A functional assay–based procedure to classify mismatch repair gene variants in Lynch syndrome

Research output: Contribution to journalJournal articleResearchpeer-review

Mark Drost, Yvonne Tiersma, Bryony A. Thompson, Jane H. Frederiksen, Guido Keijzers, Dylan Glubb, Scott Kathe, Jan Osinga, Helga Westers, Lisa Pappas, Kenneth M. Boucher, Siska Molenkamp, José B. Zonneveld, Christi J. van Asperen, David E. Goldgar, Susan S. Wallace, Rolf H. Sijmons, Amanda B. Spurdle, Lene J. Rasmussen, Marc S. Greenblatt & 2 others Niels de Wind, Sean V. Tavtigian

Purpose: To enhance classification of variants of uncertain significance (VUS) in the DNA mismatch repair (MMR) genes in the cancer predisposition Lynch syndrome, we developed the cell-free in vitro MMR activity (CIMRA) assay. Here, we calibrate and validate the assay, enabling its integration with in silico and clinical data. Methods: Two sets of previously classified MLH1 and MSH2 variants were selected from a curated MMR gene database, and their biochemical activity determined by the CIMRA assay. The assay was calibrated by regression analysis followed by symmetric cross-validation and Bayesian integration with in silico predictions of pathogenicity. CIMRA assay reproducibility was assessed in four laboratories. Results: Concordance between the training runs met our prespecified validation criterion. The CIMRA assay alone correctly classified 65% of variants, with only 3% discordant classification. Bayesian integration with in silico predictions of pathogenicity increased the proportion of correctly classified variants to 87%, without changing the discordance rate. Interlaboratory results were highly reproducible. Conclusion: The CIMRA assay accurately predicts pathogenic and benign MMR gene variants. Quantitative combination of assay results with in silico analysis correctly classified the majority of variants. Using this calibration, CIMRA assay results can be integrated into the diagnostic algorithm for MMR gene variants.

Original languageEnglish
JournalGenetics in Medicine
ISSN1098-3600
DOIs
Publication statusE-pub ahead of print - 2019

    Research areas

  • assay calibration, functional assay, Lynch syndrome, variant classification, variants of uncertain significance

ID: 212124417