ArticleBMC medical genomics2011
Integrative network analysis identifies key genes and pathways in the progression of hepatitis C virus induced hepatocellular carcinoma.
Article in BMC medical genomics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
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Who cites it
27 citing papers in PubMed, 42 citations in OpenAlex.
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- Identification of Key Pathways and Genes in the Dynamic Progression of HCC Based on WGCNA.Genes · 2018Article
- Towards integrated oncogenic marker recognition through mutual information-based statistically significant feature extraction: an association rule mining based study on cancer expression and methylation profiles.Quantitative biology (Beijing, China) · 2017Article
- High throughput deep degradome sequencing reveals microRNAs and their targets in response to drought stress in mulberry (Morus alba).PloS one · 2017Article
- Enhancer of rudimentary homolog regulates DNA damage response in hepatocellular carcinoma.Scientific reports · 2015Article
- Dynamical Regulation Analysis Identifies Molecular Mechanisms of Fuzheng-Huayu Formula against Hepatitis B-Caused Liver Cirrhosis.Evidence-based complementary and alternative medicine : eCAM · 2015Article
- The Effect of C-X-C Motif Chemokine 13 on Hepatocellular Carcinoma Associates with Wnt Signaling.BioMed research international · 2015Article
- Transcriptional profiling and dynamical regulation analysis identify potential kernel target genes of SCYL1-BP1 in HEK293T cells.Molecules and cells · 2014Article
- Reproducible combinatorial regulatory networks elucidate novel oncogenic microRNAs in non-small cell lung cancer.RNA (New York, N.Y.) · 2014Article
- Article
- Network-based study reveals potential infection pathways of hepatitis-C leading to various diseases.PloS one · 2014Article
- Integrative bayesian network analysis of genomic data.Cancer informatics · 2014Article
- EnRICH: Extraction and Ranking using Integration and Criteria Heuristics.BMC systems biology · 2013Article
- Dynamic protein interaction modules in human hepatocellular carcinoma progression.BMC systems biology · 2013Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundIncidence 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.
methodsTo 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.
resultsAmong 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.
conclusionsOur 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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