RHOGTPase-Related Gene Signature Predicts Prognosis, Immunotherapy Response, and Chemotherapy Sensitivity in Colon Cancer.
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2025
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Abstract
Rho GTPases are known to promote colon cancer cell invasion and metastasis by modulating cell motility and adhesion. However, the clinical implications of Rho GTPase-related genes in prognosis and treatment response for colon cancer remain underexplored. We identified Rho GTPase-related prognostic genes using univariate Cox regression and applied Least Absolute Shrinkage and Selection Operator (LASSO) regression to refine these genes and develop a prognostic model. The Rho GTPase-related gene signature was analyzed for associations with clinical outcomes, immune status, immunotherapy, and chemotherapy response in colon cancer patients. A Rho GTPase-related 12-gene signature was established to predict prognosis across training and validation cohorts. Both univariate and multivariate analyses confirmed the Rho GTPase risk score as an independent prognostic factor. The model's area under the curve (AUC) and decision curve analysis (DCA) outperformed traditional TNM staging and several existing models. Immune cell analysis showed high Rho GTPase risk scores correlated with increased macrophage/monocyte and cancer-associated fibroblast infiltration. Tumor Immune Dysfunction and Exclusion (TIDE) analysis revealed an association between high Rho GTPase risk scores and immune dysfunction, suggesting potential resistance to immune checkpoint inhibitors in high-risk patients. Additionally, differential sensitivity to 59 chemotherapeutics was observed: high-risk patients showed greater sensitivity to CCT007093, CGP.082996, and AS601245, while low-risk patients were more sensitive to BMS.708163, NSC.87877, and Cisplatin, informing potential treatment choices. The Rho GTPase-related 12-gene signature offers a valuable tool for predicting prognosis and therapeutic response in colon cancer, supporting personalized treatment strategies and improved patient outcomes.
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zhang2025rhogtpaserelated
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| Authors | Zhang, Bixiong; Xu, Lingli; Ji, Yuran; Li, Jiezhuang; Liu, Liehui; Li, Liangfang; Zhuo, Zewei; Zheng, Zhongwen |
| Journal | Applied biochemistry and biotechnology |
| Year | 2025 |
| DOI |
10.1007/s12010-025-05262-9
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