Cargando…

Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma

BACKGROUND: Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mu...

Descripción completa

Detalles Bibliográficos
Autores principales: Zhang, Yuannv, Qiu, Zhaoping, Wei, Lin, Tang, Ruqi, Lian, Baofeng, Zhao, Yingjun, He, Xianghuo, Xie, Lu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4079600/
https://www.ncbi.nlm.nih.gov/pubmed/24988079
http://dx.doi.org/10.1371/journal.pone.0100854
_version_ 1782323871196643328
author Zhang, Yuannv
Qiu, Zhaoping
Wei, Lin
Tang, Ruqi
Lian, Baofeng
Zhao, Yingjun
He, Xianghuo
Xie, Lu
author_facet Zhang, Yuannv
Qiu, Zhaoping
Wei, Lin
Tang, Ruqi
Lian, Baofeng
Zhao, Yingjun
He, Xianghuo
Xie, Lu
author_sort Zhang, Yuannv
collection PubMed
description BACKGROUND: Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. PRINCIPAL FINDINGS: In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. CONCLUSIONS: Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers.
format Online
Article
Text
id pubmed-4079600
institution National Center for Biotechnology Information
language English
publishDate 2014
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-40796002014-07-08 Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma Zhang, Yuannv Qiu, Zhaoping Wei, Lin Tang, Ruqi Lian, Baofeng Zhao, Yingjun He, Xianghuo Xie, Lu PLoS One Research Article BACKGROUND: Recently, a number of studies have performed genome or exome sequencing of hepatocellular carcinoma (HCC) and identified hundreds or even thousands of mutations in protein-coding genes. However, these studies have only focused on a limited number of candidate genes, and many important mutation resources remain to be explored. PRINCIPAL FINDINGS: In this study, we integrated mutation data obtained from various sources and performed pathway and network analysis. We identified 113 pathways that were significantly mutated in HCC samples and found that the mutated genes included in these pathways contained high percentages of known cancer genes, and damaging genes and also demonstrated high conservation scores, indicating their important roles in liver tumorigenesis. Five classes of pathways that were mutated most frequently included (a) proliferation and apoptosis related pathways, (b) tumor microenvironment related pathways, (c) neural signaling related pathways, (d) metabolic related pathways, and (e) circadian related pathways. Network analysis further revealed that the mutated genes with the highest betweenness coefficients, such as the well-known cancer genes TP53, CTNNB1 and recently identified novel mutated genes GNAL and the ADCY family, may play key roles in these significantly mutated pathways. Finally, we highlight several key genes (e.g., RPS6KA3 and PCLO) and pathways (e.g., axon guidance) in which the mutations were associated with clinical features. CONCLUSIONS: Our workflow illustrates the increased statistical power of integrating multiple studies of the same subject, which can provide biological insights that would otherwise be masked under individual sample sets. This type of bioinformatics approach is consistent with the necessity of making the best use of the ever increasing data provided in valuable databases, such as TCGA, to enhance the speed of deciphering human cancers. Public Library of Science 2014-07-02 /pmc/articles/PMC4079600/ /pubmed/24988079 http://dx.doi.org/10.1371/journal.pone.0100854 Text en © 2014 Zhang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Zhang, Yuannv
Qiu, Zhaoping
Wei, Lin
Tang, Ruqi
Lian, Baofeng
Zhao, Yingjun
He, Xianghuo
Xie, Lu
Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma
title Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma
title_full Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma
title_fullStr Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma
title_full_unstemmed Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma
title_short Integrated Analysis of Mutation Data from Various Sources Identifies Key Genes and Signaling Pathways in Hepatocellular Carcinoma
title_sort integrated analysis of mutation data from various sources identifies key genes and signaling pathways in hepatocellular carcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4079600/
https://www.ncbi.nlm.nih.gov/pubmed/24988079
http://dx.doi.org/10.1371/journal.pone.0100854
work_keys_str_mv AT zhangyuannv integratedanalysisofmutationdatafromvarioussourcesidentifieskeygenesandsignalingpathwaysinhepatocellularcarcinoma
AT qiuzhaoping integratedanalysisofmutationdatafromvarioussourcesidentifieskeygenesandsignalingpathwaysinhepatocellularcarcinoma
AT weilin integratedanalysisofmutationdatafromvarioussourcesidentifieskeygenesandsignalingpathwaysinhepatocellularcarcinoma
AT tangruqi integratedanalysisofmutationdatafromvarioussourcesidentifieskeygenesandsignalingpathwaysinhepatocellularcarcinoma
AT lianbaofeng integratedanalysisofmutationdatafromvarioussourcesidentifieskeygenesandsignalingpathwaysinhepatocellularcarcinoma
AT zhaoyingjun integratedanalysisofmutationdatafromvarioussourcesidentifieskeygenesandsignalingpathwaysinhepatocellularcarcinoma
AT hexianghuo integratedanalysisofmutationdatafromvarioussourcesidentifieskeygenesandsignalingpathwaysinhepatocellularcarcinoma
AT xielu integratedanalysisofmutationdatafromvarioussourcesidentifieskeygenesandsignalingpathwaysinhepatocellularcarcinoma