Establishment of a prognostic model for hepatocellular carcinoma patients based on bioinformatics analysis and exploration of prognostic biomarker EPPK1

Hepatocellular carcinoma (HCC) poses a significant global health challenge, and its complex and diverse pathogenesis requires further in-depth investigation. With the development of bioinformatics, omics sequencing has become an indispensable detection tool for dissecting the complex molecular characteristics of diseases. We analyzed the transcriptomic and proteomic data from TCGA-LIHC and identified a prognosis-related gene, EPPK1. Subsequently, validation by single-cell sequencing revealed that EPPK1 is specifically highly expressed in HCC cells. Further combined analysis of immune infiltration and spatial transcriptomics indicated that high EPPK1 expression is associated with various immune cells, particularly showing a negative correlation with CD8 + T cells. Enrichment analysis of EPPK1-related transcriptomic data demonstrated that EPPK1 is involved in pathways such as cell cycle and apoptosis of HCC. We employed virtual perturbation technology to predict the potential downstream pathways associated with EPPK1. Finally, in vitro functional experiments confirmed that EPPK1 promotes the malignant progression of HCC cells. Our study suggests that EPPK1 is a promising diagnostic and prognostic biomarker in HCC.