ArticleMedicine2019
Identification of key genes and pathways in hepatocellular carcinoma: A preliminary bioinformatics analysis.
Article in Medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed, 36 citations in OpenAlex.
- Polypharmacological Exploration of Petroselinum Crispum for Antifibrotic Therapeutics: from Herb to Hepatoprotection.Applied biochemistry and biotechnology · 2026Article
- Integrated molecular analysis of granulosa cells and follicular fluid extracellular vesicles reveals predictive biomarkers of oocyte maturation in the southern white rhinoceros.Frontiers in cell and developmental biology · 2026Article
- Identification of CDK1 as a Biomarker for the Treatment of Liver Fibrosis and Hepatocellular Carcinoma Through Bioinformatics Analysis.International journal of molecular sciences · 2025Article
- Article
- Statistical and machine learning based platform-independent key genes identification for hepatocellular carcinoma.PloS one · 2025Article
- The role of Cyclin Dependent Kinase Inhibitor 3 (Heliyon · 2024Review
- Comprehensive Profiling and Therapeutic Insights into Differentially Expressed Genes in Hepatocellular Carcinoma.Cancers · 2023Article
- Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning.Scientific reports · 2023Article
- Article
- Identification of genes predicting unfavorable prognosis in hepatitis B virus-associated hepatocellular carcinoma.Annals of translational medicine · 2021Article
- Identification of Key Genes for Hepatitis Delta Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis.The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology · 2021Article
- A Five-Gene-Based Prognostic Signature for Hepatocellular Carcinoma.Frontiers in medicine · 2021Article
- Comprehensive Pan-Cancer Analysis of the Prognostic and Immunological Roles of the METTL3/lncRNA-SNHG1/miRNA-140-3p/UBE2C Axis.Frontiers in cell and developmental biology · 2021Article
- Identification and Validation of Key Genes in Hepatocellular Carcinoma by Bioinformatics Analysis.BioMed research international · 2021Article
- Identification of 40S ribosomal protein S8 as a novel biomarker for alcohol‑associated hepatocellular carcinoma using weighted gene co‑expression network analysis.Oncology reports · 2020Observational
- Identification of Key Biomarkers in Bladder Cancer: Evidence from a Bioinformatics Analysis.Diagnostics (Basel, Switzerland) · 2020Article
- Bioinformatics Analysis based on Multiple Databases Identifies Hub Genes Associated with Hepatocellular Carcinoma.Current genomics · 2019Article
- MicroRNA‑181c suppresses growth and metastasis of hepatocellular carcinoma by modulating NCAPG.Cancer management and research · 2019Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide. However, the precise mechanisms of the development and progression of HCC remain unclear. The present study attempted to identify and functionally analyze the differentially expressed genes between HCC and cirrhotic tissues by using comprehensive bioinformatics analyses.
methodsThe GSE63898 gene expression profile was downloaded from the Gene Expression Omnibus (GEO) and analyzed using the online tool GEO2R to identify differentially expressed genes (DEGs). Gene ontology (GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the DEGs were performed in DAVID. The STRING database was used to evaluate the interactions of DEGs and to construct a protein-protein interaction (PPI) network using Cytoscape software. Hub genes were selected using the cytoHubba plugin and were validated with the cBioPortal database.
resultsA total of 301 DEGs were identified between HCC and cirrhotic tissues. The GO analysis results showed that these DEGs were significantly enriched in certain biological processes including negative regulation of growth and cell chemotaxis. Several significant pathways, including the p53 signaling pathway, were identified as being closely associated with these DEGs. The top 12 hub genes were screened and included TTK, NCAPG, TOP2A, CCNB1, CDK1, PRC1, RRM2, UBE2C, ZWINT, CDKN3, AURKA, and RACGAP1. The cBioPortal analysis found that alterations in hub genes could result in significantly reduced disease-free survival in HCC.
conclusionThe present study identified a series of key genes and pathways that may be involved in the tumorigenicity and progression of HCC, providing a new understanding of the underlying molecular mechanisms of carcinogenesis in HCC.
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