Germline mutation in the RAD51B gene confers predisposition to breast cancer.

International audienceBACKGROUND: Most currently known breast cancer predisposition genes play a role in DNA repair by homologous recombination. Recent studies conducted on RAD51 paralogs, involved in the same DNA repair pathway, have identified rare germline mutations conferring breast and/or ovarian cancer predisposition in the RAD51C, RAD51D and XRCC2 genes. The present study analysed the five RAD51 paralogs (RAD51B, RAD51C, RAD51D, XRCC2, XRCC3) to estimate their contribution to breast and ovarian cancer predisposition. METHODS: The study was conducted on 142 unrelated patients with breast and/or ovarian cancer either with early onset or with a breast/ovarian cancer family history. Patients were referred to a French family cancer clinic and had been previously tested negative for a BRCA1/2 mutation. Coding sequences of the five genes were analysed by EMMA (Enhanced Mismatch Mutation Analysis). Detected variants were characterized by Sanger sequencing analysis. RESULTS: Three splicing mutations and two likely deleterious missense variants were identified: RAD51B c.452 + 3A > G, RAD51C c.706-2A > G, RAD51C c.1026 + 5_1026 + 7del, RAD51B c.475C > T/p.Arg159Cys and XRCC3 c.448C > T/p.Arg150Cys. No RAD51D and XRCC2 gene mutations were detected. These mutations and variants were detected in families with both breast and ovarian cancers, except for the RAD51B c.475C > T/p.Arg159Cys variant that occurred in a family with 3 breast cancer cases. CONCLUSIONS: This study identified the first RAD51B mutation in a breast and ovarian cancer family and is the first report of XRCC3 mutation analysis in breast and ovarian cancer. It confirms that RAD51 paralog mutations confer breast and ovarian cancer predisposition and are rare events. In view of the low frequency of RAD51 paralog mutations, international collaboration of family cancer clinics will be required to more accurately estimate their penetrance and establish clinical guidelines in carrier individuals

Effect of BRCA2 sequence variants predicted to disrupt exonic splice enhancers on BRCA2 transcripts

Background: Genetic screening of breast cancer patients and their families have identified a number of variants of unknown clinical significance in the breast cancer susceptibility genes, BRCA1 and BRCA2. Evaluation of such unclassified variants may be assisted by web-based bioinformatic prediction tools, although accurate prediction of aberrant splicing by unclassified variants affecting exonic splice enhancers (ESEs) remains a challenge

Description and analysis of genetic variants in French hereditary breast and ovarian cancer families recorded in the UMD-BRCA1/BRCA2 databases

BRCA1 and BRCA2 are the two main genes responsible for predisposition to breast and ovarian cancers, as a result of protein-inactivating monoallelic mutations. It remains to be established whether many of the variants identified in these two genes, so-called unclassified/unknown variants (UVs), contribute to the disease phenotype or are simply neutral variants (or polymorphisms). Given the clinical importance of establishing their status, a nationwide effort to annotate these UVs was launched by laboratories belonging to the French GGC consortium (Groupe Génétique et Cancer), leading to the creation of the UMD-BRCA1/BRCA2 databases (http://www.umd.be/BRCA1/ and http://www.umd.be/BRCA2/). These databases have been endorsed by the French National Cancer Institute (INCa) and are designed to collect all variants detected in France, whether causal, neutral or UV. They differ from other BRCA databases in that they contain co-occurrence data for all variants. Using these data, the GGC French consortium has been able to classify certain UVs also contained in other databases. In this article, we report some novel UVs not contained in the BIC database and explore their impact in cancer predisposition based on a structural approach

Associations of common breast cancer susceptibility alleles with risk of breast cancer subtypes in BRCA1 and BRCA2 mutation carriers

Introduction: More than 70 common alleles are known to be involved in breast cancer (BC) susceptibility, and several exhibit significant heterogeneity in their associations with different BC subtypes. Although there are differences in the association patterns between BRCA1 and BRCA2 mutation carriers and the general population for several loci, no study has comprehensively evaluated the associations of all known BC susceptibility alleles with risk of BC subtypes in BRCA1 and BRCA2 carriers. Methods: We used data from 15,252 BRCA1 and 8,211 BRCA2 carriers to analyze the associations between approximately 200,000 genetic variants on the iCOGS array and risk of BC subtypes defined by estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and triple-negative- (TN) status; morphologic subtypes; histological grade; and nodal involvement. Results: The estimated BC hazard ratios (HRs) for the 74 known BC alleles in BRCA1 carriers exhibited moderate correlations with the corresponding odds ratios from the general population. However, their associations with ER-positive BC in BRCA1 carriers were more consistent with the ER-positive as

