Characterization of BRCA1 and BRCA2 splicing variants: a collaborative report by ENIGMA consortium members.

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.