ArticleCancer biomarkers : section A of Disease markers2022
Identification and validation of real hub genes in hepatocellular carcinoma based on weighted gene co-expression network analysis.
Article in Cancer biomarkers : section A of Disease markers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed, 4 citations in OpenAlex.
- The role of kinesin family members in hepatobiliary carcinomas: from bench to bedside.Biomarker research · 2024Review
- The neurological and non-neurological roles of the primary microcephaly-associated protein ASPM.Frontiers in neuroscience · 2023Review
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHepatocellular carcinoma (HCC) is one of the most common liver malignancies in the world. With highly invasive biological characteristics and a lack of obvious clinical manifestations, hepatocellular carcinoma usually has a poor prognosis and ranks fourth in cancer mortality. The etiology and exact molecular mechanism of primary hepatocellular carcinoma are still unclear.
objectiveThis work aims to help identify biomarkers of early HCC diagnosis or prognosis based on weighted gene co-expression network analysis (WGCNA).
methodsExpression data and clinical information of HTSeq-Counts were downloaded from The Cancer Genome Atlas (TCGA) database, and gene expression map GSE121248 was downloaded from Gene Expression Omnibus (GEO). By differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) searched for modules in the two databases that had the same effect on the biological characteristics of HCC, and extracted the module genes with the highest positive correlation with HCC from two databases, and finally obtained overlapping genes. Then, we performed functional enrichment analysis on the overlapping genes to understand their potential biological functions. The top ten hub genes were screened according to MCC through the string database and Cytoscape software and then subjected to survival analysis.
resultsHigh expression of CDK1, CCNA2, CDC20, KIF11, DLGAP5, KIF20A, ASPM, CEP55, and TPX2 was associated with poorer overall survival (OS) of HCC patients. The DFS curve was plotted using the online website GEPIA2. Finally, based on the enrichment of these genes in the KEGG pathway, real hub genes were screened out, which were CDK1, CCNA2, and CDC20 respectively.
conclusionsHigh expression of these three genes was negatively correlated with survival time in HCC, and the expression of CDK1, CCNA2, and CDC20 were significantly higher in tumor tissues of HCC patients than in normal liver tissues as verified again by the HPA database. All in all, this provides a new feasible target for early and accurate diagnosis of HCC, clinical diagnosis, treatment, and prognosis.
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