Human positive cofactor 4 (PC4) is associated with the development and therapeutic resistance of several malignancies. However, the role of PC4 in hepatocellular carcinoma (HCC) remains obscure.

The expression status of PC4 was explored in Gene Expression Omnibus and The Cancer Genome Atlas datasets. Subsequently, the prognostic and diagnostic significance of PC4 in HCC patients was analyzed. Functional enrichment analyses were conducted to explore biological functions and potential mechanisms. The CIBERSORT algorithm was used for immune infiltration analysis. The risk signature was constructed by LASSO-Cox regression and was validated with the International Cancer Genome Consortium dataset. Quantitative real-time polymerase chain reaction was used to verify the expression levels of all genes. Tumor Immune Dysfunction and Exclusion analysis evaluated immunotherapy response. Finally, using online databases, PC4-related competing endogenous RNA networks were constructed.

PC4 levels were significantly upregulated in HCC and positively correlated with the pathological grade and clinical stage. The PC4-high expression group showed worse prognosis. In addition, PC4 could distinguish between tumor and normal tissues with an area under the curve of 0.965. The PC4 level was associated with immune checkpoints and immune cell infiltration. In the training and validation sets, the eight-gene risk signature strongly correlated with HCC patient prognosis. Tumor Immune Dysfunction and Exclusion analysis showed that patients in both the PC4-low and low-risk groups were more likely to benefit from immunotherapy. Finally, an lncRNA/microRNA-101-3p/PC4 network was constructed.

We confirmed PC4 as a diagnostic and prognostic biomarker in HCC patients. We also developed and validated an eight-gene risk signature, which will help in clinical decision-making. The competing endogenous RNA network could help explore the regulatory mechanisms of PC4 in HCC.