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. Author manuscript; available in PMC: 2013 Jul 30.
Published in final edited form as: JAMA. 2012 Jan 25;307(4):382–390. doi: 10.1001/jama.2012.20

Association Between BRCA1 and BRCA2 Mutations and Survival in Women with Invasive Epithelial Ovarian Cancer

Kelly L Bolton 1,2, Georgia Chenevix-Trench 3, Cindy Goh 4, Siegal Sadetzki 5,6, Susan J Ramus 7, Beth Y Karlan 8, Diether Lambrechts 9, Evelyn Despierre 10, Daniel Barrowdale 11, Lesley McGuffog 11, Sue Healey 3, Douglas F Easton 11, Olga Sinilnikova 12,13, Javier Benitez 14,15, María J García 15,16, Susan Neuhausen 17, Mitchell H Gail 1, Patricia Hartge 1; EMBRACE study team11, Susan Peock 11, Debra Frost 11, D Gareth Evans 18, Ros Eeles 19, Andrew K Godwin 20, Mary B Daly 21, Ava Kwong 22,23, Edmond SK Ma 22,24, Conxi Lázaro 25, Ignacio Blanco 25, Marco Montagna 26, Emma D’Andrea 27,28, Ornella Nicoletto 29, kConFab Investigators 30, Sharon E Johnatty 3, Susanne Krüger Kjær 31,32, Allan Jensen 31,32, Estrid Høgdall 31,32, Ellen L Goode 33, Brooke L Fridley 33, Jennifer T Loud 34, Mark H Greene 34, Phuong L Mai 34, Angela Chetrit 5, Flora Lubin 35, Galit Hirsh-Yechezkel 5, Gord Glendon 36, Irene L Andrulis 36,37, Amanda E Toland 38, Leigha Senter 39, Martin E Gore 40, Charlie Gourley 41, Caroline O Michie 41, Honglin Song 42, Jonathan Tyrer 42, Alice S Whittemore 43, Valerie McGuire 43, Weiva Sieh 43, Ulf Kristoffersson 44, Håkan Olsson 45, Åke Borg 45, Douglas A Levine 46; Cancer Genome Atlas Research Network47, Linda Steele 17, Mary S Beattie 48,49, Salina Chan 48, Robert Nussbaum 48,49, Kirsten B Moysich 50, Jenny Gross 8, Ilana Cass 8, Christine Walsh 8, Andrew J Li 8, Ronald Leuchter 8, Ora Gordon 8, Montserrat Garcia-Closas 51, Simon A Gayther 7, Stephen J Chanock 1, Antonis C Antoniou 11, Paul DP Pharoah 42
PMCID: PMC3727895  NIHMSID: NIHMS449532  PMID: 22274685

Abstract

Context

Approximately 10 percent of women with invasive epithelial ovarian cancer (EOC) carry deleterious germline mutations in BRCA1 or BRCA2. A recent report suggested that BRCA2 related EOC was associated with an improved prognosis, but the effect of BRCA1 remains unclear.

Objective

To characterize the survival of BRCA carriers with EOC compared to non-carriers and to determine whether BRCA1 and BRCA2 carriers show similar survival patterns.

Design, Setting, and Participants

We pooled data from 26 studies on the survival of women with ovarian cancer. This included data on 1,213 EOC cases with pathogenic germline mutations in BRCA1 (909) or BRCA2 (304) and 2,666 non-carriers recruited and followed for variable times between 1987 and 2010; the median year of diagnosis was 1998.

Main Outcome Measures

Five year overall mortality.

Results

The five-year overall survival was 36 percent (95% CI: 34–38) for non-carriers, 44 percent (95% CI: 40–48) for BRCA1 carriers and 52 percent (95% CI: 46–58) for BRCA2 carriers. After adjusting for study and year of diagnosis, BRCA1 and BRCA2 carriers showed a more favorable survival than non-carriers (BRCA1, HR=0.78; 95% CI=0.68–0.89, P=2×10−4; BRCA2, HR = 0.61; 95% CI=0.50–0.76, P=6×10−6). These survival differences remained after additional adjustment for stage, grade, histology and age at diagnosis (BRCA1, HR=0.73, 95% CI=0.64–0.84, P=2×10−5; BRCA2, HR = 0.49, 95% CI=0.39–0.61, P=3×10−10).

