A Computational Method to Classify Variants of Uncertain Significance Using Functional Assay Data With Application to BRCA1

摘要

BackgroundBesides revealing cancer–predisposition variants or the absence of any changes, genetic testing for cancer predisposition genes can also identify variants of uncertain clinical significance (VUS). Classifying VUSs is a pressing problem as ever more patients seek genetic testing for disease syndromes and receive non–informative results from those tests. In cases like the breast–ovarian cancer syndrome where prophylactic options can be severe and life changing, having information on the disease relevance of the VUS that a patient harbors can be critical.