Lin Wenfeng, Xue Ruizhi, Ueki Hideo, Huang Peng
Department of Urology, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama, Japan.
Department of Urology, Affiliated Qingyuan Hospital, Guangzhou Medical University, Qingyuan People's Hospital, Qingyuan, China.
Curr Cancer Drug Targets. 2025;25(3):244-256. doi: 10.2174/0115680096286503240321040556.
It remains controversial whether the current subtypes of kidney renal papillary cell carcinoma (KIRP) can be used to predict the prognosis independently.
This observational study aimed to identify a risk signature based on necroptotic process- related genes (NPRGs) in KIRP.
In the training cohort, LASSO regression was applied to construct the risk signature from 158 NPRGs, followed by the analysis of Overall Survival (OS) using the Kaplan-Meier method. The signature accuracy was evaluated by the Receiver Operating Characteristic (ROC) curve, which was further validated by the test cohort. Wilcoxon test was used to compare the expressions of immune-related genes, neoantigen genes, and immune infiltration between different risk groups, while the correlation test was performed between NPRGs expressions and drug sensitivity. Gene set enrichment analysis was used to investigate the NPRGs' signature's biological functions.
We finally screened out 4-NPRGs (BIRC3, CAMK2B, PYGM, and TRADD) for constructing the risk signature with the area under the ROC curve (AUC) reaching about 0.8. The risk score could be used as an independent OS predictor. Consistent with the enriched signaling, the NPRGs signature was found to be closely associated with neoantigen, immune cell infiltration, and immune-related functions. Based on NPRGs expressions, we also predicted multiple drugs potentially sensitive or resistant to treatment.
The novel 4-NPRGs risk signature can predict the prognosis, immune infiltration, and therapeutic sensitivity of KIRP.
肾肾乳头细胞癌（KIRP）目前的亚型是否可独立用于预测预后仍存在争议。
本观察性研究旨在基于KIRP中坏死性凋亡相关基因（NPRGs）确定一种风险特征。
在训练队列中，采用LASSO回归从158个NPRGs构建风险特征，随后使用Kaplan-Meier方法分析总生存期（OS）。通过受试者工作特征（ROC）曲线评估特征准确性，并在测试队列中进一步验证。采用Wilcoxon检验比较不同风险组之间免疫相关基因、新抗原基因的表达及免疫浸润情况，同时对NPRGs表达与药物敏感性进行相关性检验。利用基因集富集分析研究NPRGs特征的生物学功能。
我们最终筛选出4个NPRGs（BIRC3、CAMK2B、PYGM和TRADD）用于构建风险特征，ROC曲线下面积（AUC）约为0.8。风险评分可作为独立的OS预测指标。与富集的信号一致，发现NPRGs特征与新抗原、免疫细胞浸润及免疫相关功能密切相关。基于NPRGs表达，我们还预测了多种可能对治疗敏感或耐药的药物。
新的4-NPRGs风险特征可预测KIRP的预后、免疫浸润及治疗敏感性。
