{"title":"Activation of RHO-GTPase gene pattern correlates with adverse clinical outcome and immune microenvironment in clear cell renal cell carcinoma.","authors":"Kehang Guo, Pengyue Ma, Qi Yang, Lingli Xu, Biixiong Zhang, Hong Zhang, Zhongwen Zheng, Zewei Zhuo","doi":"10.1007/s10238-025-01593-3","DOIUrl":null,"url":null,"abstract":"<p><p>Clear cell renal cell carcinoma (ccRCC), the most prevalent renal cancer subtype, is frequently associated with poor prognosis. RHO-GTPase signaling genes have been implicated in tumor aggressiveness and unfavorable survival, but their potential in risk stratification and therapeutic guidance for ccRCC patients remains unexplored. Univariate regression identified prognostically relevant RHO-GTPase signaling genes, followed by consensus clustering for ccRCC subtype classification. LASSO regression selected key genes to construct a six-gene risk model. The model was evaluated for prognostic stratification, immune status, immunotherapy response, and chemotherapy sensitivity. Key genes were analyzed at the genomic, single-cell, and protein levels to explore underlying mechanisms. Among 62 prognostically relevant RHO-GTPase signaling genes, six (ARHGAP11B, NUF2, PLK1, CYFIP2, IQGAP2, and VAV3) were identified to form a robust prognostic signature. This model stratified patients into high- and low-risk groups, with high-risk patients demonstrating significantly worse outcomes. The model exhibited excellent predictive accuracy (AUC > 0.7 in training and validation cohorts). High-risk patients were characterized by an immunosuppressive microenvironment and reduced sensitivity to immunotherapy. Drug sensitivity analysis revealed 107 agents correlated with the risk score, underscoring therapeutic relevance. Mechanistically, the six key genes showed distinct expression patterns, cellular distribution, and positive correlation with VHL mutations, highlighting their potential as actionable drug targets. This study established a novel six-gene RHO-GTPase signaling model for predicting prognosis, immune status, and therapeutic responses in ccRCC, which offers potential for improving patient stratification and guiding personalized treatment strategies.</p>","PeriodicalId":10337,"journal":{"name":"Clinical and Experimental Medicine","volume":"25 1","pages":"67"},"PeriodicalIF":3.2000,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11861022/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical and Experimental Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s10238-025-01593-3","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MEDICINE, RESEARCH & EXPERIMENTAL","Score":null,"Total":0}
引用次数: 0
Abstract
Clear cell renal cell carcinoma (ccRCC), the most prevalent renal cancer subtype, is frequently associated with poor prognosis. RHO-GTPase signaling genes have been implicated in tumor aggressiveness and unfavorable survival, but their potential in risk stratification and therapeutic guidance for ccRCC patients remains unexplored. Univariate regression identified prognostically relevant RHO-GTPase signaling genes, followed by consensus clustering for ccRCC subtype classification. LASSO regression selected key genes to construct a six-gene risk model. The model was evaluated for prognostic stratification, immune status, immunotherapy response, and chemotherapy sensitivity. Key genes were analyzed at the genomic, single-cell, and protein levels to explore underlying mechanisms. Among 62 prognostically relevant RHO-GTPase signaling genes, six (ARHGAP11B, NUF2, PLK1, CYFIP2, IQGAP2, and VAV3) were identified to form a robust prognostic signature. This model stratified patients into high- and low-risk groups, with high-risk patients demonstrating significantly worse outcomes. The model exhibited excellent predictive accuracy (AUC > 0.7 in training and validation cohorts). High-risk patients were characterized by an immunosuppressive microenvironment and reduced sensitivity to immunotherapy. Drug sensitivity analysis revealed 107 agents correlated with the risk score, underscoring therapeutic relevance. Mechanistically, the six key genes showed distinct expression patterns, cellular distribution, and positive correlation with VHL mutations, highlighting their potential as actionable drug targets. This study established a novel six-gene RHO-GTPase signaling model for predicting prognosis, immune status, and therapeutic responses in ccRCC, which offers potential for improving patient stratification and guiding personalized treatment strategies.
期刊介绍:
Clinical and Experimental Medicine (CEM) is a multidisciplinary journal that aims to be a forum of scientific excellence and information exchange in relation to the basic and clinical features of the following fields: hematology, onco-hematology, oncology, virology, immunology, and rheumatology. The journal publishes reviews and editorials, experimental and preclinical studies, translational research, prospectively designed clinical trials, and epidemiological studies. Papers containing new clinical or experimental data that are likely to contribute to changes in clinical practice or the way in which a disease is thought about will be given priority due to their immediate importance. Case reports will be accepted on an exceptional basis only, and their submission is discouraged. The major criteria for publication are clarity, scientific soundness, and advances in knowledge. In compliance with the overwhelmingly prevailing request by the international scientific community, and with respect for eco-compatibility issues, CEM is now published exclusively online.