified and used calendar year and cohort-specific cancer incidences for BRCA1 and BRCA2 [Antoniou et al., 2008b]. For sensitivity analyses, strata with small numbers of mutation carriers were grouped. We used a robust variance-estimation approach to allow for the nonindependence among related carriers [Boos, 1992].
In total, 12,599 BRCA1 and 7,132 BRCA2 carriers were eligible for analysis of associations between ovarian cancer risk and rs10088218 (8q24), rs2665390 (3q25), rs717852 (2q31), and rs9303542 (17q21). The primary analysis included 2,678 mutation carriers who were followed up to the age at diagnosis of invasive ovarian cancer (cases) and 17,053 carriers who were censored as unaffected (Table 1).
The minor allele of rs2665390 (3q25) was associated with a significantly increased risk of ovarian cancer for both BRCA1 carriers (per-allele HR = 1.25, 95% CI: 1.10–1.42, P-trend = 6.1 × 10−4)) and BRCA2 carriers (per allele HR = 1.48, 95% CI: 1.21–1.83, P-trend = 1.8 × 10−4) (Table 2). The minor allele of rs10088218 (8q24) was associated with a significantly decreased risk of ovarian cancer for both BRCA1 carriers (per-allele HR = 0.89, 95% CI: 0.81–0.99, P-trend = 0.029), and BRCA2 carriers (per allele HR = 0.81, 95% CI: 0.67–0.98, P-trend = 0.033). The two remaining SNPs, rs717852 (2q31) and rs9303542 (17q21), were associated with ovarian cancer risk for BRCA2 carriers (rs717852-per allele HR = 1.25, 95% CI: 1.10–1.42, P-trend = 6.6 × 10−4; rs9303542-per allele HR = 1.16, 95% CI: 1.02–1.33, P-trend = 0.026). The estimated HRs in BRCA1 carriers for these two SNPs were also >1 but not significantly different from 1, nor did they differ significantly from the HRs in BRCA2 carriers. There was no evidence that the HRs varied by age for either BRCA1 or BRCA2 mutation carriers (BRCA1-rs10088218 P = 0.34, rs2665390 P = 0.24, rs717852 P = 0.09, rs9303542 P = 0.58; BRCA2-rs10088218 P = 0.66, rs2665390 P = 0.95, rs717852 P = 0.88, rs9303542 P = 0.67). The country-specific HRs are shown in Figure 1. There was no evidence of heterogeneity in HRs across the studies/countries (BRCA1-rs10088218 P = 0.27, rs2665390 P = 0.59, rs717852 P = 0.60, rs9303542 P = 0.10; BRCA2 -rs10088218 P = 0.16, rs2665390 P = 0.32, rs717852 P = 0.75, rs9303542 P = 0.49).
To determine if any survival bias was introduced by including long-term survivors, we excluded all ovarian cancer cases recruited 5 or more years after diagnosis (Supp. Table S2). All HR estimates were similar to those from the primary analysis although only three were significant in the reduced sample set.
We examined the associations between the SNPs and ovarian cancer risk by the BRCA1 mutation-type based on the predicted functional consequence (Supp. Table S2). We found no evidence of a difference in the per-allele HR by BRCA1 mutation type for rs10088218 (8q24) (P for difference in HR = 0.99). For rs2665390 (3q25) the estimated HR for class 1 mutations was somewhat higher (per-allele HR = 1.34 [95% CI: 1.15-1.56] P-trend = 2.2 × 10−4) compared to class 2 mutations (HR = 1.08 (95% CI: 0.78–1.36), P-trend = 0.85), but the difference in HRs was not significant (P = 0.06). Similar patterns in the HRs between class 1 and class 2 mutations were seen for rs9303542 (17q21) and rs717852 (2q31), but none of the differences were significant (P = 0.20 and P = 0.36, respectively).
