免疫原性细胞死亡（ICD）是自适应免疫反应的触发器。然而，在透明细胞肾癌（ccRCC）中，ICD相关基因的作用仍不清楚。我们旨在鉴定与ICD相关的生物标志物，并建立一个预测模型，以预测ccRCC的免疫微环境、预后和免疫治疗反应。我们的研究包括739名患者（603名在训练组和136名在验证组），具有临床病理信息和转录组测序数据。我们使用共识聚类、主成分分析（PCA）、加权基因共表达网络分析（WGCNA）、单变量COX分析、多变量COX分析和Lasso-Cox算法来缩小预测因子并构建总体生存期（OS）的预测签名。我们使用R软件包IOBR中的CIBERSORT、ESTIMATE和TIMER来评估每个样本的肿瘤微环境和免疫浸润模式。最后，我们使用ccRCC中免疫细胞的单细胞测序结果来验证免疫浸润分析的结果，并通过校准曲线和c指数评估预测模型的性能。本研究揭示了初始免疫反应的无效性和原发性免疫缺陷在ICD亚组中显著富集，而这个亚组预后不良。我们发现十个潜在的ICD基因（CALR、ENTPD1、FOXP3、HSP90AA1、IFNB1、IFNG、IL6、LY96、PIK3CA和TLR4）可以影响ccRCC的预后（p＜0.05）。我们构建的预测模型（PRE）不仅可以预测长期生存概率，还可以评估ccRCC的免疫浸润景观。我们的研究证明，ccRCC中树突状细胞的浸润不足意味着预后不良，而CTL浸润的程度则不那么重要。我们创建了一个个体化的预测模型，以预测ccRCC患者在1、2、3和5年内的生存和对免疫治疗的反应性，这可能成为临床医生做出更好的治疗决策的有力工具，从而提高ccRCC患者的总体生存率（OS）。 ©2023作者。

Immunogenic cell death (ICD) is the trigger of adaptive immune responses. However, the role of ICD-related genes in clear cell renal carcinoma (ccRCC) remains unclear. We aimed to identify biomarkers associated with ICD and develop an ICD-related predictive model that predicts the immune microenvironment, prognosis, and response to immunotherapy in ccRCC. Our study included 739 patients (603 in the training set and 136 in the validation set) with clinicopathologic information and transcriptome sequencing data. Consensus clustering, principal component analysis (PCA), weighted gene co-expression network analysis (WGCNA), univariate COX analysis, multivariate COX analysis, and the Lasso-Cox algorithm were applied to shrink predictors and construct a predictive signature of overall survival (OS). We used CIBERSORT, ESTIMATE, and TIMER in the R package IOBR to evaluate the tumor microenvironment and immune infiltration pattern of each sample. Finally, the single cell sequencing results of immune cells in ccRCC were used to verify the results of immune infiltration analysis, and the performance of the prognostic model was evaluated by calibration curves and c-index. This study revealed that inability of the initial immune response and primary immunodeficiency were significantly enriched in the ICD subgroup with poor prognosis. We found that the ten candidate ICD genes (CALR, ENTPD1, FOXP3, HSP90AA1, IFNB1, IFNG, IL6, LY96, PIK3CA, and TLR4) could affect the prognosis of ccRCC (p < 0.05). The prediction model (PRE) we constructed can not only predict the long-term survival probability but also evaluate the landscape of immune infiltration in ccRCC. Our study demonstrated that low infiltration of dendritic cells in ccRCC implies a poor prognosis, whereas the degree of CTL infiltration is less important. An individualized prediction model was created to predict the 1-, 2-, 3-, and 5-year survival and responsiveness of ccRCC patients to immunotherapy, which may serve as a potent tool for clinicians to make better treatment decisions and thus improve the overall survival (OS) of ccRCC patients in the future.© 2023. The Author(s).