Background: Hepatocellular carcinoma (HCC) is globally recognized as one of the most frequently occurring primary malignant liver tumor, making the identification of HCC biomarkers critically important. Methods: The gene expression and clinicopathology analysis, GO enrichment analysis (GSEA) and immune infiltration analysis are based on data obtained from The Cancer Genome Atlas (TCGA), with additional bioinformatics analyses performed. The statistical analysis was conducted in R. The

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... otein interaction (PPI) networks was constructed and the module analysis was performed using STRING and Cytoscape. Construction and evaluation of prognostic model based on PDRG1 and tumor status used nomogram and calibration.Results: The expression of PDRG1 was significantly higher in HCC tumor tissues. High expression of PDRG1 in HCC patients was significantly correlated with poor Overall Survival and adverse clinicopathological features including advanced T stage, residual tumor, histologic grade, vascular invasion, TP53 status and AFP level. GO, GSEA revealed that PDRG1 was closely correlated with DNA repair, DNA replication and cell cycle. Spearman correlation showed high expression of PDRG1 was significantly correlated with Th2 cells level in HCC patients. Nomograms based on PDRG1 and tumor stage had good predictive performance on overall survival rates of HCC patients.Conclusions: Our study demonstrated the potential significance of PDRG1 expression in the diagnosis and prognosis of HCC and further explored the function in HCC. Further study is still needed to confirm these results. The underlying mechanism revealed by these results provides a basis for PDRG1 as a new molecular target for the prevention and treatment of HCC.