To determine whether these four SNPs were also associated with breast cancer risk for BRCA1 and BRCA2 mutation carriers, we performed an analysis in which we estimated HRs for breast and ovarian cancer simultaneously within a bivariate outcome model (Table 3). There was no evidence of association between these SNPs and breast cancer risk for mutation carriers. The estimated HRs for ovarian cancer risk under this analysis were similar to those estimated in the main analysis. However, some of the results were no longer significant due to the fact that mutation carriers diagnosed with ovarian cancer after a breast cancer diagnosis are censored at breast cancer, which results in a reduced number of ovarian cancer cases. The 3q25 SNP, rs2665390, was significantly associated with ovarian cancer risk for both BRCA1 and BRCA2 carriers (per-allele HR = 1.23, 95% CI: 1.06-1.44, P-trend = 8.5 × 10−3 and per-allele HR = 1.59, 95% CI: 1.25–2.02, P-trend = 1.9 × 10−4, respectively). As in the primary analysis, rs717852 (2q31) was only associated with an increased ovarian cancer risk in BRCA2 carriers (HR = 1.31, 95% CI: 1.12–1.53, P-trend = 8.5 × 10−4). The magnitude of the association between SNP rs10088218 (8q24) and ovarian cancer risk in BRCA2 carriers was somewhat larger than in the primary analysis (HR = 0.72, 95% CI: 0.57–0.91, P-trend = 5.7 × 10−3).
Recent studies have shown that common genetic variants identified from ovarian cancer GWAS are associated with susceptibility to ovarian cancer for BRCA1 and/or BRCA2 mutation carriers [Couch et al., in press; Ramus et al., 2011]. In the present study, we genotyped four SNPs, rs10088218 (8q24), rs2665390 (3q25), rs717852 (2q31), and rs9303542 (17q21) that were found to be associated with ovarian cancer in women from the general population. We found that all SNPs were associated with ovarian cancer risk for BRCA2 mutation carriers. There was significant evidence that two of the SNPs (rs10088218 at 8q24 and rs2665390 at 3q25) were also associated with ovarian cancer risk for BRCA1 mutation carriers. For the remaining two SNPs at 2q31 and 17q21, the associations with ovarian cancer risk in BRCA1 mutations did not reach statistical significance. However, the estimated HRs were still consistent with both the estimated HRs in BRCA2 carriers, and the estimated ORs in the general population. Thus these data, combined with those for the previously detected ovarian cancer risk SNPs at 9p22.2 [Ramus et al., 2011] and 19p13 [Couch et al, in press], indicate that all six known common susceptibility loci for ovarian cancer, are also associated with the ovarian cancer risk in BRCA1 and BRCA2 carriers, and moreover that the relative risk of ovarian cancer is generally similar to that in the general population.
In the general population, the magnitude of the associations with ovarian cancer risk were stronger for cases with the serous histological subtype for rs2072590 (2q31) Pheterogeneity = 2.9 × 10−4, rs10088218 (8q24) Pheterogeneity = 1.1 × 10−7, and rs2665390 (3q25) Pheterogeneity = 0.02 [Goode et al., 2010]. However, we were not able to assess this interaction in the BRCA1 and BRCA2 carriers, due to small numbers and incomplete pathology data for histological subtype.
When the data were analyzed within a competing risks framework, we observed no evidence that these SNPs were associated with breast cancer risk for BRCA1 or BRCA2 mutation carriers. None of the published breast cancer GWAS using women from the general population [Ahmed et al., 2009; Easton et al., 2007; Gold et al., 2008; Hunter et al., 2007; Thomas et al., 2009] have reported associations for these SNPs at the strict genome-wide levels of significance. These results indicate that, for both groups of mutation carriers and for the general population, the predominant association is with ovarian cancer risk and that the association with breast cancer risk, if any, is very weak.
The fine-mapping and functional follow-up of the risk alleles from the ovarian cancer GWAS are currently being performed. Therefore, the gene most likely to be driving the ovarian cancer risk in each region has not yet been identified but the closest genes to each SNP and the genes in the linkage disequilibrium block provide some insight to the potential candidates. The rs2665390 SNP is located at 3q25, and is intronic to the TIPARP gene, a member of the poly (ADP-ribose) polymerase (PARP) superfamily. BRCA1-BRCA2–deficient cells can use the PARP1 alternative DNA repair mechanism to survive, and synthetic inhibition of PARP1 has been developed as a new therapy for breast and ovarian cancer patients with mutations in these genes [Fong et al., 2009]. There are no other candidate genes within 200 kb of this SNP and the five other genes within the linkage disequilibrium block (LEKR1, LOC730091, PA2G4P4, SSR3, and KCNAB1) are not known to have functions that suggest a role in cancer [www.genecards.org; Safran et al., 2010].