Conclusions

Among patients with invasive epithelial ovarian cancer, having a germline mutation in BRCA1 or BRCA2 was associated with improved 5-year overall survival.

Introduction

Germline mutations in the genes BRCA1 and BRCA2 are the strongest known genetic risk factors for both breast and epithelial ovarian cancer (EOC) and are found in 6–15 percent of women with EOC1–3. BRCA1 is involved in DNA repair, cell-cycle checkpoint control, chromatin remodeling, transcriptional regulation and mitosis and BRCA2 has an important role in homologous recombination 4. The clinical characteristics of EOCs among BRCA1/2 carriers differ from that of non-carriers. BRCA1 related disease is more likely to be of serous histology5, high grade6 and advanced stage3. Less data are available for BRCA2-related EOC due to their lower prevalence and lower EOC penetrance relative to BRCA1 but a similar pattern is generally reported5;7.

The relative prognosis of BRCA1/2 carriers and non-carriers is unclear. A recent report found a more favorable outcome for BRCA2 mutation carriers, with no significant difference in outcome for BRCA1 mutation carriers compared to non-carriers8. However, some studies have demonstrated a more favorable prognosis for BRCA1 and BRCA2 carriers6;7;9 compared to non-carriers whereas others have reported no significant difference10;11. Several factors may account for these divergent results. Most studies contained fewer than 50 carriers and all contained fewer than 250 carriers resulting in imprecise survival estimates. Small sample sizes have also resulted in the grouping of BRCA1 and BRCA2 carriers together for analysis, despite potential prognostic differences. In addition, adjustment for prognostic factors known to differ by carrier status has varied among studies. Finally, few studies employed appropriate statistical methods to account for the potential bias that results from the inclusion of prevalent cases12. The mechanism driving the association between BRCA1/2 mutations and survival is not known but some retrospective studies suggested that the survival advantage of carriers could be mediated through improved response to platinum-based agents7;13. This is consistent with in vitro studies showing that BRCA1 and BRCA2 deficient cells are hypersensitive to drugs which induce double strand DNA breaks such as platinum-based agents14.

The aim of this study was to collate the data from multiple EOC case series with data on BRCA1 and BRCA2 mutation status in order to provide definitive evidence of the relative effect of germline BRCA1 and BRCA2 mutations on prognosis. The results could provide insight into the biology of BRCA1/2 mutations, improve clinical management of mutation carriers and have implications for clinical trial design, particularly for agents targeting BRCA1/2 dysfunction such as poly (ADP-ribose)-polymerase (PARP) inhibitors15.

Methods

Study Design

Study participants were women with confirmed invasive EOC both with and without pathogenic mutations in BRCA1 and BRCA2. Participants were drawn from 26 studies: 10 from the USA, six from Europe, two from Israel, one from Hong Kong, one from Canada, one from Australia and five from the UK. Participants were enrolled in clinical research protocols between 1987 and 2010 that were approved by local institutional review boards. Written consent was obtained from all living patients. Most participating studies were affiliated with either the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA)16 or the Ovarian Cancer Association Consortium (OCAC)17. Investigators submitted data on patient demographics, tumor pathology, vital status and treatment to the coordinating group in Cambridge. In some studies, EOC cases were recruited based on a strong family history of ovarian and/or breast cancer (family-based), while others used population-based sampling or enrolled a consecutive series of cases treated at a single or multiple institution(s). In all studies, BRCA1/2 carriers and non-carriers were enrolled into the study using the same criteria.

