Comprehensive Analysis of the Expression and Prognosis for Lipid Metabolism-Related Genes in Hepatocellular Carcinoma

Background This study aimed to screen potential key genes associated with lipid metabolism and to evaluate their expressions and prognosis values in hepatocellular carcinoma (HCC). Methods Data sets GSE6764, GSE14520, and GSE112790 were used to identify the common differentially expressed genes (DEGs). Protein-protein interaction (PPI) network was constructed by STRING database. Hub genes in PPI network were identified and subjected to functional enrichment analysis to screen lipid metabolism-related genes. The expressions of selected genes and their associations with prognosis were analyzed using UALCAN, The Human Protein Atlas, and Kaplan-Meier plotter databases. The transcriptional factor (TF)-gene regulatory network was constructed using NetworkAnalyst. Results A total of 331 common DEGs including 106 upregulated and 225 downregulated genes were identified. PPI network analysis showed that 76 genes with high degrees were identified as hub genes, among which 14 genes were lipid metabolism-related genes. PON1, CYP2C9, and SPP1 were found to be the independent prognostic markers. Key TFs with close interactions with these prognostic genes, including HINFP, SRF, YY1, and NR3C1, were identified from the TF-gene regulatory network. Conclusion This study presented evidence for the prognostic capabilities of lipid metabolism-related genes in HCC, and newly identified HINFP and NR3C1 as potential biomarkers for HCC.