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.