Researchers have developed a framework to prioritize variants of uncertain significance in the BRCA1 and BRCA2 genes, which are associated with hereditary breast cancer. The approach involves comprehensive genomic profiling and may utilize machine learning models and computational methods to predict the pathogenicity of variants. Studies examining large datasets, including over 400,000 women, are providing evidence to refine variant classification and better understand the contribution of rare variants to hereditary breast cancer.