ABSTRACT
We evaluated homologous recombination deficient (HRD) phenotypes in epithelial ovarian cancer (EOC) considering BRCA1, BRCA2, and RAD51C in a large well-annotated patient set. We evaluated EOC patients for germline deleterious mutations (n = 899), somatic mutations (n = 279) and epigenetic alterations (n = 482) in these genes using NGS and genome-wide methylation arrays. Deleterious germline mutations were identified in 32 (3.6%) patients for BRCA1, in 28 (3.1%) for BRCA2 and in 26 (2.9%) for RAD51C. Ten somatically sequenced patients had deleterious alterations, six (2.1%) in BRCA1 and four (1.4%) in BRCA2. Fifty two patients (10.8%) had methylated BRCA1 or RAD51C. HRD patients with germline or somatic alterations in any gene were more likely to be high grade serous, have an earlier diagnosis age and have ovarian and/or breast cancer family history. The HRD phenotype was most common in high grade serous EOC. Identification of EOC patients with an HRD phenotype may help tailor specific therapies.
Subject(s)
BRCA1 Protein/genetics , BRCA2 Protein/genetics , DNA-Binding Proteins/genetics , Neoplasms, Glandular and Epithelial/genetics , Ovarian Neoplasms/genetics , Base Sequence , Carcinoma, Ovarian Epithelial , DNA Methylation/genetics , Female , Homologous Recombination/genetics , Humans , Middle Aged , Mutation , Neoplasms, Glandular and Epithelial/classification , Neoplasms, Glandular and Epithelial/mortality , Ovarian Neoplasms/classification , Ovarian Neoplasms/mortality , Sequence Analysis, DNAABSTRACT
Several genes conferring susceptibility to breast and ovarian cancer, notably BRCA1 and BRCA2, have been identified. The majority of the familial aggregation of breast cancer is, however, not explained by these genes. We have previously derived, using segregation analysis, a susceptibility model (BOADICEA, Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm) in which susceptibility to these genes is explained by mutations in BRCA1 and BRCA2 together with a polygenic component reflecting the joint multiplicative effect of multiple genes of small effect on breast cancer risk. Here, we consider the predictions made by this model. The overall familial risks of breast cancer predicted by this model are close to those observed in epidemiological studies. The predicted prevalences of BRCA1 and BRCA2 mutations among unselected cases of breast and ovarian cancer are also consistent with observations from population-based studies. These predictions are closer to the observed values than those obtained using the Claus model and BRCAPRO. The predicted mutation probabilities and cancer risks in individuals with a family history (FH) can differ markedly from those predicted by other models. We conclude that this model provides a rational basis for risk assessment in individuals with a FH of breast or ovarian cancer.