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1,395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; and 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared with information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known nonpathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification

Common breast cancer susceptibility alleles are associated with tumor subtypes in BRCA1 and BRCA2 mutation carriers : results from the Consortium of Investigators of Modifiers of BRCA1/2.

Abstract Introduction Previous studies have demonstrated that common breast cancer susceptibility alleles are differentially associated with breast cancer risk for BRCA1 and/or BRCA2 mutation carriers. It is currently unknown how these alleles are associated with different breast cancer subtypes in BRCA1 and BRCA2 mutation carriers defined by estrogen (ER) or progesterone receptor (PR) status of the tumour. Methods We used genotype data on up to 11,421 BRCA1 and 7,080 BRCA2 carriers, of whom 4,310 had been affected with breast cancer and had information on either ER or PR status of the tumour, to assess the associations of 12 loci with breast cancer tumour characteristics. Associations were evaluated using a retrospective cohort approach. Results The results suggested stronger associations with ER-positive breast cancer than ER-negative for 11 loci in both BRCA1 and BRCA2 carriers. Among BRCA1 carriers, single nucleotide polymorphism (SNP) rs2981582 (FGFR2) exhibited the biggest difference based on ER status (per-allele hazard ratio (HR) for ER-positive = 1.35, 95% CI: 1.17 to 1.56 vs HR = 0.91, 95% CI: 0.85 to 0.98 for ER-negative, P-heterogeneity = 6.5 × 10-6). In contrast, SNP rs2046210 at 6q25.1 near ESR1 was primarily associated with ER-negative breast cancer risk for both BRCA1 and BRCA2 carriers. In BRCA2 carriers, SNPs in FGFR2, TOX3, LSP1, SLC4A7/NEK10, 5p12, 2q35, and 1p11.2 were significantly associated with ER-positive but not ER-negative disease. Similar results were observed when differentiating breast cancer cases by PR status. Conclusions The associations of the 12 SNPs with risk for BRCA1 and BRCA2 carriers differ by ER-positive or ER-negative breast cancer status. The apparent differences in SNP associations between BRCA1 and BRCA2 carriers, and non-carriers, may be explicable by differences in the prevalence of tumour subtypes. As more risk modifying variants are identified, incorporating these associations into breast cancer subtype-specific risk models may improve clinical management for mutation carriers

Large scale multifactorial likelihood quantitative analysis of BRCA1 and BRCA2 variants: An ENIGMA resource to support clinical variant classification

Abstract The multifactorial likelihood analysis method has demonstrated utility for quantitative assessment of variant pathogenicity for multiple cancer syndrome genes. Independent data types currently incorporated in the model for assessing BRCA1 and BRCA2 variants include clinically calibrated prior probability of pathogenicity based on variant location and bioinformatic prediction of variant effect, co-segregation, family cancer history profile, co-occurrence with a pathogenic variant in the same gene, breast tumor pathology, and case-control information. Research and clinical data for multifactorial likelihood analysis were collated for 1395 BRCA1/2 predominantly intronic and missense variants, enabling classification based on posterior probability of pathogenicity for 734 variants: 447 variants were classified as (likely) benign, and 94 as (likely) pathogenic; 248 classifications were new or considerably altered relative to ClinVar submissions. Classifications were compared to information not yet included in the likelihood model, and evidence strengths aligned to those recommended for ACMG/AMP classification codes. Altered mRNA splicing or function relative to known non-pathogenic variant controls were moderately to strongly predictive of variant pathogenicity. Variant absence in population datasets provided supporting evidence for variant pathogenicity. These findings have direct relevance for BRCA1 and BRCA2 variant evaluation, and justify the need for gene-specific calibration of evidence types used for variant classification. This article is protected by copyright. All rights reserved.Peer reviewe