ArticleInternational journal of clinical and experimental medicine2014
Regulation of gene expression in HBV- and HCV-related hepatocellular carcinoma: integrated GWRS and GWGS analyses.
Article in International journal of clinical and experimental medicine, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 4 citations in OpenAlex.
- Regulatory Role of Ribonucleotide Reductase Subunit M2 in Hepatocyte Growth and Pathogenesis of Hepatitis C Virus.International journal of molecular sciences · 2023Review
- Mechanism of Phellodendron and Anemarrhena Drug Pair on the Treatment of Liver Cancer Based on Network Pharmacology and Bioinformatics.Frontiers in oncology · 2022Article
- Microarray-based identification of genes associated with cancer progression and prognosis in hepatocellular carcinoma.Journal of experimental & clinical cancer research : CR · 2016Article
- Laparoscopic versus open hepatectomy for hepatocellular carcinoma: short- and long-term outcomes comparison.International journal of clinical and experimental medicine · 2015Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivesTo explore the molecular mechanism of hepatitis B virus-related and hepatitis C virus-related hepatocellular carcinoma, samples from hepatitis B virus and hepatitis C virus infected patients and the normal were compared, respectively.
methodsIn both experiments, genes with high value were selected based on a genome-wide relative significance and genome-wide global significance model. Co-expression network of the selected genes was constructed, and transcription factors in the network were identified. Molecular complex detection algorithm was used to obtain sub-networks.
resultsBased on the new model, the top 300 genes were selected. Co-expression network was constructed and transcription factors were identified. We obtained two common genes FCN2 and CXCL14, and two common transcription factors RFX5 and EZH2. In hepatitis B virus experiment, cluster 1 and 3 had the higher value. In cluster 1, ten of the 17 genes and one transcription factor were all reported associated with hepatocellular carcinoma. In cluster 3, transcription factor ESR1 was reported related with hepatocellular carcinoma. In hepatitis C virus experiment, the value of cluster 3 and 4 was higher. In cluster 3, nine genes were reported to play a key role in hepatocellular carcinoma. In cluster 4, there were 5 genes in the 34 genes. To compare the relevance of a node in holding together communicating nodes, centralities based analysis was performed and we obtained some genes with high stress value.
conclusionThe analysis above helped us to understand the pathogenesis of hepatitis B virus and hepatitis C virus associated hepatocellular carcinoma.
Indexed as
Identifiers
25550913PMC4276171W1904080989What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.