Exceptions to the Rule: Case Studies in the Prediction of Pathogenicity for Genetic Variants in Hereditary Cancer Genes

abstract

 Based on current consensus guidelines and standard practice, many genetic variants detected in clinical testing are classified as disease-causing based on their predicted impact on the normal expression or function of the gene in the absence of additional data. However, our laboratory has identified a subset of such variants in hereditary cancer genes for which compelling contradictory evidence emerged after the initial evaluation following the first observation of the variant. Three representative examples of variants in BRCA1, BRCA2 and MSH2 that are predicted to disrupt splicing, prematurely truncate the protein, or remove the start codon were evaluated for pathogenicity by analyzing clinical data with multiple classification algorithms. Available clinical data for all 3 variants contradicts the expected pathogenic classification. These variants illustrate potential pitfalls associated with standard approaches to variant classification as well as the challenges associated with monitoring data, updating classifications, and reporting potentially contradictory interpretations to the clinicians responsible for translating test outcomes to appropriate clinical action. It is important to address these challenges now as the model for clinical testing moves towards the use of large multi-gene panels and whole exome/genome analysis, which will dramatically increase the number of genetic variants identified.