Mutations were considered pathogenic if they met criteria defined by the Breast Cancer Information Core18;19 and were grouped into categories based on their predicted functional effect20–23. Women with variants of unknown significance in BRCA1 or BRCA2 were excluded. Class I mutations are the most frequent and represent loss-of-function mutations predicted to result in reduced transcript or protein level due to mRNA nonsense-mediated RNA decay, translational retention or absence of expression. Class II contains those mutations likely to generate stable proteins that may have some normal or dominant negative function. This includes missense substitutions and mutations generating a premature stop codon in the last exon. All participants were screened for both BRCA1 and BRCA2 mutations with three exceptions. In three family-based studies, the Kathleen Cuningham Consortium for Research into Familial Breast Cancer, the UK Gilda Radner Familial Ovarian Cancer Registries and the National Cancer Institute study, some EOC cases were not tested for BRCA1/2 and BRCA1/2 status was assumed to be same as that of affected family member(s) who had been tested. The non-carrier group from the RMH study contained some untested EOC cases but who reported no family history of breast or ovarian cancer and were therefore considered unlikely to harbor mutations. Finally, in the Stanford Genetic Epidemiology of Ovarian Cancer study, only BRCA1 mutation testing was performed. A variety of methods were used to perform mutation testing (eTable 1).

Data on tumor pathology, vital status and treatment were obtained through a combination of medical records, local cancer registries and death certificates. Infrequently, vital status was determined through direct contact with a physician or family member of the patient. In a subset of studies, information regarding residual disease following primary surgery was available from medical records. Optimal debulking was defined as residual disease =<1cm and suboptimal debulking as residual disease > 1cm.

BRCA1/2 status may modify response to platinum based chemotherapy which became standard of care in most countries around 1990. Among the 36 percent of subjects with chemotherapy data, 95 percent of cases diagnosed after 1990 were reported to have received a platinum-based agent. We therefore excluded women diagnosed before 1990 if chemotherapy regime was unknown, and those known not to have received platinum based chemotherapy.

Statistical Analysis

The primary endpoint was overall survival (OS) up to five years following EOC diagnosis. We chose this endpoint in order to minimize the influence of non-EOC related deaths. Time-to-event (death or censoring) was calculated from the date of diagnosis. However, cases were recruited at variable times after diagnosis and so time under observation was calculated from date of recruitment (left truncation) in order to prevent the bias that could result from the inclusion of prevalent cases. Effect estimates from left-truncated data are considered to be unbiased if the event time and delayed entry time are independent, given the covariates24. Differences in tumor stage, grade, histology and age at diagnosis between BRCA1, BRCA2 and non-carriers were tested using logistic regression adjusted for study site. We used Cox proportional-hazards models to estimate hazard ratios (HR) and 95 percent confidence intervals (CI). All models were adjusted for year of EOC diagnosis (<1990, 1990–1995, 1996–2000, 2000–2010) and stratified by study site. In stratified survival analyses, strata with small numbers of deaths can lead to unreliable estimates. For this reason, four studies with less than 30 cases were placed in the same strata as other studies sharing similar study designs and baseline survival rates.

We performed analyses with and without adjustment for stage, grade, histology and age at diagnosis. The proportional hazards assumption was tested for each covariate analytically using Schoenfeld residuals. Age at diagnosis and histology violated the PH assumption so additional covariates were included to allow for time-dependent effects

Differences in the HR estimates for the survival impact of BRCA1 and BRCA2 by different clinical factors were tested using Cochrane’s chi-square test (Q-test) for heterogeneity. To assess the impact of possible competing mortality from breast cancer on effect estimates, we compared analyses restricted to women with and without a diagnosis of breast cancer before or in the five years following EOC diagnosis. We tested for heterogeneity by study in the HR estimates through the inclusion of an interaction term between study and BRCA1/2 mutation status.

Some participants were missing data for stage (19%), grade (22%) and histology (5%). In order to decrease potential bias and loss of power due to missingness, we performed multiple imputation for these three variables (eMethods). All analyses, except for comparison of pathological characteristics and Kaplan Meier estimation of survival, were performed on the imputed data. The results using non-imputed data were similar to those presented here using imputed data; for comparison, the main results using non-imputed data are presented in eTable 2. All analyses were performed using STATA/SE version 11 (StataCorp, College Station, TX, USA). Statistical significance was defined as a P value of less than 0.05. Statistical tests were two sided.