The rs717852 SNP is located at 2q31 in a region containing a family of homeobox (HOX) genes; HOXD10, HOXD11, HOXD12, HOXD13, HOXD3, HOXD4, HOXD8, HOXD9, and HOXD1. HOX genes are involved in regulating embryogenesis and organogenesis and altered expression of HOX genes has been reported in many cancers [Buzzai and Licht, 2008; Shiraishi et al., 2002.]. The other genes in this region, KIAA1715, EVX2, and MTX2, do not have a reported role in cancer [www.genecards.org; Safran et al., 2010]. The ovarian cancer risk-associated SNP rs2072590 is downstream of HOXD3 and upstream of HOXD1, and it tags SNPs in the HOXD3 3′ untranslated region. The genotyped SNP rs717852 is intronic of HOXD3.
Common variants that confer susceptibility to multiple cancer phenotypes, including prostate, colorectal, breast, and bladder cancers have been identified in a 500-kb region of a gene desert at 8q24, approximately 200 kb 5′ of MYC [Jia et al., 2009]. Functional studies have suggested that transcriptional regulation of MYC may explain these associations [Jia et al., 2009; Pomerantz et al., 2009]. In contrast, rs10088218 is >700 kb 3′ of MYC. Variants in this region may also be capable of distant regulation of MYC. However, PVT1, a noncoding RNA which is an MYC protein target, is another plausible candidate in this region. PVT1 is amplified in breast and ovarian tumors, and is overexpressed in transformed cells [Guan et al., 2007]. A prostate cancer risk variant at the 8q24 locus, located 0.5 Mb upstream of the PVT1 gene has recently been shown to be associated with increased expression of the PVT1 gene rather than affecting MYC expression [Meyer et al., 2011].
The final SNP, rs9303542 at 17q21, is intronic to SKAP1, a src kinase-associated phosphoprotein, which regulates mitotic progression [Fang et al., 2009]. SKAP1 has been shown to suppress activation of RAS and RAF1 genes that may have a role in the early-stage development of ovarian cancer [Kosco et al., 2008]. The region also contains 10 HOXB genes and, as described earlier, altered expression of HOX genes has been reported in many cancers. Of the other 12 genes in this region, the only ones with a suggested role in cancer are, PRAC, encoding a small nuclear protein which is a prostate cancer susceptibility candidate, CBX1, which may play an important role in the epigenetic control of chromatin structure and gene expression, and CDK5RAP3 that may be involved in cell proliferation [www.genecards.org; Safran et al., 2010].
We have previously demonstrated that common risk alleles for breast cancer increase the risk of breast cancer to a similar relative extent in BRCA1 and BRCA2 carriers (once estrogen receptor status is taken into account). These results demonstrate that the same holds true for ovarian cancer loci identified through GWAS, and provides a general model in which common susceptibility loci and BRCA1 and BRCA2 mutations interact multiplicatively on the risk of developing ovarian cancer [Wacholder et al., 2011]. Although the HR conferred by each locus is modest, the HRs are much larger in combination. These translate to small differences in absolute risk between different genotypes for the vast majority of women at low risk of this disease, but the absolute risk differences for mutation carriers will be much greater. As more genetic modifiers of ovarian cancer risk are identified, in the future, such information combined with other risk factors such as parity and oral contraceptive use could be incorporated into risk prediction algorithms such as BOADICEA [Antoniou et al., 2008b]. This could enable the stratification of mutation carriers into different ovarian cancer risk categories and could potentially be used for guiding the clinical management of mutation carriers with respect to screening or prophylactic surgery.
This work was supported by Cancer Research UK grants C12292/A11174 and C1287/A10118, NHMRC grants to GCT, and grants from the NIH (CA128978), and the U.S. Department of Defense Ovarian Cancer Idea award (W81XWH-10-1-0341) to FJC. The research leading to these results has received funding from the European Community’s Seventh Framework Programme No. 223175 (HEALTH-F2-2009-223175); European Community’s Seventh Framework Programme under grant agreement No. 223175 (HEALTH-F2-2009-223175). ACA is a CR-UK Senior Cancer Research Fellow, DFE is CR-UK Principal Research Fellow, GCT is a NHMRC Senior Principal Research Fellow and JS is Chairholder of the Canada Research Chair in Oncogenetics. This work was supported by the Canadian Institutes of Health Research for the “CIHR Team in Familial Risks of Breast Cancer” program (grant number CRN_87521); and the Canadian Breast Cancer Research Alliance (grant number 019511)
Breast Cancer Family Registry (BCFR): was supported by the National Cancer Institute, National Institutes of Health under RFA-CA-06-503 and through cooperative agreements with members of the Breast Cancer Family Registry and Principal Investigators, including Cancer Care Ontario (U01 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), and Research Triangle Institute Informatics Support Center (RFP No. N02PC45022-46). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the BCFR, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the BCFR.
