Key hub genes and pathways associated with HCV-related hepatocellular carcinoma as potential diagnostic biomarkers.

Authors

Elham Karimi, Niloufar Sadat Kalaki, Mahnaz Shavandi, Fargol Mahlouji, Abed El Hasan Haidar, Aria Abedi Asl, Fahimeh Safarnezhad Tameshkel, Farhad Zamani, Mohammad Hadi Karbalaie Niya

Published in

Journal, genetic engineering & biotechnology. Volume 24. Issue 3. Pages 100721. Epub Jun 11, 2026.

Abstract

Hepatitis C virus (HCV)-related hepatocellular carcinoma (HCC) remains a major global health challenge, with high morbidity and mortality despite recent therapeutic advances. Early detection and identification of reliable molecular biomarkers are essential to improve patient outcomes. Therefore, the present study aimed to investigate key hub genes and pathways associated with HCV-related HCC as potential diagnostic biomarkers.
The datasets GSE69715 and GSE62232 were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were recognized according to an adjusted p-value and a log fold change (logFC). The GEO2R tool facilitated the identification of common DEGs across the two datasets. Pathways were explored using the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) databases. Furthermore, protein-protein interactions (PPIs) were assessed through Cytoscape. The target genes were confirmed through a GEPIA analysis.
A total of 421 common DEGs were identified, and 80 hub genes were subsequently determined through GEO and PPI network analyses, respectively. The GO and KEGG pathways analysis presented DEGs were enhanced in metabolic pathways, cellular components, extracellular exosome, detoxification of copper ion and monooxygenase activity. The GEPIA analysis indicated a notable variation in the expression levels of four specific genes -CDKN2A, CDK1, CCNB1, and TOP2A-when comparing normal samples to tumor samples.
The present study discovered novel genes by expression variation in HCV-related hepatocellular carcinoma development. These findings suggest that CDKN2A, CDK1, CCNB1, and TOP2A are promising candidates for diagnostic biomarkers and present a valuable opportunity for the early identification of HCV-HCC, which could lead to improved treatment outcomes.

PMID:
42749402
Bibliographic data and abstract were imported from PubMed on 17 Sep 2026.

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