Cargando…

An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma

Mutations in the von Hippel–Lindau (VHL) gene are pathogenic in VHL disease, congenital polycythaemia and clear cell renal carcinoma (ccRCC). pVHL forms a ternary complex with elongin C and elongin B, critical for pVHL stability and function, which interacts with Cullin-2 and RING-box protein 1 to t...

Descripción completa

Detalles Bibliográficos
Autores principales: Gossage, Lucy, Pires, Douglas E. V., Olivera-Nappa, Álvaro, Asenjo, Juan, Bycroft, Mark, Blundell, Tom L., Eisen, Tim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4204774/
https://www.ncbi.nlm.nih.gov/pubmed/24969085
http://dx.doi.org/10.1093/hmg/ddu321
_version_ 1782340600935219200
author Gossage, Lucy
Pires, Douglas E. V.
Olivera-Nappa, Álvaro
Asenjo, Juan
Bycroft, Mark
Blundell, Tom L.
Eisen, Tim
author_facet Gossage, Lucy
Pires, Douglas E. V.
Olivera-Nappa, Álvaro
Asenjo, Juan
Bycroft, Mark
Blundell, Tom L.
Eisen, Tim
author_sort Gossage, Lucy
collection PubMed
description Mutations in the von Hippel–Lindau (VHL) gene are pathogenic in VHL disease, congenital polycythaemia and clear cell renal carcinoma (ccRCC). pVHL forms a ternary complex with elongin C and elongin B, critical for pVHL stability and function, which interacts with Cullin-2 and RING-box protein 1 to target hypoxia-inducible factor for polyubiquitination and proteasomal degradation. We describe a comprehensive database of missense VHL mutations linked to experimental and clinical data. We use predictions from in silico tools to link the functional effects of missense VHL mutations to phenotype. The risk of ccRCC in VHL disease is linked to the degree of destabilization resulting from missense mutations. An optimized binary classification system (symphony), which integrates predictions from five in silico methods, can predict the risk of ccRCC associated with VHL missense mutations with high sensitivity and specificity. We use symphony to generate predictions for risk of ccRCC for all possible VHL missense mutations and present these predictions, in association with clinical and experimental data, in a publically available, searchable web server.
format Online
Article
Text
id pubmed-4204774
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-42047742014-10-23 An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma Gossage, Lucy Pires, Douglas E. V. Olivera-Nappa, Álvaro Asenjo, Juan Bycroft, Mark Blundell, Tom L. Eisen, Tim Hum Mol Genet Articles Mutations in the von Hippel–Lindau (VHL) gene are pathogenic in VHL disease, congenital polycythaemia and clear cell renal carcinoma (ccRCC). pVHL forms a ternary complex with elongin C and elongin B, critical for pVHL stability and function, which interacts with Cullin-2 and RING-box protein 1 to target hypoxia-inducible factor for polyubiquitination and proteasomal degradation. We describe a comprehensive database of missense VHL mutations linked to experimental and clinical data. We use predictions from in silico tools to link the functional effects of missense VHL mutations to phenotype. The risk of ccRCC in VHL disease is linked to the degree of destabilization resulting from missense mutations. An optimized binary classification system (symphony), which integrates predictions from five in silico methods, can predict the risk of ccRCC associated with VHL missense mutations with high sensitivity and specificity. We use symphony to generate predictions for risk of ccRCC for all possible VHL missense mutations and present these predictions, in association with clinical and experimental data, in a publically available, searchable web server. Oxford University Press 2014-11-15 2014-06-26 /pmc/articles/PMC4204774/ /pubmed/24969085 http://dx.doi.org/10.1093/hmg/ddu321 Text en © The Author 2014. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Articles
Gossage, Lucy
Pires, Douglas E. V.
Olivera-Nappa, Álvaro
Asenjo, Juan
Bycroft, Mark
Blundell, Tom L.
Eisen, Tim
An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma
title An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma
title_full An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma
title_fullStr An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma
title_full_unstemmed An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma
title_short An integrated computational approach can classify VHL missense mutations according to risk of clear cell renal carcinoma
title_sort integrated computational approach can classify vhl missense mutations according to risk of clear cell renal carcinoma
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4204774/
https://www.ncbi.nlm.nih.gov/pubmed/24969085
http://dx.doi.org/10.1093/hmg/ddu321
work_keys_str_mv AT gossagelucy anintegratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT piresdouglasev anintegratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT oliveranappaalvaro anintegratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT asenjojuan anintegratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT bycroftmark anintegratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT blundelltoml anintegratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT eisentim anintegratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT gossagelucy integratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT piresdouglasev integratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT oliveranappaalvaro integratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT asenjojuan integratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT bycroftmark integratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT blundelltoml integratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma
AT eisentim integratedcomputationalapproachcanclassifyvhlmissensemutationsaccordingtoriskofclearcellrenalcarcinoma