BRCA-gene mutations and breast cancer in South African women (BMBSA): was supported by grants from the Cancer Association of South Africa (CANSA) to Elizabeth J. van Rensburg.
Copenhagen Breast Cancer Study (CBCS): was supported by the Neye Foundation.
Spanish National Cancer Center (CNIO). This study was partially supported by Fundación Mutua Madrileña, Asociación Española Contra el Cáncer, the Spanish Minestry of Science and Innovation FIS PI08/1120 and Cancer Network RD06/0020/1060. Funded in part by the Basque Foundation for Health Innovation and Research (BIOEF: BIO07/CA/006).
CONsorzio Studi Italiani Tumori Ereditari Alla Mammella (CONSIT TEAM) was supported by grants from Associazione Italiana per la Ricerca sul Cancro (4017) and by funds from Italian citizens who allocated the 5 × 1,000 share of their tax payment in support of the Fondazione IR-CCS Istituto Nazionale Tumori, according to Italian laws (INT-Institutional strategic projects “5 × 1,000”) to PP. Supported by grants from Ministero della Salute (“Progetto Tevere”—Linea 1 RC D/08/02B—“Progetto Tumori Femminili”—F/08/0PZ—Linea1 RC CORR/08) to SM. Supported by grants from Associazione Italiana per la Ricerca sul Cancro (8713) to LO. Supported by grants from Fondazione Italiana per la Ricerca sul Cancro (Special Project “Hereditary tumors”), Ministero della Salute (RFPS-2006-3-340203, Extraordinary National Cancer Program 2006 “Alleanza contro il Cancro”, and “Progetto Tumori Femminili”) and Ministero dell’Universita’ e Ricerca (RBLAO3-BETH) to PR.
Deutsches Krebsforschungszentrum (DKFZ) study: was supported by the DKFZ.
Epidemiological study of BRCA1 & BRCA2 mutation carriers (EMBRACE) was supported by Cancer Research UK Grants (C1287/A10118 and C1287/A11990). D. Gareth Evans and Fiona Lalloo 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. Ros Eeles, Elizabeth Bancroft, and Lucia D’Mello were also supported by Cancer Research UK Grant (C5047/A8385).
Fox Chase Cancer Center (FCCC): was supported by the National Institutes of Health (U01 CA69631, 5U01 CA113916, R01 CA140323 to A.K.G.); the Ovarian Cancer Research Fund, and the Eileen Stein Jacoby Fund. The author acknowledges support from The University of Kansas Cancer Center and the Kansas Bioscience Authority Eminent Scholar Program. A.K.G. is the Chancellors Distinguished Chair in Biomedical Sciences endowed Professor. The German Consortium of Hereditary Breast and Ovarian Cancer (GC-HBOC): was supported by a grant of the German Cancer Aid (grant 109076) and by the Centre of Molecular Medicine Cologne (CMMC).
Genetic Modifiers of cancer risk in BRCA1/2 mutation carriers (GEMO) study (Cancer Genetics Network “Groupe Génétique et Cancer”, Fédération Nationale des Centres de Lutte Contre le Cancer, France) was supported by the Ligue National Contre le Cancer; Association for International Cancer Research Grant (AICR-07-0454); and the Association “Le cancer du sein, parlons-en!” Award.
Georgetown. CI received support from the Familial Cancer Registry at Georgetown University (NIH/NCI grant P30-CA051008), the Cancer Genetics Network (HHSN261200744000C), and Swing For the Cure.
Gynecologic Oncology Group (GOG): KAP is the Cancer Council Victoria, Colebatch Clinical Research Fellow.
The Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON). The HEBON study is supported by the Dutch Cancer Society grants NKI1998-1854, NKI2004-3088, NKI2007-3756 and the ZonMW grant 91109024.
Hospital Clinico San Carlos (HCSC): was supported by The National Institute of Health Carlos III (RTICC 06/0020/0021).
Helsinki Breast Cancer Study (HEBCS): was supported by the Helsinki University Central Hospital Research Fund, Academy of Finland (132473), the Finnish Cancer Society, and the Sigrid Juselius Foundation.
The Hong Kong Hereditary Breast Cancer Family Registry (HRBCP): thanks the Dr. Ellen Li Charitable Foundation and Kuok Foundation for grant support.
Hungarian Breast and Ovarian Cancer Study (HUNBOCS) was supported by Hungarian Research Grant KTIA-OTKA CK-80745 to Edith Olah.
