ArticleAnnals of translational medicine2021
Identification of genes predicting unfavorable prognosis in hepatitis B virus-associated hepatocellular carcinoma.
Article in Annals of translational medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Identification of RAD51AP1 as a key gene in hepatitis B virus-associated hepatocellular carcinoma.Heliyon · 2025Article
- Statistical and machine learning based platform-independent key genes identification for hepatocellular carcinoma.PloS one · 2025Article
- Role of Epigenetic Factors in Determining the Biological Behavior and Prognosis of Hepatocellular Carcinoma.Diagnostics (Basel, Switzerland) · 2024Article
- Construction and validation of a joint diagnosis model based on random forest and artificial intelligence network for hepatitis B-related hepatocellular carcinoma.Translational cancer research · 2024Article
- [Screening and validation of pivotal genes in hepatitis B virus-associated hepatocellular carcinoma].Zhonghua gan zang bing za zhi = Zhonghua ganzangbing zazhi = Chinese journal of hepatology · 2023Article
- Differentially expressed discriminative genes and significant meta-hub genes based key genes identification for hepatocellular carcinoma using statistical machine learning.Scientific reports · 2023Article
- Construction and validation of prognostic signature for hepatocellular carcinoma basing on hepatitis B virus related specific genes.Infectious agents and cancer · 2022Article
- LncRNA TP53TG1 Promotes the Growth and Migration of Hepatocellular Carcinoma Cells via Activation of ERK Signaling.Non-coding RNA · 2021Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundTo identify potential key genes predicting unfavorable prognosis in hepatitis B virus (HBV)-associated hepatocellular carcinoma (HCC).
methodsGene expression profiles of GSE121248, GSE62232, and GSE55092 from the GEO database were obtained and analyzed. Differentially expressed genes (DEGs) between HBV-associated HCC tissues and adjacent normal tissues were screened by the limma package and Venn diagram software. Functional assessment of DEGs was performed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Hub genes were selected by the protein-protein interaction (PPI) network and further validated by GSE14520 clinical data.
resultsA total of 26 up-regulated genes and 76 down-regulated genes were identified by analyzing three databases. GO and KEGG analysis demonstrated that these genes were involved in cell division, metabolism-related biological processes, the p53 pathway, and the cell cycle, among others. PPI network suggested that 14 hub DEGs (
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