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Integrative network analysis identifies key genes and pathways in the progression of hepatitis C virus induced hepatocellular carcinoma

BACKGROUND: Incidence of hepatitis C virus (HCV) induced hepatocellular carcinoma (HCC) has been increasing in the United States and Europe during recent years. Although HCV-associated HCC shares many pathological characteristics with other types of HCC, its molecular mechanisms of progression remai...

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Autores principales: Zheng, Siyuan, Tansey, William P, Hiebert, Scott W, Zhao, Zhongming
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3212927/
https://www.ncbi.nlm.nih.gov/pubmed/21824427
http://dx.doi.org/10.1186/1755-8794-4-62
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author Zheng, Siyuan
Tansey, William P
Hiebert, Scott W
Zhao, Zhongming
author_facet Zheng, Siyuan
Tansey, William P
Hiebert, Scott W
Zhao, Zhongming
author_sort Zheng, Siyuan
collection PubMed
description BACKGROUND: Incidence of hepatitis C virus (HCV) induced hepatocellular carcinoma (HCC) has been increasing in the United States and Europe during recent years. Although HCV-associated HCC shares many pathological characteristics with other types of HCC, its molecular mechanisms of progression remain elusive. METHODS: To investigate the underlying pathology, we developed a systematic approach to identify deregulated biological networks in HCC by integrating gene expression profiles with high-throughput protein-protein interaction data. We examined five stages including normal (control) liver, cirrhotic liver, dysplasia, early HCC and advanced HCC. RESULTS: Among the five consecutive pathological stages, we identified four networks including precancerous networks (Normal-Cirrhosis and Cirrhosis-Dysplasia) and cancerous networks (Dysplasia-Early HCC, Early-Advanced HCC). We found little overlap between precancerous and cancerous networks, opposite to a substantial overlap within precancerous or cancerous networks. We further found that the hub proteins interacted with HCV proteins, suggesting direct interventions of these networks by the virus. The functional annotation of each network demonstrates a high degree of consistency with current knowledge in HCC. By assembling these functions into a module map, we could depict the stepwise biological functions that are deregulated in HCV-induced hepatocarcinogenesis. Additionally, these networks enable us to identify important genes and pathways by developmental stage, such as LCK signalling pathways in cirrhosis, MMP genes and TIMP genes in dysplastic liver, and CDC2-mediated cell cycle signalling in early and advanced HCC. CDC2 (alternative symbol CDK1), a cell cycle regulatory gene, is particularly interesting due to its topological position in temporally deregulated networks. CONCLUSIONS: Our study uncovers a temporal spectrum of functional deregulation and prioritizes key genes and pathways in the progression of HCV induced HCC. These findings present a wealth of information for further investigation.
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spelling pubmed-32129272011-11-11 Integrative network analysis identifies key genes and pathways in the progression of hepatitis C virus induced hepatocellular carcinoma Zheng, Siyuan Tansey, William P Hiebert, Scott W Zhao, Zhongming BMC Med Genomics Research Article BACKGROUND: Incidence of hepatitis C virus (HCV) induced hepatocellular carcinoma (HCC) has been increasing in the United States and Europe during recent years. Although HCV-associated HCC shares many pathological characteristics with other types of HCC, its molecular mechanisms of progression remain elusive. METHODS: To investigate the underlying pathology, we developed a systematic approach to identify deregulated biological networks in HCC by integrating gene expression profiles with high-throughput protein-protein interaction data. We examined five stages including normal (control) liver, cirrhotic liver, dysplasia, early HCC and advanced HCC. RESULTS: Among the five consecutive pathological stages, we identified four networks including precancerous networks (Normal-Cirrhosis and Cirrhosis-Dysplasia) and cancerous networks (Dysplasia-Early HCC, Early-Advanced HCC). We found little overlap between precancerous and cancerous networks, opposite to a substantial overlap within precancerous or cancerous networks. We further found that the hub proteins interacted with HCV proteins, suggesting direct interventions of these networks by the virus. The functional annotation of each network demonstrates a high degree of consistency with current knowledge in HCC. By assembling these functions into a module map, we could depict the stepwise biological functions that are deregulated in HCV-induced hepatocarcinogenesis. Additionally, these networks enable us to identify important genes and pathways by developmental stage, such as LCK signalling pathways in cirrhosis, MMP genes and TIMP genes in dysplastic liver, and CDC2-mediated cell cycle signalling in early and advanced HCC. CDC2 (alternative symbol CDK1), a cell cycle regulatory gene, is particularly interesting due to its topological position in temporally deregulated networks. CONCLUSIONS: Our study uncovers a temporal spectrum of functional deregulation and prioritizes key genes and pathways in the progression of HCV induced HCC. These findings present a wealth of information for further investigation. BioMed Central 2011-08-08 /pmc/articles/PMC3212927/ /pubmed/21824427 http://dx.doi.org/10.1186/1755-8794-4-62 Text en Copyright ©2011 Zheng et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zheng, Siyuan
Tansey, William P
Hiebert, Scott W
Zhao, Zhongming
Integrative network analysis identifies key genes and pathways in the progression of hepatitis C virus induced hepatocellular carcinoma
title Integrative network analysis identifies key genes and pathways in the progression of hepatitis C virus induced hepatocellular carcinoma
title_full Integrative network analysis identifies key genes and pathways in the progression of hepatitis C virus induced hepatocellular carcinoma
title_fullStr Integrative network analysis identifies key genes and pathways in the progression of hepatitis C virus induced hepatocellular carcinoma
title_full_unstemmed Integrative network analysis identifies key genes and pathways in the progression of hepatitis C virus induced hepatocellular carcinoma
title_short Integrative network analysis identifies key genes and pathways in the progression of hepatitis C virus induced hepatocellular carcinoma
title_sort integrative network analysis identifies key genes and pathways in the progression of hepatitis c virus induced hepatocellular carcinoma
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3212927/
https://www.ncbi.nlm.nih.gov/pubmed/21824427
http://dx.doi.org/10.1186/1755-8794-4-62
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