Two integrated and highly predictive functional analysis-based procedures for the classification of MSH6 variants in Lynch syndrome
Mark Drost, Yvonne Tiersma, Dylan M. Glubb, Scott D. Kathe, Sandrine van Hees, Fabienne M.G.R. Calléja, José B.M. Zonneveld, Kenneth M. Boucher, Renuka P.E. Ramlal, Bryony A. Thompson, Lene Juel Rasmussen, Marc S. Greenblatt, Andrea Lee, Amanda B. Spurdle, Sean V. Tavtigian, Niels de Wind
Abstract
PURPOSE: Variants in the DNA mismatch repair (MMR) gene MSH6, identified in individuals suspected of Lynch syndrome, are difficult to classify owing to the low cancer penetrance of defects in that gene. This not only obfuscates personalized health care but also the development of a rapid and reliable classification procedure that does not require clinical data. METHODS: The complete in vitro MMR activity (CIMRA) assay was calibrated against clinically classified MSH6 variants and, employing Bayes' rule, integrated with computational predictions of pathogenicity. To enable the validation of this two-component classification procedure we have employed a genetic screen to generate a large set of inactivating Msh6 variants, as proxies for pathogenic variants. RESULTS: The genetic screen-derived variants established that the two-component classification procedure displays high sensitivities and specificities. Moreover, these inactivating variants enabled the direct reclassification of human variants of uncertain significance (VUS) as (likely) pathogenic. CONCLUSION: The two-component classification procedure and the genetic screens provide complementary approaches to rapidly and cost-effectively classify the large majority of human MSH6 variants. The approach followed here provides a template for the classification of variants in other disease-predisposing genes, facilitating the translation of personalized genomics into personalized health care.