Results

Data were available for 3,879 EOC cases; 909 BRCA1 and 304 BRCA2 mutation carriers and 2,666 non-carriers. The median number of months from ascertainment to diagnosis for participants was 1 month (25th–75th percentile: 0–15 months). Women were under active follow-up for a median time of 38 months (25th–75th percentile: 18–77 months). The proportion of cases with censored survival time (not followed to death or 5 years after diagnosis) was 15 percent. After controlling for study site, there was no significant difference in the proportion of cases with censored survival time among BRCA1 (p=0.22) or BRCA2 (p=0.41) carriers compared to non-carriers. The median year of diagnosis was 1998 (range: 1981–2010). During the five years following EOC diagnosis, 1,766 deaths occurred. We found several significant differences in the clinical features of BRCA1 and BRCA2 carriers compared to non-carriers (Table 1). Tumors in BRCA1 and BRCA2 carriers were more likely to be of serous histology and less likely to be of mucinous histology than tumors in non-carriers. BRCA1 and BRCA2 carriers were more likely to have stage III/IV tumors and poorly differentiated/undifferentiated tumors than non-carriers. Compared to BRCA1 carriers, BRCA2 carriers were more likely to have stage III/IV tumors. While BRCA1 carriers were younger at diagnosis than non-carriers, BRCA2 carriers were slightly older.

Table 1.

Characteristics of 4,284 study participants by BRCA1/2 germline mutation status

Characteristics Non-carriers (n=2666) BRCA1 (n=909) BRCA2 (n=304) P (BRCA1 vs BRCA2 carriers)
No. No. P (BRCA1 vs non-carriers) No. P (BRCA2 vs non-carriers)
Months from Diagnosis to Study Entry:
Median (25–75%)		 0.5 (0–13) 2 (0–18) 2 (0–17)
Months of Follow-up:
Median (25–75%)		 38 (18–83) 35 (18–66) 39 (21–75)
Year of EOC Diagnosis:
Median (Max-Min)		 1998 (1981–2009) 1998 (1986–2010) 1999 (1986–2009)
Deaths within 5 years of EOC diagnosis 1249 409 108
Histology
 Serous 1769(67) 617(74) 1×10−3 213(80) 2×10−3 0.20
 Mucinous 214(8) 7(1) 3×10−5 0(0) 0.02 0.33
 Endometroid 324(12) 105(13) 0.85 24(9) 0.39 0.16
 Clear Cell 119(4) 15(2) 0.13 6(2) 0.14 0.42
 Other 45(2) 10(1) - 5(2) -
 Carcinoma, NOS 187(7) 80(10) - 18(7) -
 Missing* 8(0.3) 75(8) - 38(13) -
Grade 9×10−7 6×10−4 0.37
 Well differentiated 298(13) 18(3) 8(4)
 Poorly differentiated 543(24) 129(19) 28(13)
 Un-differentiated 1382(62) 533(78) 184(84)
 Missing* 443(17) 229(25) 84(28)
Stage (FIGO) 0.03 7×10−3 0.02
 I 501(21.0) 84(12.3) 22(9.5)
 II 213(8.9) 71(10.4) 13(5.6)
 III 1286(54.0) 436(64.0) 170(73.3)
 IV 382(16.0) 90(13.2) 27(11.6)
 Missing* 284(11) 228(25) 72(24)
Age at EOC Diagnosis:
Mean (SD)		 58(12) 52(10) 8×10−18 60(11) 0.04 1×10−17
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*

The proportion of tumors in various categories of a variable was calculated among subjects with non-missing data for that variable

The five-year overall survival was 36 percent (95% CI: 34–38) for non-carriers, 44 percent (95% CI: 40–48) for BRCA1 carriers and 52 percent (95% CI: 46–58) for BRCA2 carriers (Figure 1 and eFigure 1). In a Cox regression model only adjusted for study and year of diagnosis, BRCA1 carriers showed a more favorable survival than non-carriers (HR=0.78; 95% CI=0.68–0.89; P=2×10−4) (Table 2). This improved slightly after additional adjustment for stage, grade, histology and age at diagnosis (HR=0.73; 95% CI=0.64–0.84; P=2×10−5). BRCA2 carriers showed a greater survival advantage compared to non-carriers (HR = 0.61; 95% CI=0.50–0.76, P=6×10−6), particularly after adjusting for other prognostic factors (HR = 0.49; 95% CI=0.39–0.61, P=3×10−10). The BRCA1 HR estimates were significantly different from the BRCA2 HR estimates in unadjusted (Phet=0.05) and adjusted models (Phet=0.003).

