Systems biology investigation of epithelial-mesenchymal transition in hepatocellular carcinoma pathogenesis

Hepatocellular carcinoma (HCC) is a malignancy showing rising prevalence and mortality rates despite scientific progress. Studies indicate that Epithelial-Mesenchymal Transition (EMT) may be involved in the increased mortality among HCC patients. Therefore, the objective of our study was to identify and analyze EMT-related genes in HCC using publicly available datasets and bioinformatics tools. We obtained a total of 1184 genes known to be linked to EMT in humans from the dbEMT2 database. Two gene expression datasets, GSE36376 and GSE39791 were acquired from the GEO database. Using GEO2R online software, differentially expressed genes (DEGs) were identified based on log fold change and statistical significance. The intersection of up-regulated, down-regulated, and EMT-related genes from dbEMT2 comprised the final list of EMT-associated DEGs. Functional enrichment analysis was conducted using the Enrichr tool. Protein-protein interaction (PPI) analysis was performed using the STRING database, and hub genes were identified using the CytoHubba plugin in Cytoscape. The diagnostic potential of hub genes was assessed at both the mRNA and protein levels using UALCAN software, and survival analysis was conducted to evaluate their prognostic significance. The analysis revealed 13 up-regulated and 13 down-regulated EMT-associated DEGs in HCC samples. Functional enrichment analysis indicated their involvement in key biological processes, molecular functions, cellular components, and critical pathways such as the Pentose Phosphate Pathway. PPI analysis identified four hub genes consistently recognized by degree, closeness, and betweenness centralities: BIRC5, CCNA2, AURKA, and EZH2. These hub genes demonstrated significant diagnostic potential, with higher expression levels in HCC patients compared to healthy individuals at the mRNA level. Furthermore, survival analysis revealed their association with decreased patient survival, suggesting their potential as prognostic biomarkers in HCC. Our study provides comprehensive insights into the EMT-related genes associated with HCC using a bioinformatics approach. The findings contribute to a better understanding of EMT-related mechanisms in HCC and may guide future research in developing targeted therapeutic strategies. [Display omitted]