2012
DOI: 10.1002/humu.22214
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Calibration of Multiple In Silico Tools for Predicting Pathogenicity of Mismatch Repair Gene Missense Substitutions

Abstract: 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 pathogenicity for MMR… Show more

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Cited by 82 publications
(118 citation statements)
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“…This classification system is described in (Thompson et al. 2013). If the variant was not reported in the LOVD database, we used the same system as InSiGHT for classification.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…This classification system is described in (Thompson et al. 2013). If the variant was not reported in the LOVD database, we used the same system as InSiGHT for classification.…”
Section: Methodsmentioning
confidence: 99%
“…2008; Thompson et al. 2013), in which class 1 and 2 variants are not or most likely not pathogenic, respectively, VUS are class 3 variants, whereas class 4 and 5 are likely pathogenic and pathogenic, respectively. The classification of variants is important because class 4 and 5 is used to confirm a Lynch syndrome diagnosis and predictive testing can subsequently be offered to family members.…”
Section: Introductionmentioning
confidence: 99%
“…Also the Ile219Val polymorphism may be linked with greater mutation frequency (deletions or substitutions rather than insertions) [31]. However, the recent qualitative classification by calibration in silico Tools defined the MLH1 (p.Ile219Leu) missense substitution as non-pathogenic [32]. Some studies also show no association between MLH1 Ile219Val polymorphisms and hereditary colorectal cancer development [33,34].…”
Section: Discussionmentioning
confidence: 99%
“…A variety of computational and structural machine learning methods have been used to probe the effects of SNPs on protein structure and function (Chan et al, 2007;Miller et al, 2011;Thompson et al, 2012). Current methods include some that use only multiple protein alignments, some that use only structural information, and some that combine these two inputs (Katsonis et al, 2014).…”
Section: Introduction Pmentioning
confidence: 99%
“…Current methods include some that use only multiple protein alignments, some that use only structural information, and some that combine these two inputs (Katsonis et al, 2014). Especially notable are predictive approaches related to missense substitutions in mismatch repair genes that can underlie rapid, noninvasive diagnoses in the clinic (Thompson et al, 2012).…”
Section: Introduction Pmentioning
confidence: 99%