Prognostic significance and immune-related prediction of proteomic features in hepatocellular carcinoma

Abstract Background: Hepatocellular carcinoma (HCC) is the most prevalent primary liver malignancy, characterized by high metastasis and recurrence rates. Proteins play essential roles in the progression of HCC; however, their prognostic significance remains unclear. This study aimed to analyze proteomic features associated with HCC prognosis and to develop a multi-protein-based prognostic model. Methods: Protein expression data were obtained from The Cancer Proteome Atlas (TCPA) and clinical information from The Cancer Genome Atlas (TCGA). Prognostic proteins were identified using Cox regression and Kaplan-Meier analysis. A prognostic model was constructed based on three proteins: AKT, BRAF, and P27_pT198. Model performance was assessed via survival analysis, ROC curves, and immune infiltration analysis. Immunohistochemistry (IHC), protein-protein interaction (PPI), and functional enrichment analyses were performed to explore expression patterns and biological significance. Results: The risk model stratified patients into high- and low-risk groups with significantly different overall survival. ROC analysis demonstrated moderate predictive power. Functional annotation revealed the model proteins were involved in pathways such as PI3K-AKT and MAPK signaling. The proteins were also associated with immune cell infiltration and immune modulators in HCC. Conclusion: AKT, BRAF, and P27_pT198 may serve as potential biomarkers and therapeutic targets in HCC. The proposed model offers clinical utility for prognostic evaluation and may support treatment decision-making.