International Hereditary Cancer Center (IHCC): was supported by the State Committee for Scientific Research (PBZ_KBN_122/P05/2004). Katarzyna Jaworska is a fellow of International PhD program, Postgraduate School of Molecular Medicine, Warsaw Medical University, supported by the Polish Foundation of Science.
Iceland Landspitali-University Hospital (ILUH): The ILUH group was supported by a grant from the Icelandic Association “Walking for Breast Cancer Research” and by the Landspitali University Hospital Research Fund.
Istituto Oncologico Veneto Hereditary Breast and Ovarian Cancer Study (IOVHBOCS) was supported by Ministero dell’Istruzione, dell’Università e della Ricerca (MIUR), and “Ministero della Salute” (“Progetto Tumori Femminili and grant numbersRFPS 2006-5-341353, ACC2/R6.9”).
Kathleen Cuningham Consortium for Research into Familial Breast Cancer (KCONFAB) was 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. ABS is a Senior Research Fellow of the NHMRC.
The research of the MAGIC consortium at the University of Pennsylvania was funded by RO1-CA083855 and RO1-CA102776 to TRR.
Mayo Clinic Study (MAYO) was supported by the National Institutes of Health (R01 CA128978 and P50 CA116201); the Komen race for the cure (KG081527); the Breast Cancer Research Foundation and the U.S. Department of Defense Ovarian Cancer Idea award (W81XWH-10-1-0341).
Memorial Sloane Kettering Cancer Center (MSKCC) was supported by the Breast Cancer Research Foundation and the Lomangino Family Research Fund.
National Cancer Institute (NCI): was supported by the Intramural Research Program of the US National Cancer Institute at the National Institutes of Health, and by support services contracts NO2-CP-11019-50 and N02-CP-65504 with Westat, Inc, Rockville, MD to PLM and MHG.
N.N. Petrov Institute of Oncology (NNPIO): was supported by the Russian Foundation for Basic Research (grant numbers 10-04-92601, 10-04-92110, 11-04-00227), the Federal Agency for Science and Innovations (contract 16.512.11.2237), the Commission of the European Communities (grant number PITN-GA-2009-238132), and through a Royal Society International Joint grant (JP090615).
Ontario Cancer Genetics Network (OCGN): was supported by Cancer Care Ontario, Canada (ILA); and the National Cancer Institute, National Institutes of Health under RFA-CA-06-503 and through cooperative agreements with members of the Breast Cancer Family Registry and PIs. The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in the CFR, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or the CFR.
The Ohio State University Clinical Cancer Genetics (OSUCCG): was supported by the Ohio State University Comprehensive Cancer Center.
Pisa Breast Cancer Study (PBCS): was supported by Fondazione Cassa di Risparmio di Pisa Grant n.122/07 and grant 2010 from ITT (Istituto Toscano Tumori).
Swedish Breast Cancer Study (SWE-BRCA): was supported by the Swedish Cancer Society.
Beckman Research Institute City of Hope (BRICOH) was supported by the National Institutes of Health (R01 CA74415 to SLN and YCD) University of California, Los Angeles (UCLA) was supported by funding from the Jonsson Comprehensive Cancer Center Foundation.
University of California San Francisco (UCSF): was supported by the Clinical and Translational Science Institute at the University of California, San Francisco (to MSB).
UK and Gilda Radner Familial Ovarian Cancer Registries (UKGRFOCR): UKFOCR was supported by a project grant from CRUK to PP. We would like to acknowledge the Roswell Park Alliance Foundation for their continued support of the Gilda Radner Ovarian Family Cancer Registry.
University of Pennsylvania (UPENN) was supported by Breast Cancer Research Foundation (BRCF) to KLN and Komen Foundation for the Cure to SMD.
Women’s Cancer Program (WCP): was supported in part by the American Cancer Society Early Detection Professorship (SIOP-06-258-01-COUN).
Breast Cancer Family Registry (BCFR): Samples from the FCCC, HCI, and NCCC were processed and distributed by the Coriell Institute for Medical Research.
Baltic Familial Breast Ovarian Cancer Consortium (BFBOCC): A special acknowledgement for Laima Tihomirova (Latvian Biomedical Research and Study Center, Riga, Latvia) for providing samples and data for joint Lithuanian-Latvian BFBOCC study.