Figure 1. Kaplan Meier Estimates of Cumulative Survival According to BRCA1/2 status.

Figure 1

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Caption: Kaplan Meier analysis was adjusted for year of diagnosis and study.

Table 2.

Proportional hazards regression models for impact of BRCA status on all-cause mortality using imputed data.

Comparison Groups Unadjusteda
Adjustedb
#Carriers (deaths) #Ref (deaths) HR (95% CI) P-value #Carriers (deaths) #Ref (deaths) HR (95% CI) P-value
BRCA1 vs Non-Carriers (ref) 909 (409) 2666 (1249) 0.78 (0.68–0.89) 2.3×10−4 909 (409) 2666 (1249) 0.73 (0.64–0.84) 1.6×10−5
BRCA2 vs Non-Carriers (ref) 304 (108) 2666 (1249) 0.61 (0.50–0.76) 5.8×10−6 304 (108) 2666 (1249) 0.49 (0.39–0.61) 2.7×10−10
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a

Model was stratified by study site, and adjusted for year of ovarian cancer diagnosis.

b

Model was stratified by study site and tumor stage, and ajusted for year of ovarian cancer diagnosis, grade, histology and age at ovarian cancer diagnsois.

We studied the impact of BRCA1/2 mutation status on all-cause mortality after stratifying patients by other clinical features (Table 3). In analyses stratified by grade and adjusted for other prognostic factors the HRs were >1 for both BRCA1 vs. non-carriers and BRCA2 vs. non-carriers in low grade cases but <1 in high grade cases. There were no significant differences in the HRs for BRCA1 vs. non-carriers or BRCA2 vs. non-carriers when stratified according to tumor stage, histology or history of breast cancer before or during the study period. The survival advantage of BRCA1 and BRCA2 carriers compared to non-carriers was found to be attenuated in women with ovarian cancer selected based on family history of ovarian and/or breast cancer (Table 4). However, the difference in survival between BRCA1 and BRCA2 carriers did not depend on ascertainment (HR for BRCA2 vs. BRCA1: 0.71, 95% CI=0.52–0.98 and 0.64, 95% CI=0.45–0.91 for familial and unselected cases respectively; Phet=0.65). There was no evidence of study-specific heterogeneity in the HR estimates for mutation status among family-based studies (BRCA1, p=0.22; BRCA2, p=0.92) or unselected studies (BRCA1, p=0.73; BRCA2, p=0.57).

Table 3.

Impact of BRCA1/2 mutations on all-cause mortality in adjusted models stratified by selected subgroups.

Subgroups BRCA1 vs Non-carriers
BRCA2 vs Non-carriers
#Carriers (deaths) #Ref (deaths) HR (95% CI) P P-het #Carriers (deaths) #Ref (deaths) HR (95% CI) P P-het
Stage
 Localized (I/II) 208 (51) 856 (130) 0.85 (0.53–1.37) 0.51 0.53 55 (11) 856 (130) 0.65 (0.53–1.37) 0.31 0.51
 Advanced (III/IV) 701 (358) 1810 (1119) 0.73 (0.63–0.84) 2×10−5 249 (97) 1810 (1119) 0.49 (0.39–0.61) 5×10−10
Grade
 Well differentiated 28 (11) 364 (82) 2.66 (0.86–8.17) 0.09 0.02 8 (5) 364 (82) 3.86 (0.59–25.15) 0.16 0.03
 Pooly/Un-differentiated 881 (398) 2302 (1167) 0.71 (0.61–0.82) 3×10−5 296 (103) 2302 (1167) 0.47 (0.38–0.59) 8×10−10
Histology
 Non-serousa 127 (5) 657 (184) 0.68 (0.45–1.04) 0.07 0.76b 30 (11) 657 (184) 0.70 (0.36–1.37) 0.30 0.19b
 Serous 617 (286) 1769 (939) 0.73 (0.62–0.86) 2×10−4 213 (74) 1769 (939) 0.43 (0.33–0.56) 3×10−10
 High grade serous 598 (278) 1602 (887) 0.72 (0.61–0.85) 8×10−5 206 (69) 1602 (887) 0.41 (0.31–0.53) 1×10−10
Breast Cancer before or during study peroid
 No 551 (273) 1171 (683) 0.86 (0.72–1.02) 0.08 0.75 165 (73) 1171 (683) 0.62 (0.47–0.82) 3×10−4 0.61
 Yes 214 (89) 61 (25) 0.77 (0.41–1.45) 0.42 75 (21) 61 (25) 0.50 (0.24–1.07) 0.08
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a

