Accurate classification of MLH1/MSH2 missense variants with multivariate analysis of protein polymorphisms–mismatch repair (MAPP-MMR)
✍ Scribed by Elizabeth C. Chao; Jonathan L. Velasquez; Mavee S.L. Witherspoon; Laura S. Rozek; David Peel; Pauline Ng; Stephen B. Gruber; Patrice Watson; Gad Rennert; Hoda Anton-Culver; Henry Lynch; Steven M. Lipkin
- Book ID
- 102262100
- Publisher
- John Wiley and Sons
- Year
- 2008
- Tongue
- English
- Weight
- 233 KB
- Volume
- 29
- Category
- Article
- ISSN
- 1059-7794
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✦ Synopsis
Communicated by Marc Greenblatt
Lynch syndrome, also known as hereditary nonpolyposis colon cancer (HNPCC), is the most common known genetic syndrome for colorectal cancer (CRC). MLH1/MSH2 mutations 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 classifies MLH1/MSH2 deleterious and neutral missense variants. We compiled a large database (n4300) of MLH1/MSH2 missense 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 distinguishes MLH1/MSH2 deleterious variants from neutral variants. Hum Mutat 29(6), 852-860, 2008.