Predicting the Impact of ARHGAP33 Gene on Liver Cancer Prognosis Based on Multi-Algorithm Model

Objective: To investigate the impact of Rho GTPase-activating protein 33 (ARHGAP33) and its synergistic interaction with SFPQ on the prognosis of hepatocellular carcinoma (HCC) through bioinformatics and experimental research. Materials and Methods: RNA sequencing data from The Cancer Genome Atlas (TCGA) were analyzed to assess ARHGAP33 expression in hepatocellular carcinoma (HCC). Co-expressed genes were identified using WGCNA and GSVA, and integrated into a multi-algorithm consensus prognostic model. Results: The analysis of the TCGA database indicated a marked overexpression of ARHGAP33 mRNA in tissues from hepatocellular carcinoma (LIHC), with a statistically significant finding (P < 0.001). WGCNA revealed that SFPQ is a gene associated with ARHGAP33. In the developed consensus prognostic model, survival analysis using Kaplan-Meier (K-M) alongside the CoxBoost model demonstrated that the overall survival time for patients classified as high-risk was significantly less than that of those classified as low-risk (P < 0.05).The Institutional Review Board at Shihezi University granted ethical approval for this research (Ethics Application No.: KJ2025-290-01). Conclusion: The expression level of ARHGAP33 affects HCC prognosis, and its synergistic overexpression with SFPQ impairs the prognosis of HCC patients. ARHGAP33 could potentially be used as a biomarker for evaluating prognosis in hepatocellular carcinoma (HCC), offering a new theoretical foundation for enhancing HCC outcomes.