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Background Hepatocellular carcinoma (HCC) is a common and lethal liver cancer primarily associated with viral infections like hepatitis B virus (HBV) and hepatitis C virus (HCV), as well as non-viral causes. Understanding the molecular mechanisms of these subtypes is essential for identifying potential biomarkers and therapeutic targets. Methods In this study, an integrated bioinformatics approach was used to analyze publicly available datasets related to HBV-associated, HCV-associated, and non-viral HCC. Functional enrichment analyses and protein–protein interaction (PPI) networks were constructed to identify key hub genes. Results Our analysis identified dysregulated genes across all HCC subtypes. Among these, GPC3 and SPARCL1 were significantly upregulated, while ALB and HNF4α were downregulated, and are involved in critical cancer pathways such as Wnt, PI3K/Akt, and p53 signaling. Functional analysis linked these DEGs to essential processes in tumorigenesis, including cell cycle regulation and immune modulation. Notably, SPARCL1 has been identified as a potential inhibitor of SPP1 , a key driver of HCC. Validation using databases such as GEPIA and TNMplot confirmed the dysregulation of these genes in numerous HCC tissue samples and their significant association with patient prognosis. Conclusion This study provides a comprehensive overview of HCC pathogenesis by suggesting a shared gene profile between viral and non-viral forms, paving the way for universal diagnostic markers and targeted therapies while highlighting the need for further experimental validation to advance precision medicine in HCC.
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Zamanian et al. (2026) studied this question.
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