ArticleJournal of gastrointestinal oncology2022
Identification of potential prognostic biomarkers for hepatocellular carcinoma.
Article in Journal of gastrointestinal oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Development of a four-gene prognostic signature for hepatocellular carcinoma using TCGA and GEO datasets.Discover oncology · 2026Article
- Unraveling risk factors and transcriptomic signatures in liver cancer progression and mortality through machine learning and bioinformatics.Briefings in functional genomics · 2026Article
- Identification of acetylshikonin as a novel tubulin polymerization inhibitor with antitumor activity in human hepatocellular carcinoma cells.Journal of gastrointestinal oncology · 2023Article
- Identification of potential prognostic biomarkers among gene models for coiled-coil domain-containing family members in hepatocellular carcinoma elucidates their influence on the hypoxia pathway and immune microenvironment.Journal of gastrointestinal oncology · 2023Article
- Identification of tumor antigens and immune subtypes of hepatocellular carcinoma for mRNA vaccine development.World journal of gastrointestinal oncology · 2023Article
- Development of a prognostic model for anoikis and identifies hub genes in hepatocellular carcinoma.Scientific reports · 2023Article
- Identification of glutamyl-prolyl-tRNA synthetase as a new therapeutic target in hepatocellular carcinoma via a novel bioinformatic approach.Journal of gastrointestinal oncology · 2023Article
- [Construction and verification of a prognostic model combining anoikis and immune prognostic signatures for primary liver cancer].Nan fang yi ke da xue xue bao = Journal of Southern Medical UniversityArticle
- Identification of Prognostic Gene Signatures for Survival of Patients With Phaeochromocytoma, Paraganglioma, and Other Tumor Types.Cancer diagnosis & prognosisArticle
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: The incidence of liver cancer is increasing every year. Hepatocellular carcinoma (HCC) accounts for nearly 90% of liver cancer, and the overall 5-year survival rate of become of Hepatocellular carcinoma patients less than 20%. However, the molecular mechanism of HCC progression and prognosis still requires further exploration. Methods: In this study, we downloaded the gene expression data from the Cancer Genome Atlas (TCGA) Genomic Data and the official website of GEO database. Weighted gene co-expression network analysis (WGCNA) and Pearson's correlation coefficient were utilized to detect the gene modules. The shared differentially-expressed genes (DEGs) were screened out by a Venn diagram, and the hub genes were identified through protein-protein interaction (PPI) network analyses. GO and KEGG enrichment analyses were constructed for these hub genes. Overall survival (OS) and correlation analysis were conducted to investigate the relationship between the hub genes and clinical features. Results: We screened out 27 shared DEGs, and the mainly enriched GO terms were mitotic nuclear division, chromosomal region, and tubulin binding. Furthermore, the top three enriched KEGG pathways were "cell cycle", "oocyte meiosis", and "p53 signaling pathway". According to the Maximal Clique Centrality (MCC) algorithm, the top 10 candidate hub genes were Conclusions: Three hub genes (
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