Includes tumors of mucinous, clear cell and endometroid histology

b

test for heterogeneity is for differences between non-serous and serous subtypes

Table 4.

Proportional hazards regression for impact of BRCA status on all-cause mortality by study type.

Subgroup #Carriers (deaths) #Ref (deaths) HR (95% CI) P-value
Main effect Heterogeneity
BRCA1 vs Non-Carriers (ref)
Selected for Family History 556 (254) 283 (126) 1.03 (0.79–1.35) 0.83 0.002
Unselected for Family History 353 (155) 2383 (1123) 0.62 (0.52–0.75) 2.4×10−7
BRCA2 vs Non-Carriers (ref)
Selected for Family History 179 (63) 283 (126) 0.71 (0.49–1.03) 0.07 0.04
Unselected for Family History 125 (45) 2383 (1123) 0.43 (0.32–0.58) 5.0×10−8
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Models were stratified by study site and tumor stage, and ajusted for year of ovarian cancer diagnosis, grade, histology and age at ovarian cancer diagnsois

The proportion of mutation carriers with the Ashkenazi Jewish founder mutations 185delAG and 5382insC in BRCA1 and 6174delT in BRCA2 was 26 percent. We did not find any significant differences in the adjusted HRs for BRCA1 vs. non-carriers among carriers by mutation type (Class I vs. Class II mutation Phet=0.10). However, the survival advantage of BRCA1 mutation carriers with Class I mutations differed depending on mutation location; worse survival was associated with mutations on the 5′ end compared to the 3′ end of BRCA1 (P=0.03) (eMethods and eTable 3).

A subset of 1129 patients had information on residual disease following primary surgery. We assessed the impact of lack of adjustment for these variables in our main analysis by comparing results with and without adjustment for residual disease in this subgroup. Optimal debulking occurred in 85% of non-carriers, 87% of BRCA1 carriers and 91% of BRCA2 carriers. After adjusting for study site and year of diagnosis, there was no significant difference in the likelihood of optimal debulking between non-carriers and BRCA1 (p=0.74) or BRCA2 (p=0.46) carriers. Adjustment for residual disease did not substantially change the HR estimates for the relative survival of either BRCA1 or BRCA2 carriers compared to non-carriers (eTable 4).

Discussion

Our data demonstrate an improved survival in EOC patients with germline BRCA1 and BRCA2 mutations relative to non-carriers, with BRCA2 carriers having the best prognosis. BRCA1 carriers presented with EOC at an earlier age than BRCA2 carriers which is consistent with the age-specific penetrances for BRCA1 compared to BRCA2 carriers. The pathological characteristics of BRCA1 and BRCA2 related tumors are similar to each other, but differ from those of tumors in non-carriers. This contrasts with breast cancer, in which substantial differences between BRCA1 and BRCA2-associated disease are present25;26. The differences in grade, stage and histology by mutation status are consistent with previously reported data5;27. The impact of BRCA1 and BRCA2 mutations on survival appeared to be similar among patients with both localized and advanced stage tumors and among both serous and non-serous tumors. The lack of a survival advantage for BRCA1 and BRCA2 mutation carriers with low grade disease suggests that disruptions of the BRCA1/2 pathways may not be as important in the etiology of these tumors, supporting evidence of etiologic heterogeneity between high grade and low grade serous carcinoma from other studies28;29. However, these results were based on small numbers and require confirmation in larger studies.

