Gene Expression Profiling of Advanced Stage Hepatocellular Carcinoma: A Bioinformatic Analysis

This study aims to examine and explain genetic expression, important genetic markers, and how the immune system interacts with tumors in the advanced stage of hepatocellular carcinoma (HCC). We obtained datasets from the Gene Expression Omnibus (GEO) database consisting of 135 HCC patients. Datasets containing at least 100 significant genes determined by volcano plot analysis were utilized. Differentially expressed genes (DEGs) were analyzed by GEO2R. Protein-protein interaction (PPI) networks were built by STRING and Cytoscape. Crucial genes were determined by Network Analyzer and CytoHubba based on four centrality parameters (degree, betweenness, closeness, stress). Gene Ontology, KEGG, and Reactome enrichment analyses were performed to explore the underlying biochemical processes and tumor-immune interaction. We obtained 3,314 DEGs from two datasets, 75 of which overlapped. The STRING database recognized 63 genes to form PPI (p-value=0.0143). Among them, 13 genes were determined as crucial gene candidates. The action map revealed a significant interaction between 11 of them. Gene enrichment (p-value <0.05) showed biochemical processes involving crucial genes related to advanced-stage HCC, including antioxidant activity, longevity regulating pathways, and reduced oxidized thioredoxin. After enrichment analysis, TXNRD1 and NQO1 were identified as the most crucial genes and may serve as biomarkers and be involved in treatment strategies for patients with advanced-stage liver cancer. Both genes also showed a positive correlation with neutrophil infiltration (p-value <0.001). TXNRD1, NQO1, and their related pathways showed potential as biomarkers and therapeutic targets for advanced-stage HCC.