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已发表论文
基于多算法模型预测 ARHGAP33 基因对肝癌预后的影响
Authors Zhao Y, Wang C, Shen X, Cao X, Wang Z, Jiang H, Chen X, Wu X
Received 30 September 2025
Accepted for publication 14 December 2025
Published 10 January 2026 Volume 2026:19 571357
DOI https://doi.org/10.2147/IJGM.S571357
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Dana Kristjansson
Yaohui Zhao,1– 3,* Chenjie Wang,1– 3,* Xiaotong Shen,1– 3 Xinhui Cao,1– 3 Zi Wang,1– 3 Huijiao Jiang,1– 3 Xueling Chen,1– 3 Xiangwei Wu1– 4
1School of Medicine, Shihezi University, Shihezi, 832000, People’s Republic of China; 2NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases, Shihezi University, Shihezi, 832000, People’s Republic of China; 3The Clinical Research Center for Infectious Diseases of Xinjiang Production and Construction Corps, Shihezi University, Shihezi, 832000, People’s Republic of China; 4Department of Hepatobiliary Surgery, The First Affiliated Hospital of Shihezi University, Shihezi, 832000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Xiangwei Wu, School of Medicine, Shihezi University, North Fourth Road, Shihezi City, Xinjiang, 832000, People’s Republic of China, Email Wu_xiangweii@outlook.com Xueling Chen, School of Medicine, Shihezi University, North Fourth Road, Shihezi City, Xinjiang, 832000, People’s Republic of China, Email XXuelingchen@outlook.com
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.
Keywords: ARHGAP33 gene, hepatocellular carcinoma, multi-algorithm, prognostic model, bioinformatics
1School of Medicine, Shihezi University, Shihezi, 832000, People’s Republic of China; 2NHC Key Laboratory of Prevention and Treatment of Central Asia High Incidence Diseases, Shihezi University, Shihezi, 832000, People’s Republic of China; 3The Clinical Research Center for Infectious Diseases of Xinjiang Production and Construction Corps, Shihezi University, Shihezi, 832000, People’s Republic of China; 4Department of Hepatobiliary Surgery, The First Affiliated Hospital of Shihezi University, Shihezi, 832000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Xiangwei Wu, School of Medicine, Shihezi University, North Fourth Road, Shihezi City, Xinjiang, 832000, People’s Republic of China, Email Wu_xiangweii@outlook.com Xueling Chen, School of Medicine, Shihezi University, North Fourth Road, Shihezi City, Xinjiang, 832000, People’s Republic of China, Email XXuelingchen@outlook.com
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.
Keywords: ARHGAP33 gene, hepatocellular carcinoma, multi-algorithm, prognostic model, bioinformatics