Bioinformatic Analysis of GCN1 as a Novel Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma and Preliminary Exploration of Its Molecular Mechanisms

Min Wei, Chengming Ke, Sumin Wu — Wed, 30 Jul 2025 00:00:00 +0000

Background: Hepatocellular carcinoma (HCC) faces significant challenges in early diagnosis and prognostic assessment, necessitating novel molecular biomarkers. The role of GCN1 in tumorigenesis remains unclear, warranting systematic investigation of its clinical value. Methods:Utilizing multi-omics data from 164 HCC patients in the TCGA database, we comprehensively evaluated the diagnostic and prognostic value of GCN1 through differential expression analysis, Cox proportional hazards regression, and gene set enrichment analysis (GSEA). Results: GCN1 expression was significantly upregulated in tumor tissues (P<0.001), with ROC analysis demonstrating an AUC of 0.921 (95% CI: 0.893-0.950) for discriminating tumor from normal tissue. Clinical correlation analysis revealed that high GCN1 expression significantly associated with advanced T stage (OR=1.941, P=0.002) and AFP levels >400 ng/ml (OR=3.697, P<0.001). Multivariate survival analysis confirmed its independent prognostic value (HR=1.454, P=0.038). Functional analysis indicated GCN1 promotes tumor progression by regulating cell cycle (NES=2.385) and axon guidance (NES=2.307) pathways. Conclusion:This study first elucidates the dual clinical value of GCN1 in HCC, providing a theoretical foundation for developing novel diagnostic biomarkers and prognostic evaluation systems. Future research should validate its molecular mechanisms and explore potential targeted therapies.

World Journal of Cancer and Oncology Research

Bioinformatic Analysis of GCN1 as a Novel Diagnostic and Prognostic Biomarker in Hepatocellular Carcinoma and Preliminary Exploration of Its Molecular Mechanisms