Identification of 5 Hub Genes Related to the Early Diagnosis, Tumour Stage, and Poor Outcomes of Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34603487", "kind": "science-record", "revision": 7, "content_hash": "sha256:c6a3671f1fa3549a0eaefdc3ec5d0d02e6ba3e8f1293bff035da6ececb8000bb", "created_at": "2026-11-01T15:41:55Z", "updated_at": "2026-11-01T22:04:52Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of 5 Hub Genes Related to the Early Diagnosis, Tumour Stage, and Poor Outcomes of Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis.", "doi": "10.1155/2021/9991255", "pmid": "34603487", "authors": ["Rui Qiang", "Zitong Zhao", "Lu Tang", "Qian Wang", "Yanhong Wang", "Qian Huang"], "journal": "Computational and mathematical methods in medicine", "year": 2021, "abstract": "BACKGROUND: The majority of primary liver cancers in adults worldwide are hepatocellular carcinomas (HCCs, or hepatomas). Thus, a deep understanding of the underlying mechanisms for the pathogenesis and carcinogenesis of HCC at the molecular level could facilitate the development of novel early diagnostic and therapeutic treatments to improve the approaches and prognosis for HCC patients. Our study elucidates the underlying molecular mechanisms of HBV-HCC development and progression and identifies important genes related to the early diagnosis, tumour stage, and poor outcomes of HCC.\nMETHODS: GSE55092 and GSE121248 gene expression profiling data were downloaded from the Gene Expression Omnibus (GEO) database. There were 119 HCC samples and 128 nontumour tissue samples. GEO2R was used to screen for differentially expressed genes (DEGs). Volcano plots and Venn diagrams were drawn by using the ggplot2 package in R. A heat map was generated by using Heatmapper. By using the clusterProfiler R package, KEGG and GO enrichment analyses of DEGs were conducted. Through PPI network construction using the STRING database, key hub genes were identified by cytoHubba. Finally, KM survival curves and ROC curves were generated to validate hub gene expression.\nRESULTS: By GO enrichment analysis, 694 DEGs were enriched in the following GO terms: organic acid catabolic process, carboxylic acid catabolic process, carboxylic acid biosynthetic process, collagen-containing extracellular matrix, blood microparticle, condensed chromosome kinetochore, arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. In the KEGG pathway enrichment analysis, DEGs were enriched in arachidonic acid epoxygenase activity, arachidonic acid monooxygenase activity, and monooxygenase activity. By PPI network construction and analysis of hub genes, we selected the top 10 genes, including CDK1, CCNB2, CDC20, BUB1, BUB1B, CCNB1, NDC80, CENPF, MAD2L1, and NUF2. By using TCGA and THPA databases, we found five genes, CDK1, CDC20, CCNB1, CENPF, and MAD2L1, that were related to the early diagnosis, tumour stage, and poor outcomes of HBV-HCC.\nCONCLUSIONS: Five abnormally expressed hub genes of HBV-HCC are informative for early diagnosis, tumour stage determination, and poor outcome prediction.", "claims": [{"id": "claim-method", "statement": "The expression of hub genes in liver tumour samples and adjacent normal samples was compared using the Wilcoxon rank-sum test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34603487", "locator": "sections[7] \"2.5. 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