Mutations in BRCA1 and BRCA2 predispose carriers to early onset breast and ovarian cancer. A common problem in clinical genetic testing is interpretation of variants with unknown clinical significance. The Evidence-based Network for the Interpretation of Germline Mutant Alleles (ENIGMA) consortium was initiated to evaluate and implement strategies to characterize the clinical significance of BRCA1 and BRCA2 variants. As an initial project of the ENIGMA Splicing Working Group, we report splicing and multifactorial likelihood analysis of 25 BRCA1 and BRCA2 variants from seven different laboratories. Splicing analysis was performed by reverse transcriptase PCR or mini gene assay, and sequencing to identify aberrant transcripts. The findings were compared to bioinformatic predictions using four programs. The posterior probability of pathogenicity was estimated using multifactorial likelihood analysis, including co-occurrence with a deleterious mutation, segregation and/or report of family history. Abnormal splicing patterns expected to lead to a non-functional protein were observed for 7 variants (BRCA1 c.441+2T>A, c.4184_4185+2del, c.4357+1G>A, c.4987-2A>G, c.5074G>C, BRCA2 c.316+5G>A, and c.8754+3G>C). Combined interpretation of splicing and multifactorial analysis classified an initiation codon variant (BRCA2 c.3G>A) as likely pathogenic, uncertain clinical significance for 7 variants, and indicated low clinical significance or unlikely pathogenicity for another 10 variants. Bioinformatic tools predicted disruption of consensus donor or acceptor sites with high sensitivity, but cryptic site usage was predicted with low specificity, supporting the value of RNA-based assays. The findings also provide further evidence that clinical RNA-based assays should be extended from analysis of invariant dinucleotides to routinely include all variants located within the donor and acceptor consensus splicing sites. Importantly, this study demonstrates the added value of collaboration between laboratories, and across disciplines, to collate and interpret information from clinical testing laboratories to consolidate patient management.

Mutational screening of the breast cancer susceptibility gene BRCA1 leads to the identification of numerous pathogenic variants such as frameshift and nonsense variants, as well as large genomic rearrangements. The screening moreover identifies a large number of variants, for example, missense, silent, and intron variants, which are classified as variants of unknown clinical significance owing to the lack of causal evidence. Variants of unknown clinical significance can potentially have an impact on splicing and therefore functional examinations are warranted to classify whether these variants are pathogenic or benign. Here we validate a mini-gene splicing assay by comparing the results of 24 variants with previously published data from RT-PCR analysis on RNA from blood samples/lymphoblastoid cell lines. The analysis showed an overall concordance of 100%. In addition, we investigated 13 BRCA1 variants of unknown clinical significance or putative variants affecting splicing by in silico analysis and mini-gene splicing assay. Both the in silico analysis and mini-gene splicing assay classified six BRCA1 variants as pathogenic (c.80+1G>A, c.132C>T (p.=), c.213−1G>A, c.670+1delG, c.4185+1G>A, and c.5075−1G>C), whereas six BRCA1 variants were classified as neutral (c.-19-22_-19-21dupAT, c.302−15C>G, c.547+14delG, c.4676−20A>G, c.4987−21G>T, and c.5278−14C>G) and one BRCA1 variant remained unclassified (c.670+16G>A). In conclusion, our study emphasizes that in silico analysis and mini-gene splicing assays are important for the classification of variants, especially if no RNA is available from the patient. This knowledge is crucial for proper genetic counseling of patients and their family members.

Germ-line mutations in the RAD51C gene have recently been identified in families with breast and ovarian cancer and have been associated with an increased risk of ovarian cancer. In this study, we describe the frequency of pathogenic RAD51C mutations identified in Danish breast and/or ovarian cancer families. We screened the RAD51C gene in 1228 Danish hereditary breast and/or ovarian cancer families by next-generation sequencing analysis. The frequency of the identified variants was examined in the exome sequencing project database and in data from 2000 Danish exomes and the presumed significance of missense and intronic variants was predicted by in silico analysis. We identified six families with a pathogenic mutation in RAD51C, including three frameshift mutations, one nonsense mutation, and 2 missense mutations. Overall, pathogenic RAD51C mutations were identified in 0.5 % of Danish families with increased risk of hereditary breast and/or ovarian cancer. Moreover, we identified 24 additional RAD51C variants of which 14 have not been previously reported in the literature. In this study, we determine the prevalence of RAD51C mutations in Danish breast and/or ovarian cancer families. We identified six pathogenic RAD51C mutations as well as 23 variants of uncertain clinical significance and one benign variant. Together, the study extends our knowledge of the RAD51C mutation spectrum and supports that RAD51C should be included in gene panel testing of individuals with high risk of breast and ovarian cancer.