Bioinformatics Knowledge Map for Analysis of Beta-Catenin Function in Cancer.

Given the wealth of bioinformatics resources and the growing complexity of biological information, it is valuable to integrate data from disparate sources to gain insight into the role of genes/proteins in health and disease. We have developed a bioinformatics framework that combines literature mini...

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Main Authors: İrem Çelen, Karen E Ross, Cecilia N Arighi, Cathy H Wu
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4624812?pdf=render
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spelling doaj-cc0a8510483b4ebbacbba11812bb0f972020-11-24T22:18:06ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-011010e014177310.1371/journal.pone.0141773Bioinformatics Knowledge Map for Analysis of Beta-Catenin Function in Cancer.İrem ÇelenKaren E RossCecilia N ArighiCathy H WuGiven the wealth of bioinformatics resources and the growing complexity of biological information, it is valuable to integrate data from disparate sources to gain insight into the role of genes/proteins in health and disease. We have developed a bioinformatics framework that combines literature mining with information from biomedical ontologies and curated databases to create knowledge "maps" of genes/proteins of interest. We applied this approach to the study of beta-catenin, a cell adhesion molecule and transcriptional regulator implicated in cancer. The knowledge map includes post-translational modifications (PTMs), protein-protein interactions, disease-associated mutations, and transcription factors co-activated by beta-catenin and their targets and captures the major processes in which beta-catenin is known to participate. Using the map, we generated testable hypotheses about beta-catenin biology in normal and cancer cells. By focusing on proteins participating in multiple relation types, we identified proteins that may participate in feedback loops regulating beta-catenin transcriptional activity. By combining multiple network relations with PTM proteoform-specific functional information, we proposed a mechanism to explain the observation that the cyclin dependent kinase CDK5 positively regulates beta-catenin co-activator activity. Finally, by overlaying cancer-associated mutation data with sequence features, we observed mutation patterns in several beta-catenin PTM sites and PTM enzyme binding sites that varied by tissue type, suggesting multiple mechanisms by which beta-catenin mutations can contribute to cancer. The approach described, which captures rich information for molecular species from genes and proteins to PTM proteoforms, is extensible to other proteins and their involvement in disease.http://europepmc.org/articles/PMC4624812?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author İrem Çelen
Karen E Ross
Cecilia N Arighi
Cathy H Wu
spellingShingle İrem Çelen
Karen E Ross
Cecilia N Arighi
Cathy H Wu
Bioinformatics Knowledge Map for Analysis of Beta-Catenin Function in Cancer.
PLoS ONE
author_facet İrem Çelen
Karen E Ross
Cecilia N Arighi
Cathy H Wu
author_sort İrem Çelen
title Bioinformatics Knowledge Map for Analysis of Beta-Catenin Function in Cancer.
title_short Bioinformatics Knowledge Map for Analysis of Beta-Catenin Function in Cancer.
title_full Bioinformatics Knowledge Map for Analysis of Beta-Catenin Function in Cancer.
title_fullStr Bioinformatics Knowledge Map for Analysis of Beta-Catenin Function in Cancer.
title_full_unstemmed Bioinformatics Knowledge Map for Analysis of Beta-Catenin Function in Cancer.
title_sort bioinformatics knowledge map for analysis of beta-catenin function in cancer.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
description Given the wealth of bioinformatics resources and the growing complexity of biological information, it is valuable to integrate data from disparate sources to gain insight into the role of genes/proteins in health and disease. We have developed a bioinformatics framework that combines literature mining with information from biomedical ontologies and curated databases to create knowledge "maps" of genes/proteins of interest. We applied this approach to the study of beta-catenin, a cell adhesion molecule and transcriptional regulator implicated in cancer. The knowledge map includes post-translational modifications (PTMs), protein-protein interactions, disease-associated mutations, and transcription factors co-activated by beta-catenin and their targets and captures the major processes in which beta-catenin is known to participate. Using the map, we generated testable hypotheses about beta-catenin biology in normal and cancer cells. By focusing on proteins participating in multiple relation types, we identified proteins that may participate in feedback loops regulating beta-catenin transcriptional activity. By combining multiple network relations with PTM proteoform-specific functional information, we proposed a mechanism to explain the observation that the cyclin dependent kinase CDK5 positively regulates beta-catenin co-activator activity. Finally, by overlaying cancer-associated mutation data with sequence features, we observed mutation patterns in several beta-catenin PTM sites and PTM enzyme binding sites that varied by tissue type, suggesting multiple mechanisms by which beta-catenin mutations can contribute to cancer. The approach described, which captures rich information for molecular species from genes and proteins to PTM proteoforms, is extensible to other proteins and their involvement in disease.
url http://europepmc.org/articles/PMC4624812?pdf=render
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