ABSTRACT
PURPOSE: Integration of gene panels in the diagnosis of hereditary breast and ovarian cancer (HBOC) requires a careful evaluation of the risk associated with pathogenic or likely pathogenic variants (PVs) detected in each gene. Here we analyzed 34 genes in 5131 suspected HBOC index cases by next-generation sequencing. METHODS: Using the Exome Aggregation Consortium data sets plus 571 individuals from the French Exome Project, we simulated the probability that an individual from the Exome Aggregation Consortium carries a PV and compared it to the estimated frequency within the HBOC population. RESULTS: Odds ratio conferred by PVs within BRCA1, BRCA2, PALB2, RAD51C, RAD51D, ATM, BRIP1, CHEK2, and MSH6 were estimated at 13.22 [10.01-17.22], 8.61 [6.78-10.82], 8.22 [4.91-13.05], 4.54 [2.55-7.48], 5.23 [1.46-13.17], 3.20 [2.14-4.53], 2.49 [1.42-3.97], 1.67 [1.18-2.27], and 2.50 [1.12-4.67], respectively. PVs within RAD51C, RAD51D, and BRIP1 were associated with ovarian cancer family history (OR = 11.36 [5.78-19.59], 12.44 [2.94-33.30] and 3.82 [1.66-7.11]). PALB2 PVs were associated with bilateral breast cancer (OR = 16.17 [5.48-34.10]) and BARD1 PVs with triple-negative breast cancer (OR = 11.27 [3.37-25.01]). Burden tests performed in both patients and the French Exome Project population confirmed the association of PVs of BRCA1, BRCA2, PALB2, and RAD51C with HBOC. CONCLUSION: Our results validate the integration of PALB2, RAD51C, and RAD51D in the diagnosis of HBOC and suggest that the other genes are involved in an oligogenic determinism.
Subject(s)
DNA-Binding Proteins/genetics , Fanconi Anemia Complementation Group N Protein/genetics , Hereditary Breast and Ovarian Cancer Syndrome/genetics , Adult , BRCA1 Protein/genetics , BRCA2 Protein/genetics , France/epidemiology , Genetic Predisposition to Disease , Genetic Testing , Genetic Variation/genetics , Hereditary Breast and Ovarian Cancer Syndrome/diagnosis , Hereditary Breast and Ovarian Cancer Syndrome/epidemiology , Hereditary Breast and Ovarian Cancer Syndrome/pathology , High-Throughput Nucleotide Sequencing , Humans , Middle Aged , Neoplasm Proteins/genetics , Risk Factors , Exome SequencingABSTRACT
Highlighting tumoral mutations is a key step in oncology for personalizing care. Considering the genetic heterogeneity in a tumor, software used for detecting mutations should clearly distinguish real tumor events of interest that could be predictive markers for personalized medicine from false positives. OutLyzer is a new variant-caller designed for the specific and sensitive detection of mutations for research and diagnostic purposes. It is based on statistic and local evaluation of sequencing background noise to highlight potential true positive variants. 130 previously genotyped patients were sequenced after enrichment by capturing the exons of 22 genes. Sequencing data were analyzed by HaplotypeCaller, LofreqStar, Varscan2 and OutLyzer. OutLyzer had the best sensitivity and specificity with a fixed limit of detection for all tools of 1% for SNVs and 2% for Indels. OutLyzer is a useful tool for detecting mutations of interest in tumors including low allele-frequency mutations, and could be adopted in standard practice for delivering targeted therapies in cancer treatment.
