Identification of PC4 as a diagnostic and prognostic biomarker in hepatocellular carcinoma

Abstract

Background Human positive cofactor 4 (PC4) is associated with the development and therapeutic resistance of several malignancies. Nonetheless, the role of PC4 in HCC remains obscure, warranting further investigation. Methods PC4 differential expression between HCC and normal tissues and its association with the clinicopathological characteristics of HCC patients were explored in the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets. Subsequently, the prognostic and diagnostic significance of PC4 in HCC patients was analyzed. Functional enrichment analyses were conducted by Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene set enrichment analysis (GSEA) analysis to explore the biological functions of PC4. The CIBERSORT algorithm was used for immune infiltration analysis. The risk signature based on PC4-related genes was constructed by LASSO-COX regression and validated with the International Cancer Genome Consortium (ICGC) dataset. The qRT-PCR was used to verify the expression levels of all genes. Tumor Immune Dysfunction and Exclusion (TIDE) analysis evaluated the correlation between PC4 level and risk score and immunotherapy response in HCC patients. Finally, based on online databases, PC4-related ceRNA networks were constructed to explore the regulatory mechanism of PC4 in HCC. Results PC4 levels were significantly upregulated in HCC compared to normal tissues and positively correlated with the pathological grade and clinical stage. The PC4-high expression group showed a worse prognosis. In addition, PC4 could help distinguish tumor tissues from normal ones with an area under the curve (AUC) 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 (Risk score = 0.074*CEP55 + 0.091*TRIP13 + 0.100*BRIX1 + 0.081*STIP1 + 0.191*PIGU + 0.038*CFL1 + 0.017*RBM17 + 0.178*OLA1) was strongly correlated with HCC patient prognosis and was considered as an independent prognostic factor. TIDE analysis showed that patients in both the PC4-low and low-risk groups were more likely to benefit from immunotherapy. Finally, the lncRNAs/miRNA-101-3p/PC4 network was constructed. Conclusion We confirmed PC4 as a diagnostic and prognostic marker in HCC patients. And, we developed and validated an 8-gene risk signature, which could help for clinical decision-making. The CeRNA network could help explore the regulatory mechanism of the PC4 gene in HCC.