Spanish National Cancer Center (CNIO) and the Spanish Consortium: thanks R.M. Alonso, G. Pita, and R.M. Milne for their assistance. We also thank IBGM-CSIC, Universidad de Valladolid, and Junta de Castilla y León. CONsorzio Studi Italiani Tumori Ereditari Alla Mammella (CONSIT TEAM): thanks Gaia Roversi, Elisa Cattaneo, and Marco A. Pierotti of the Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy; Monica Barile of the Istituto Europeo di Oncologia, Milan, Italy and the personnel of the Cancer Genetic Testing laboratory at the IFOM-IEO Campus, Milan, Italy. Epidemiological study of BRCA1 & BRCA2 mutation carriers (EMBRACE): Douglas F. Easton is the PI of the study. EMBRACE Collaborating Centers are: Coordinating Centre, Cambridge: Susan Peock, Debra Frost, Steve D. Ellis, Elena Fineberg, Radka Platte. North of Scotland Regional Genetics Service, Aberdeen: Zosia Miedzybrodzka, Helen Gregory. Northern Ireland Regional Genetics Service, Belfast: Patrick Morrison, Lisa Jeffers. West Midlands Regional Clinical Genetics Service, Birmingham: Trevor Cole, Kai-ren Ong, Jonathan Hoffman. South West Regional Genetics Service, Bristol: Alan Donaldson, Margaret James. East Anglian Regional Genetics Service, Cambridge: Joan Paterson, Sarah Downing, Amy Taylor. Medical Genetics Services for Wales, Cardiff: Alexandra Murray, Mark T. Rogers, Emma McCann. St James’s Hospital, Dublin & National Centre for Medical Genetics, Dublin: M. John Kennedy, David Barton. South East of Scotland Regional Genetics Service, Edinburgh: Mary Porteous, Sarah Drummond. Peninsula Clinical Genetics Service, Exeter: Carole Brewer, Emma Kivuva, Anne Searle, Selina Goodman, Kathryn Hill. West of Scotland Regional Genetics Service, Glasgow: Rosemarie Davidson, Victoria Murday, Nicola Bradshaw, Lesley Snadden, Mark Longmuir, Catherine Watt, Sarah Gibson, Eshika Haque, Ed Tobias, Alexis Duncan. South East Thames Regional Genetics Service, Guy’s Hospital London: Louise Izatt, Chris Jacobs, Caroline Langman, Anna Whaite. North West Thames Regional Genetics Service, Harrow: Huw Dorkins. Leicestershire Clinical Genetics Service, Leicester: Julian Barwell. Yorkshire Regional Genetics Service, Leeds: Julian Adlard, Gemma Serra-Feliu. Cheshire & Merseyside Clinical Genetics Service, Liverpool: Ian Ellis, Catherine Houghton. Manchester Regional Genetics Service, Manchester: D Gareth Evans, Fiona Lalloo, Jane Taylor. North East Thames Regional Genetics Service, NE Thames, London: Lucy Side, Alison Male, Cheryl Berlin. Nottingham Centre for Medical Genetics, Nottingham: Jacqueline Eason, Rebecca Collier. Northern Clinical Genetics Service, New-castle: Fiona Douglas, Oonagh Claber, Irene Jobson. Oxford Regional Genetics Service, Oxford: Lisa Walker, Diane McLeod, Dorothy Halliday, Sarah Durell, Barbara Stayner. The Institute of Cancer Research and Royal Marsden NHS Foundation Trust: Ros Eeles, Susan Shanley, Nazneen Rahman, Richard Houlston, Elizabeth Bancroft, Lucia D’Mello, Elizabeth Page, Audrey Ardern-Jones, Kelly Kohut, Jennifer Wiggins, Elena Castro, Anita Mitra, Lisa Robertson. North Trent Clinical Genetics Service, Sheffield: Jackie Cook, Oliver Quarrell, Cathryn Bardsley. South West Thames Regional Genetics Service, London: Shirley Hodgson, Sheila Goff, Glen Brice, Lizzie Winchester, Charlotte Eddy, Vishakha Tripathi, Virginia Attard. Wessex Clinical Genetics Service, Princess Anne Hospital, Southampton: Diana Eccles, An-neke Lucassen, Gillian Crawford, Donna McBride, Sarah Smalley.
Fox Chase Cancer Center (FCCC): thanks Ms. JoEllen Weaver and Dr. Betsy Bove for their technical support.
The German Consortium of Hereditary Breast and Ovarian Cancer (GC-HBOC): thanks all the families for providing samples for this study and the German Cancer Aid for establishing the GC-HBOC and their longstanding patronage.
