Germline Mutations in the BRIP1, BARD1, PALB2, and NBN Genes in Women With Ovarian Cancer

BACKGROUND: Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy, responsible for 13 000 deaths per year in the United States. Risk prediction based on identifying germline mutations in ovarian cancer susceptibility genes could have a clinically significant impact on reducing disease mortality. METHODS: Next generation sequencing was used to identify germline mutations in the coding regions of four candidate susceptibility genes-BRIP1, BARD1, PALB2 and NBN-in 3236 invasive EOC case patients and 3431 control patients of European origin, and in 2000 unaffected high-risk women from a clinical screening trial of ovarian cancer (UKFOCSS). For each gene, we estimated the prevalence and EOC risks and evaluated associations between germline variant status and clinical and epidemiological risk factor information. All statistical tests were two-sided. RESULTS: We found an increased frequency of deleterious mutations in BRIP1 in case patients (0.9%) and in the UKFOCSS participants (0.6%) compared with control patients (0.09%) (P = 1 x 10(-4) and 8 x 10(-4), respectively), but no differences for BARD1 (P = .39), NBN1 ( P = .61), or PALB2 (P = .08). There was also a difference in the frequency of rare missense variants in BRIP1 between case patients and control patients (P = 5.5 x 10(-4)). The relative risks associated with BRIP1 mutations were 11.22 for invasive EOC (95% confidence interval CI = 3.22 to 34.10, P = 1 x 10(-4)) and 14.09 for high-grade serous disease (95% CI = 4.04 to 45.02, P = 2 x 10(-5)). Segregation analysis in families estimated the average relative risks in BRIP1 mutation carriers compared with the general population to be 3.41 (95% CI = 2.12 to 5.54, P = 7×10(-7)). CONCLUSIONS: Deleterious germline mutations in BRIP1 are associated with a moderate increase in EOC risk. These data have clinical implications for risk prediction and prevention approaches for ovarian cancer and emphasize the critical need for risk estimates based on very large sample sizes before genes of moderate penetrance have clinical utility in cancer prevention.