ArticleMedical science monitor : international medical journal of experimental and clinical research2020
Identification of Hub Genes in Hepatocellular Carcinoma Related to Progression and Prognosis by Weighted Gene Co-Expression Network Analysis.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 8 citations in OpenAlex.
- Identification and experimental validation of biomarkers associated with the endocannabinoid system in major depressive disorder.Hereditas · 2025Article
- Cross-border regulation of the STK39/MAPK14 pathway by Lycium barbarum miR166a to inhibit triple-negative breast cancer.American journal of translational research · 2024Article
- Network pharmacology-based study on apigenin present in the methanolic fraction of leaves extract of Cestrum nocturnum L. to uncover mechanism of action on hepatocellular carcinoma.Medical oncology (Northwood, London, England) · 2022Article
- Article
- Identification and Validation of Hub Genes Associated With Hepatocellular CarcinomaFrontiers in oncology · 2021Article
- RPL19 Is a Prognostic Biomarker and Promotes Tumor Progression in Hepatocellular Carcinoma.Frontiers in cell and developmental biology · 2021Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Hepatocellular carcinoma (HCC) is one of the most prevalent cancers in the world. Bioinformatics studies have been widely used for screening genes involved in the initiation and progression of HCC. MATERIAL AND METHODS We obtained liver cancer microarray raw data from the GEO database (GSE54238). Next, weighted gene co-expression network analysis (WGCNA) was used to assess the critical modules. Then, we assessed the gene significance by calculating survival, expression level, and receiver operating characteristic (ROC) in the TCGA database. We also validated the expression of selected genes in the Oncomine database and calculated the relationship between 4 hub genes and immune infiltration. Finally, GSEA enrichment analysis was used to explore the potential mechanism. RESULTS We identified the red and blue modules as the critical modules, and found 176 candidate genes by assessing gene significance. GO and KEEG results suggested that the candidate genes are involved in the cell cycle. Four hub genes - SOX4, STK39, TARBP1, and TDRKH - were eventually screened after validating their expression and power in diagnosing HCC in the TCGA database. Immune infiltration analysis and GSEA enrichment analysis showed that these 4 hub genes were correlated with the immune cell populations infiltration and that multiple mechanisms were involved, such as angiogenesis and epithelial-mesenchymal transition. CONCLUSIONS Our findings revealed that these 4 genes can be regarded as potential prognosticators and therapeutic targets for HCC.
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