Our findings confirm the findings of recent analysis of data from the Cancer Genome Atlas (TCGA) project which reported an improved prognosis for BRCA2 carriers8. In contrast we also found an improved prognosis for BRCA1 carriers, whereas the TCGA data suggested no difference between BRCA1 carriers and non-carriers. The most likely reason for this difference is the lack of power to detect a moderate difference in survival in the TCGA data. Indeed, the hazard ratio for BRCA1 carriers compared to non-carriers reported by Yang and colleagues (multivariate adjusted HR=0.76) was very similar to that from our analysis (multivariate adjusted HR=0.73).

We found a smaller survival effect of BRCA1 and BRCA2 in the subset of studies where participants selected based on a strong family history of ovarian and/or breast cancer. This could have been due to misclassification of non-carriers in these studies. The sensitivity of mutation testing is likely to be similar across all studies but the proportion of false negative carriers will be higher in familial cases. Alternatively, cases from BRCA1/2 wild-type families could carry germline mutations in genes in the same pathway as BRCA1/2 (such as RAD51C30) or in different pathways that produce similar clinical features.

The improved survival of BRCA1/2 carriers relative to non-carriers, and the survival advantage of BRCA2 carriers relative to BRCA1 carriers could be related to intrinsic biological differences, their response to therapeutic agents or both. In addition to differences in stage, grade and histology, BRCA1/2 carriers could have differences in other aspects of tumor biology that were not measured in the current study. For example, BRCA1 and BRCA2 carriers have been recently shown to differ from each other and from sporadic EOC in the incidence of visceral metastasis31.

The most notable advantage as well as disadvantage of our study is the fact that it is based on a heterogeneous population; these data were taken from studies containing different ethnic groups, employing different mutation screening methodologies and case ascertainment. By including a wide variety of studies, we were able to generate a large enough sample size to adequately address the issue of heterogeneity of the survival effect between BRCA1 and BRCA2 carriers. But, differences in study design and population may limit the specificity of the conclusions drawn. Additionally, varying levels of misclassification of BRCA status and other variables of interest may have led to some bias of our estimates towards the null. However, the absence of heterogeneity in study-specific effects (after accounting for selection on family history) suggests that these results are generalizable to many populations. Furthermore, the magnitude of the differences we observed between BRCA1, BRCA2 carriers and non-carriers, despite the presence of heterogeneity, provide further testament to their robustness. Even at the lower bounds of our effect estimates, BRCA2 carriers would be predicted to show a 64% decreased risk of death in the five years following diagnosis compared to non- carriers.

Our findings could have relevance to an even higher proportion of EOC patients if somatic mutations and epigenetic silencing of BRCA1 and BRCA2 show similar effects on prognosis to germline mutations. It has been estimated that roughly 30% of EOC and over half of high-grade serous EOC could show dysfunction of BRCA1 or BRCA2 through genetic or epigenetic events32;33. There is evidence that EOC cases with somatic BRCA1/2 mutations show a survival advantage over non-carriers33, but data from The Cancer Genome Atlas and others suggest that silencing of BRCA1 through promoter methylation does not result in an improved OS34;35. Larger studies that include comprehensive genomic screening of BRCA1 and BRCA2 in primary EOCs will be needed determine if alterations at the somatic and epigenetic level have similar clinical effects to germline mutations.

The results of this study have potentially important implications for the clinical management of patients with EOC. Most immediately, our findings can be used by health care professions for patient counseling regarding expected survival. BRCA1 and BRCA2 carriers with EOC respond better than non carriers to platinum based chemotherapies, and have improved survival despite the fact that the disease is generally diagnosed at a later stage and higher grade. If patients could be stratified based on their BRCA status, their treatment could be tailored to reflect this, with non-carriers targeted for more aggressive treatments. Our data provide further support that there may be different functional mechanisms involved in the etiology of different subtypes of EOCs, and therefore different therapeutic targets based on germline and somatic genetic variation. For example, the functional characterization of BRCA1 and BRCA2 led to the development of a novel therapy in BRCA1/2 carriers based on inhibition of the poly (ADP-ribose) polymerase (PARP) DNA repair pathway, creating a synthetic lethal phenotype. Recently, phase I and II trials have shown anti-tumor activity of the PARP inhibitor Olparib in BRCA1/2 mutation carriers with EOC15;36;37. These trials were not large enough to detect differences in response to Olparib in BRCA1 vs. BRCA2 carriers and it is not known whether they will show similar levels of response. EOC clinical trials should be stratified by BRCA status not only to more appropriately target therapy but also to avoid the potential bias introduced by unequal numbers of carriers in treatment arms or between study cohorts. Furthermore, given the important prognostic information provided by BRCA1 and BRCA2 status and the potential for personalized treatment in carriers, the routine testing of women presenting with high-grade serous EOC may now be warranted.

