ArticleTranslational andrology and urology2026
Construction and verification of a prognostic model of neutrophil-related genes in clear cell renal cell carcinoma.
Article in Translational andrology and urology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: The tumor microenvironment of clear cell renal cell carcinoma (ccRCC) is heterogeneous, leading to diverse prognoses among patients. Neutrophils, as a key component of the tumor microenvironment, have predictive value for the prognosis of ccRCC. However, there are currently no predictive models based on neutrophil-related genes. This study aimed to construct and validate a prognostic model for ccRCC based on neutrophil-related genes to facilitate risk stratification and treatment guidance. This study aimed to construct and validate a prognostic model for ccRCC based on neutrophil-related genes to facilitate risk stratification and treatment guidance. Methods: We analyzed the RNA sequencing (RNA-seq) data and clinical information of ccRCC, screened out 10 neutrophil-related prognostic genes using R software, and constructed a risk prediction model. Single/multivariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used for gene screening. Results: Model validation showed that the area under the curve (AUC) values of the model for predicting 1-, 2-, and 3-year overall survival (OS) were 0.704, 0.674, and 0.656 in the test set. Its performance in the training set was better, with AUC values of 0.796, 0.784, and 0.793, respectively. The calibration curve confirmed that the model had good consistency. Kaplan-Meier (KM) survival analysis showed that the survival rate of patients in the high-risk group was significantly lower than that in the low-risk group (P<0.05), and the risk score prediction efficiency was better than clinical indicators such as age. In summary, this model demonstrated strong predictive performance on both the training and multiple validation sets, effectively identifying high-risk patients with poor prognosis who required intensive treatment and close follow-up. Further analysis showed that four drugs, such as axitinib_1021, may have anti-tumor potential, and the immune infiltration characteristics showed that the infiltration levels of B cells (naive) and CD4 memory activated T cells in the high-risk group were significantly increased. Conclusions: The proposed 10 neutrophil-related genes are promising biomarkers to predict survival and therapeutic responses in ccRCC patients.
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