Genetic Modifiers of Cancer Risk in BRCA1/2 Mutation Carriers (GEMO): thanks all the GEMO collaborating groups for their contribution to this study. GEMO Collaborating Centers are: Coordinating Centers, Unité Mixte de Génétique Constitutionnelle des Cancers Fréquents, Centre Hospitalier Universitaire de Lyon / Centre Léon Bérard,& Equipe Génétique du cancer du sein, Centre de Recherche en Cancérologie de Lyon: Olga Sinilnikova, Sylvie Mazoyer, Laure Barjhoux, Carole Verny-Pierre, Sophie Giraud, Mélanie Léone; and Service de Génétique Oncologique, Institut Curie, Paris: Dominique Stoppa-Lyonnet, Marion Gauthier-Villars, Bruno Buecher, Claude Houdayer, Virginie Moncoutier, Muriel Belotti, Carole Tirapo, Antoine de Pauw. Institut Gustave Roussy, Villejuif: Brigitte Bressac-de-Paillerets, Audrey Remenieras, Véronique Byrde, Olivier Caron, Gilbert Lenoir. Centre Jean Perrin, Clermont–Ferrand: Yves-Jean Bignon, Nancy Uhrhammer. Centre Léon Bérard, Lyon: Christine Lasset, Valérie Bonadona. Centre François Baclesse, Caen: Agnès Hardouin, Pascaline Berthet. Institut Paoli Calmettes, Marseille: Hagay Sobol, Violaine Bourdon, Tetsuro Noguchi, François Eisinger. Groupe Hospitalier Pitié-Salpétrière, Paris: Florence Coulet, Chrystelle Colas, Florent Soubrier. CHU de Arnaud-de-Villeneuve, Montpellier: Isabelle Coupier, Pascal Pujol. Centre Oscar Lambret, Lille: Jean-Philippe Peyrat, Joëlle Fournier, Françoise Révillion, Philippe Vennin, Claude Adenis. Hôpital René Huguenin/Institut Curie, St Cloud: Etienne Rouleau, Rosette Lidereau, Liliane Demange, Catherine Nogues. Centre Paul Strauss, strasbourg: Danièle Muller, Jean-Pierre Fricker. Institut Bergonié, Bordeaux: Emmanuelle Barouk-Simonet, Françoise Bonnet, Virginie Bubien, Nicolas Sevenet, Michel Longy. Institut Claudius Regaud, toulouse: Christine Toulas, Rosine Guimbaud, Laurence Gladieff, Viviane Feillel. CHU de Grenoble: Dominique Leroux, Hélène Dreyfus, Christine Rebischung, Magalie Peysselon. CHU de Dijon: Fanny Coron, Laurence Faivre. CHU de St-Etienne: Fabienne Prieur, Marine Lebrun, Caroline Kientz. Hôtel Dieu Centre Hospitalier, Chambéry: Sandra Fert Ferrer. Centre Antoine Lacassagne, Nice: Marc Frénay.CHU de Limoges: Laurence Vénat-Bouvet. CHU de Nantes: Capucine Delnatte. CHU Bretonneau, Tours: Isabelle Mortemousque. Creighton University, Omaha, USA: Henry T.Lynch, Carrie L.Snyder.
Gynecologic Oncology Group (GOG): We thank the investigators of the Australia New Zealand Gynaecological Oncology Group (ANZGOG).
Helsinki Breast Cancer Study (HEBCS): thanks Dr. Carl Blomqvist, Tuomas Heikkinen, and Taru Muranen for their help with the patient data and samples.
The Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON): HEBON Collaborating Centers: Coordinating center: Netherlands Cancer Institute, Amsterdam, NL: F.B.L. Hogervorst, S. Verhoef, M. Verheus, L.J. van ‘t Veer, F.E. van Leeuwen, M.A. Rookus; Erasmus Medical Center, Rotterdam, NL: M. Collée, A.M.W. van den Ouweland, A. Jager, M.J. Hooning, M.M.A. Tilanus-Linthorst, C. Seynaeve; Leiden University Medical Center, NL, Leiden: C.J. van Asperen, J.T. Wijnen, M.P. Vreeswijk, R.A. Tollenaar, P. Devilee; Radboud University Nijmegen Medical Center, Nijmegen, NL: M.J. Ligtenberg, N. Hoogerbrugge; University Medical Center Utrecht, Utrecht, NL: M.G. Ausems, R.B. van der Luijt; Amsterdam Medical Center, NL: C.M. Aalfs, T.A. van Os; VU University Medical Center, Amsterdam, NL: J.J.P. Gille, Q. Waisfisz, H.E.J. Meijers-Heijboer; University Hospital Maastricht, Maastricht, NL: E.B. Gomez-Garcia, C.E. van Roozendaal, Marinus J. Blok, B. Caanen; University Medical Center Groningen University, NL: J.C. Oosterwijk, A.H. van der Hout, M.J. Mourits; The Netherlands Foundation for the detection of hereditary tumours, Leiden, NL: H.F. Vasen.
