Classification of Amino Acid Substitutions in Mismatch Repair Proteins Using PON‐MMR2. Issue 12 (22nd September 2015)

• Record Type: Journal Article
• Authors: Niroula, Abhishek; Vihinen, Mauno
• Is Part Of: Human mutation. Volume 36:Issue 12(2015:Dec.)
• Page Start: 1128
• Page End: 1134
• Publication Date: 2015-09-22
• Subjects: mismatch repair -- amino acid substitutions -- missense mutation -- computational tool -- prediction -- MMR -- Lynch syndrome; Human chromosome abnormalities -- Periodicals; Mutation (Biology) -- Periodicals; 616.04205
• DOI: 10.1002/humu.22900
• Languages: English
• ISSNs: 1059-7794

Abstract

Abstract : Variations in mismatch repair (MMR) system genes are causative of Lynch syndrome and other cancers. We have developed a novel machine learning‐based tool, PON‐MMR2 (http://structure.bmc.lu.se/PON‐MMR2/ ), for prioritizing pathogenic variations. It achieves accuracy and MCC of 0.89 and 0.78, respectively, in cross‐validation and 0.86 and 0.69, respectively, on an independent test dataset. We classified all possible amino acid substitutions in four MMR proteins. PON‐MMR2 is a highly reliable tool to prioritize variants for functional analysis. ABSTRACT: Variations in mismatch repair (MMR) system genes are causative of Lynch syndrome and other cancers. Thousands of variants have been identified in MMR genes, but the clinical relevance is known for only a small proportion. Recently, the InSiGHT group classified 2, 360 MMR variants into five classes. One‐third of variants, majority of which is nonsynonymous variants, remain to be of uncertain clinical relevance. Computational tools can be used to prioritize variants for disease relevance investigations. Previously, we classified 248 MMR variants as likely pathogenic and likely benign using PON‐MMR. We have developed a novel tool, PON‐MMR2, which is trained on a larger and more reliable dataset. In performance comparison, PON‐MMR2 outperforms both generic tolerance prediction methods as well as methods optimized for MMR variants. It achieves accuracy and MCC of 0.89 and 0.78, respectively, in cross‐validation and 0.86 and 0.69, respectively, on an independent test dataset. We classified 354 class 3 variants in InSiGHT database as well as all possible amino acid substitutions in four MMR proteins. Likely harmful variants mainly appear in the protein core, whereas likely benign variants are on the surface. PON‐MMR2 is a highly reliable tool to prioritize variants for functional analysis. It is freely available athttp://structure.bmc.lu.se/PON‐MMR2/ .