A review of a multifactorial probability-based model for classification of BRCA1 and BRCA2 variants of uncertain significance (VUS).

Clinical mutation screening of the BRCA1 and BRCA2 genes for the presence of germline inactivating mutations is used to identify individuals at elevated risk of breast and ovarian cancer. Variants identified during screening are usually classified as pathogenic (increased risk of cancer) or not pathogenic (no increased risk of cancer). However, a significant proportion of genetic tests yields variants of uncertain significance (VUS) that have undefined risk of cancer. Individuals carrying these VUS cannot benefit from individualized cancer risk assessment. Recently, a quantitative "posterior probability model" for assessing the clinical relevance of VUS in BRCA1 or BRCA2, which integrates multiple forms of genetic evidence has been developed. Here, we provide a detailed review of this model. We describe the components of the model and explain how these can be combined to calculate a posterior probability of pathogenicity for each VUS. We explain how the model can be applied to public data and provide tables that list the VUS that have been classified as not pathogenic or pathogenic using this method. While we use BRCA1 and BRCA2 VUS as examples, the method can be used as a framework for classification of the pathogenicity of VUS in other cancer genes.