Calibration of Multiple In Silico Tools for Predicting Pathogenicity of Mismatch Repair Gene Missense Substitutions

Bryony A. Thompson, Marc S. Greenblatt, Maxime P. Vallee, Johanna C. Herkert, Chloe Tessereau, Erin L. Young, Ivan A. Adzhubey, Biao Li, Russell Bell, Bingjian Feng, Sean D. Mooney, Predrag Radivojac (+9 others)
<span title="2012-10-22">2012</span> <i title="Wiley"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2vzjuzyygveinhd4ab2ux34qv4" style="color: black;">Human Mutation</a> </i> &nbsp;
Classification of rare missense substitutions observed during genetic testing for patient management is a considerable problem in clinical genetics. The Bayesian integrated evaluation of unclassified variants is a solution originally developed for BRCA1/2. Here, we take a step toward an analogous system for the mismatch repair (MMR) genes (MLH1, MSH2, MSH6, and PMS2) that confer colon cancer susceptibility in Lynch syndrome by calibrating in silico tools to estimate prior probabilities of
more &raquo; ... enicity for MMR gene missense substitutions. A qualitative five-class classification system was developed and applied to 143 MMR missense variants. This identified 74 missense substitutions suitable for calibration. These substitutions were scored using six different in silico tools (Align-Grantham Variation Grantham Deviation, multivariate analysis of protein polymorphisms [MAPP], Mut-Pred, PolyPhen-2.1, Sorting Intolerant From Tolerant, and Xvar), using curated MMR multiple sequence alignments where possible. The output from each tool was calibrated by regression against the classifications of the 74 missense substitutions; these calibrated outputs are interpretable as prior probabilities of pathogenicity. MAPP was the most accurate tool and MAPP + PolyPhen-2.Contract grant sponsors: NHMRC (ID 496616); Cancer Australia (1010859); NIH NCI (P30 CA042014). vided the best-combined model (R 2 = 0.62 and area under receiver operating characteristic = 0.93). The MAPP + PolyPhen-2.1 output is sufficiently predictive to feed as a continuous variable into the quantitative Bayesian integrated evaluation for clinical classification of MMR gene missense substitutions.
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1002/humu.22214">doi:10.1002/humu.22214</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/22949387">pmid:22949387</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC4318556/">pmcid:PMC4318556</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/5m7wonq3tnbxdeabjnpzuq427m">fatcat:5m7wonq3tnbxdeabjnpzuq427m</a> </span>
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