DNA methylation profiling to assess pathogenicity of <i>BRCA1</i> unclassified variants in breast cancer

Germline pathogenic mutations in <i>BRCA1</i> increase risk of developing breast cancer. Screening for mutations in <i>BRCA1</i> frequently identifies sequence variants of unknown pathogenicity and recent work has aimed to develop methods for determining pathogenicity. We previously observed that tumor DNA methylation can differentiate <i>BRCA1</i>-mutated from <i>BRCA1</i>-wild type tumors. We hypothesized that we could predict pathogenicity of variants based on DNA methylation profiles of tumors that had arisen in carriers of unclassified variants. We selected 150 FFPE breast tumor DNA samples [47 <i>BRCA1</i> pathogenic mutation carriers, 65 BRCAx (<i>BRCA1</i>-wild type), 38 <i>BRCA1</i> test variants] and analyzed a subset (n=54) using the Illumina 450K methylation platform, using the remaining samples for bisulphite pyrosequencing validation. Three validated markers (<i>BACH2, C8orf31,</i> and <i>LOC654342</i>) were combined with sequence bioinformatics in a model to predict pathogenicity of 27 variants (independent test set). Predictions were compared with standard multifactorial likelihood analysis. Prediction was consistent for c.5194-12G&gt;A (IVS 19-12 G&gt;A) (<i>P</i>&gt;0.99); 13 variants were considered not pathogenic or likely not pathogenic using both approaches. We conclude that tumor DNA methylation data alone has potential to be used in prediction of <i>BRCA1</i> variant pathogenicity but is not independent of estrogen receptor status and grade, which are used in current multifactorial models to predict pathogenicity.