The Hong Kong Hereditary Breast Cancer Family Registry (HRBCP) wish to thank the Hong Kong Sanatorium and Hospital Molecular Pathology Laboratory staff for their technical support and the nurses, research assistants, doctors, and genetic counselors who have assisted in patient recruitment.
Interdisciplinary Health Research International Team Breast Cancer Susceptibility (INHERIT BRCAs): We would like to thank Stéphane Dubois, Dr Martine Dumont, Martine Tranchant (Cancer Genomics Laboratory, CRCHUQ) for sample management and skillful technical assistance, Sylvie Desjardins and Marc-André Rodrigue (Plateforme de séquençage et de génotypage des génome du CRCHUL/CHUQ) for iPLEX genotyping and Pascal Belleau for data quality control analyses.
Kathleen Cuningham Foundation Consortium for Research into Familial Breast Cancer (KCONFAB): thanks 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 2001–2009 by NHMRC and currently by the National Breast Cancer Foundation and Cancer Australia #628333) for their contributions to this resource, and the many families who contribute to kConFab.
Memorial Sloan-Kettering Cancer Center (MSKCC): On behalf of the MSKCC study, we acknowledge the Starr Cancer Consortium, the Breast Cancer Research Foundation, the Norman and Carol Stone Cancer Research Initiative, the Kate and Robert Niehaus Clinical Cancer Research Initiative, the Lymphoma Foundation, and the Sabin Family Research Initiative.
Ontario Cancer Genetics Network (OCGN): thanks Mona Gill, Lucine Collins, Nalan Gokgoz, Teresa Selander, Nayana Weerasooriya, and members of the Ontario Cancer Genetics Network for their contributions to the study. The Ohio State University Clinical Cancer Genetics (OSUCCG): thanks the Human Cancer Genetics Sample bank for sample preparation and Leigha Senter and Kevin Sweet for ascertainment of study participants and collection of phenotype data.
Swedish Breast Cancer Study (SWE-BRCA): SWE-BRCA collaborators: Per Karlsson, Margareta Nordling, Annika Bergman, and Zakaria Einbeigi, Gothenburg, Sahlgrenska University Hospital; Marie Stenmark-Askmalm and Sigrun Liedgren, Linköping University Hospital; Åke Borg, Niklas Loman, Håkan Olsson, Maria Soller, Helena Jernström, Katja Harbst and Karin Henriksson, Lund University Hospital; Annika Lindblom, Brita Arver, Anna von Wachenfeldt, Annelie Liljegren, Gisela Barbany-Bustinza and Johanna Rantala, Stockholm, Karolinska University Hospital; Beatrice Melin, Henrik Grönberg, Eva-Lena Stattin and Monica Emanuelsson, Umeå University Hospital; Hans Ehrencrona, Richard Rosenquist, and Niklas Dahl, Uppsala University Hospital.
Beckman Research Institute of City of Hope was supported by the National Institutes of Health (R01 CA74415 to SLN)) and the Morris and Horowitz Families Endowment.
University of California, Los Angeles (UCLA): thanks Ms. Joyce Seldon for her genetic counselling services, and Ms. Lorna Kwan for database management.
University of California San Francisco (UCSF): thanks Ms. Salina Chan for her database support and management and to Ms. Beth Crawford for her genetic counseling services.
UK and Gilda Radner Familial Ovarian Cancer Registries (UKGRFOCR): UKFOCR thanks Carole Pye, Patricia Harrington and Eva Wozniak for family recruitment and technical support. GRFOCR would like to acknowledge Lara Sucheston (Department of Cancer Prevention and Control) and Kunle Odunsi (Departments Gynecologic Oncology and Immunology).
ACA is a CR-UK Senior Cancer Research Fellow, DFE is CR-UK Principal Research Fellow, GCT is a NHMRC Senior Principal Research Fellow and. JS is Chairholder of the Canada Research Chair in Oncogenetics.
Additional Supporting Information may be found in the online version of this article.