BACKGROUND

Hepatocellular carcinoma (HCC)-a predominant type of primary liver cancer-poses a significant global health threat with high incidence and mortality rates. Despite advances in treatment modalities, including surgery, chemotherapy, and immunotherapy, HCC exhibits high relapse rates and low long-term survival, necessitating the identification of novel prognostic markers and treatment targets. This study aims to develop a prognostic model centered on the PDZ domain by identifying key PDZ proteins associated with HCC through bioinformatics analysis of large-scale public datasets, in order to improve prognosis prediction and inform therapeutic strategies.

METHODS

Differentially expressed PDZ proteins (DEPs) in HCC were identified through RNA sequencing (RNA-seq) analysis from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and Gene Expression Omnibus (GEO) databases. Cox regression and random survival forest (RSF) modeling were employed to construct a prognostic model and evaluate the prognostic potential of DEPs. Subsequently, the correlation of DEP-related risk scores with immune cell infiltration and genetic variations was analyzed separately. Quantitative polymerase chain reaction (qPCR) was conducted to validate the expression of key DEPs in HCC tissues.

RESULTS

A prognostic model for HCC constructed using nine key DEPs demonstrated reliable predictive performance across 1-, 3-, and 5-year survival rates. DEP-related risk scores were significantly associated with immune cell infiltration, with high-risk groups exhibiting an increase in pro-tumor immune cells and a decrease in anti-tumor immune cells. Genetic variations, including single nucleotide polymorphisms (SNPs) and copy number variations (CNVs), also differed between high- and low-risk groups. qPCR validation confirmed that the expression of SNX27, DLG5, PARD3, and RHPN1 was significantly upregulated in HCC tissues.

CONCLUSIONS

PDZ proteins may serve as prognostic markers and therapeutic targets in HCC. DEP-related risk scores offer insights into immune infiltration patterns and treatment responsiveness, providing a foundation for future HCC research and development of precision medicine.