Supplementary Material

Supplementary information

Table 5.

Number at risk by carrier status for Figure 1

Years Non-carriers BRCA1 BRCA2
0 1047 327 117
1 1687 593 199
2 1540 569 192
3 1395 490 179
4 1225 408 164
5 1044 342 125
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Acknowledgments

We thank all the patients and families who took part in the component studies and the many individuals who have made these studies possible. In particular we thank John Stratton, PhD and Vickie Basham, BA for their help in collecting and managing data from the UK Gilda Radner Familial Ovarian Cancer Registry study. We thank Heather Thorne, BSci, Professional Diploma in Clinical Research and Eveline Niedermayr, B.Sc, G.Dip. Information Management, G.Dip. Software Development for their help in collecting and managing data for the Kathleen Cuningham Consortium for Research into Familial Breast Cancer study. None of the individuals acknowledged here received specific compensation for their role in this article.

The contributing studies are supported by Cancer Research UK (C490/A10119, C490/A10124, C1287/A10118, C1287/A11990, C5047/A8385), the Edinburgh Experimental Cancer Medicine Centre, the European Community’s Seventh Framework Programme (n° 223175, HEALTH-F2-2009-223175), the Fondo de Investigación Sanitaria (PS09/01094 & PI081120), the Fundación Mutua Madrileña (AP-8101-2010), the Melville Trust for the Care and Cure of Cancer, the National Institutes of Health (CA74415, R01-CA 61107, R01 CA-122443, P50 CA136393, P01 CA 130818, 2P50 CA 058207 and the Intramural Research Program of the NCI, DCEG), the Nationaal Kankerplan - Actie 29′ of Belgium, the NHMRC of Australia, the National Breast Cancer Foundation of Australia, Cancer Australia (#628333), the Queensland Cancer Fund, the Cancer Councils of New South Wales, Victoria, Tasmania and South Australia, the Cancer Foundation of Western Australia, the Scottish Funding Council, the Scottish Chief Scientist’s Office, the Manchester NIHR Biomedical Research Centre, Minnesota Ovarian Cancer Alliance, Fred C. and Katherine B. Andersen Foundation, Mermaid 1 project, the Danish Cancer Society, Ministero dell’Istruzione, dell’Università e della Ricerca and Ministero della Salute (“Progetto Tumori Femminili” and RFPS 2006-5-341353, ACC2/R6.9”), the Helen Diller Family Comprehensive Cancer Center at UCSF, the Avon Foundation, The Hong Kong Hereditary Breast Cancer Family Registry and the Dr. Ellen Li Charitable Foundation and Service Grants through the National Cancer Institute (NO2-CP-11019-50 and N02-CP-65504 with Westat, Inc, Rockville, MD), Asociación Española Contra el Cáncer, Spanish Health Research Fund; Carlos III Health Institute; Catalan Health Institute and Autonomous Government of Catalonia, Contract grant numbers (ISCIIIRETIC RD06/0020/1051, PI10/01422, PI10/31488 and 2009SGR290). B.Y.K is supported by funding from the American Cancer Society Clinical Research Professorship (#SIOP-06-258-06-COUN). M.J.G. is the recipient of a Miguel Servet contract from the Instituto de Salud Carlos III, A.C.A is a Cancer Research UK Senior Cancer Research Fellow.

Role of Sponsors

None of the sponsors described above had any role in the design or conduct of the study; the collection, analysis, and interpretation of the data; or the preparation, review, or approval of the manuscript.

Footnotes

Access to data

Kelly Leigh Bolton had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

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