Accurate Classification ofMLH1/MSH2Missense Variants With Multivariate Analysis of Protein Polymorphisms-Mismatch Repair (MAPP-MMR)

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Abstract

Lynch syndrome, also known as hereditary nonpolyposis colon cancer (HNPCC), is the most common known genetic syndrome for colorectal cancer (CRC).MLH1/MSH2mutations underlie approximately 90% of Lynch syndrome families. A total of 24% of these mutations are missense. Interpreting missense variation is extremely challenging. We have therefore developed multivariate analysis of protein polymorphisms-mismatch repair (MAPP-MMR), a bioinformatic algorithm that effectively classifiesMLH1/MSH2deleterious and neutral missense variants. We compiled a large database (n>300) ofMLH1/MSH2missense variants with associated clinical and molecular characteristics. We divided this database into nonoverlapping training and validation sets and tested MAPP-MMR. MAPP-MMR significantly outperformed other missense variant classification algorithms (sensitivity, 94%; specificity, 96%; positive predictive value [PPV] 98%; negative predictive value [NPV], 89%), such as SIFT and PolyPhen. MAPP-MMR is an effective bioinformatic tool for missense variant interpretation that accurately distinguishesMLH1/MSH2deleterious variants from neutral variants. Hum Mutat 29(6), 852-860, 2008.

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