ArticleOncology letters2019
Screening of potential biomarkers in hepatitis C virus-induced hepatocellular carcinoma using bioinformatic analysis.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Key hub genes and pathways associated with HCV-related hepatocellular carcinoma as potential diagnostic biomarkers.Journal, genetic engineering & biotechnology · 2026Article
- Comprehensive transcriptomic analysis of hepatocellular Carcinoma: Uncovering shared and unique molecular signatures across diverse etiologies.Biochemistry and biophysics reports · 2025Article
- HCV-related hepatocellular carcinoma: gene signatures associated with TERT promoter mutations and sex.Journal of translational medicine · 2025Article
- Molecular and genetic markers in hepatocellular carcinoma:World journal of gastrointestinal pathophysiology · 2022Article
- Databases, Knowledgebases, and Software Tools for Virus Informatics.Advances in experimental medicine and biology · 2022Article
- Current and Emerging Molecular Markers of Liver Diseases: A Pathogenic Perspective.Gene expression · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Evidence suggests that hepatitis C virus (HCV) infection is among the main causes of hepatocellular carcinoma (HCC). In addition, HCV-induced HCC (HCV-HCC) exhibits adverse clinical outcomes and limited therapeutic treatments are available for this condition. To investigate key biomarkers in the occurrence and development of HCV-HCC, microarray datasets GSE62232, GSE69715 and GSE107170 were downloaded from the Gene Expression Omnibus database for analysis. The differentially expressed genes between HCV-HCC and normal tissue were identified using the GEO2R online tool. The function enrichment analyses including Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were performed using the Database for Annotation, Visualization and Integrated Discovery online tool. A protein-protein interaction network was constructed using the Search Tool for the Retrieval of Interacting Genes database and visualized using Cytoscape. A total of 368 DEGs were identified, and the top 10 hub genes with a high degree of connectivity were selected for further analysis. Subsequently, overall survival and disease-free survival analysis revealed that there was a significant association between altered expression of HMMR, CCNB1 and KIF20A, and poor clinical outcome. In summary, these results indicate that HMMR, CCNB1 and KIF20A are potential targets for diagnosis and therapy of HCV-HCC.
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