ArticleInternational journal of general medicine2022
Identification and Validation of Hub Genes with Poor Prognosis in Hepatocellular Carcinoma by Integrated Bioinformatical Analysis.
Article in International journal of general medicine, 2022. 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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6 citing papers in PubMed, 5 citations in OpenAlex.
- Development of a four-gene prognostic signature for hepatocellular carcinoma using TCGA and GEO datasets.Discover oncology · 2026Article
- Uncovering Prognostic Biomarkers Underlying Hepatocellular Carcinoma Through Integrative Multi-Omics and a Network-Based Approach.International journal of molecular sciences · 2026Article
- The role of Aurora kinase A in hepatocellular carcinoma: Unveiling the intriguing functions of a key but still underexplored factor in liver cancer.Cell proliferation · 2024Review
- Construction and validation of a prognosis signature based on the immune microenvironment in gastric cancer.Frontiers in surgery · 2023Article
- Comprehensive pan-cancer analysis and the regulatory mechanism of AURKA, a gene associated with prognosis of ferroptosis of adrenal cortical carcinoma in the tumor micro-environment.Frontiers in genetics · 2022Article
- Identification of Prognostic Gene Signatures for Survival of Patients With Phaeochromocytoma, Paraganglioma, and Other Tumor Types.Cancer diagnosis & prognosisArticle
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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
Background: Hepatocellular carcinoma (HCC) is the reason for the world's second largest cancer-related death. It is clinically valuable to study the molecular mechanisms of HCC occurrence and development for formulating more effective diagnosis and treatment strategies. Methods: The five microarray data sets GSE45267, GSE101685, GSE84402, GSE62232 and GSE45267 were downloaded from Gene Expression Omnibus (GEO) database, including 165 HCC tissues and 73 normal tissues. Differential expressed genes (DEGs) between HCC tissues and normal tissues were determined by GEO2R. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and the protein-protein interaction network (PPI) network analysis were employed to identify DEGs and to evaluate the clinical significance in prognosis of HCC. Results: A total of 152 genes differentially expressed in HCC tissues and normal tissues were identified. GO and KEGG functional enrichment analysis revealed that 39 up-regulated genes were mainly enriched in mitosis, cell cycle and oocyte meiosis, while those down-regulated genes (113) were concentrated in exogenous drug catabolism and the metabolism of cytochrome P450 on exogenous drugs. Totally, 19 hub genes were chosen by PPI network and module analysis and verified by The Cancer Genome Atlas (TCGA) database. Finally, 8 hub genes were selected, including CDK1, CYP2C8, CCNB1, AURKA, CYP2C9, BUB1B, MAD2L1 and TTK, which were associated with the overall survival rate of HCC patients. Conclusion: This study presented eight target genes connected to the prognosis of HCC patients. Those mainly exists in cell cycle and drug catabolism, which may be latent targets for clinical treatment.
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