Classification of mismatch repair gene missense variants with PON-MMR
Ali, Heidi ; Olatubosun, Ayodeji and Vihinen, Mauno LU
(2012)
In Human Mutation
33(4).
p.642-650
- Abstract
- Numerous mismatch repair (MMR) gene variants have been identified in Lynch syndrome and other cancer patients, but knowledge about their pathogenicity is frequently missing. The diagnosis and treatment of patients would benefit from knowing which variants are disease related. Bioinformatic approaches are well suited to the problem and can handle large numbers of cases. Functional effects were revealed based on literature for 168 MMR missense variants. Performance of numerous prediction methods was tested with this dataset. Among the tested tools, only the results of tolerance prediction methods correlated to functional information, however, with poor performance. Therefore, a novel consensus-based predictor was developed. The novel... (More)
- Numerous mismatch repair (MMR) gene variants have been identified in Lynch syndrome and other cancer patients, but knowledge about their pathogenicity is frequently missing. The diagnosis and treatment of patients would benefit from knowing which variants are disease related. Bioinformatic approaches are well suited to the problem and can handle large numbers of cases. Functional effects were revealed based on literature for 168 MMR missense variants. Performance of numerous prediction methods was tested with this dataset. Among the tested tools, only the results of tolerance prediction methods correlated to functional information, however, with poor performance. Therefore, a novel consensus-based predictor was developed. The novel prediction method, pathogenic-or-not mismatch repair (PON-MMR), achieved accuracy of 0.87 and Matthews correlation coefficient of 0.77 on the experimentally verified variants. When applied to 616 MMR cases with unknown effects, 81 missense variants were predicted to be pathogenic and 167 neutral. With PON-MMR, the number of MMR missense variants with unknown effect was reduced by classifying a large number of cases as likely pathogenic or benign. The results can be used, for example, to prioritize cases for experimental studies and assist in the classification of cases. Hum Mutat 33:642650, 2012. (c) 2012 Wiley Periodicals, Inc. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/2561837
- author
- Ali, Heidi
; Olatubosun, Ayodeji
and Vihinen, Mauno
LU
- organization
- publishing date
- 2012
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- bioinformatic prediction method, Lynch syndrome, colorectal cancer, genetic diagnostics
- in
- Human Mutation
- volume
- 33
- issue
- 4
- pages
- 642 - 650
- publisher
- John Wiley & Sons Inc.
- external identifiers
-
- wos:000301338900010
- scopus:84858205858
- pmid:22290698
- ISSN
- 1059-7794
- DOI
- 10.1002/humu.22038
- language
- English
- LU publication?
- yes
- id
- b4d2190b-1a4b-4254-8df9-5a348ecfc990 (old id 2561837)
- date added to LUP
- 2016-04-01 10:12:41
- date last changed
- 2022-04-19 23:52:11
@article{b4d2190b-1a4b-4254-8df9-5a348ecfc990,
abstract = {{Numerous mismatch repair (MMR) gene variants have been identified in Lynch syndrome and other cancer patients, but knowledge about their pathogenicity is frequently missing. The diagnosis and treatment of patients would benefit from knowing which variants are disease related. Bioinformatic approaches are well suited to the problem and can handle large numbers of cases. Functional effects were revealed based on literature for 168 MMR missense variants. Performance of numerous prediction methods was tested with this dataset. Among the tested tools, only the results of tolerance prediction methods correlated to functional information, however, with poor performance. Therefore, a novel consensus-based predictor was developed. The novel prediction method, pathogenic-or-not mismatch repair (PON-MMR), achieved accuracy of 0.87 and Matthews correlation coefficient of 0.77 on the experimentally verified variants. When applied to 616 MMR cases with unknown effects, 81 missense variants were predicted to be pathogenic and 167 neutral. With PON-MMR, the number of MMR missense variants with unknown effect was reduced by classifying a large number of cases as likely pathogenic or benign. The results can be used, for example, to prioritize cases for experimental studies and assist in the classification of cases. Hum Mutat 33:642650, 2012. (c) 2012 Wiley Periodicals, Inc.}},
author = {{Ali, Heidi and Olatubosun, Ayodeji and Vihinen, Mauno}},
issn = {{1059-7794}},
keywords = {{bioinformatic prediction method; Lynch syndrome; colorectal cancer; genetic diagnostics}},
language = {{eng}},
number = {{4}},
pages = {{642--650}},
publisher = {{John Wiley & Sons Inc.}},
series = {{Human Mutation}},
title = {{Classification of mismatch repair gene missense variants with PON-MMR}},
url = {{http://dx.doi.org/10.1002/humu.22038}},
doi = {{10.1002/humu.22038}},
volume = {{33}},
year = {{2012}},
}