尽管基于焦亡相关基因（PRG）的预后模型已在膀胱癌（BLCA）中构建，但这些基因对肿瘤微环境（TME）和免疫治疗反应的综合影响仍有待研究。基于52个PRG的表达谱，我们利用无监督聚类算法来识别 PRG 亚型，并利用 ssGSEA 来量化免疫细胞和标志通路。此外，我们筛选了不同 PRG 亚型的特征基因，并使用多重免疫荧光验证了其与组织中免疫浸润的关联。采用单变量、LASSO 和多变量 Cox 回归分析来构建评分方案。确定了四个 PRG 簇，簇 C1 中的样本比其他簇中浸润有更多的免疫细胞，这意味着对免疫治疗的良好反应。而 C2 簇显示大多数免疫细胞水平极低，对免疫治疗没有反应。 CXCL9/CXCL10和SPINK1/DHSR2被鉴定为C1和C2簇的特征基因，CXCL9/CXCL10高的标本特征为CD8 T细胞、巨噬细胞较多，Treg细胞较少。基于PRGs亚型之间的差异表达基因（DEG），建立了包括5个基因（CACNA1D、PTK2B、APOL6、CDK6、ANXA2）的预测模型（称为PRGs评分）。 PRGs评分低的患者的生存概率显着高于PRGs评分高的患者。此外，PRGs评分低的患者更有可能从抗PD1/PD-L1治疗方案中受益。PRGs与TME和致癌途径密切相关。 PRGs 评分是预测临床结果和免疫治疗反应的一个有前景的指标。版权所有 © 2024 Xu、Zhao、Zhang、Liu、Song、Chen、Xiao、Ma 和 Shi。

Although prognostic models based on pyroptosis-related genes (PRGs) have been constructed in bladder cancer (BLCA), the comprehensive impact of these genes on tumor microenvironment (TME) and immunotherapeutic response has yet to be investigated.Based on expression profiles of 52 PRGs, we utilized the unsupervised clustering algorithm to identify PRGs subtypes and ssGSEA to quantify immune cells and hallmark pathways. Moreover, we screened feature genes of distinct PRGs subtypes and validated the associations with immune infiltrations in tissue using the multiplex immunofluorescence. Univariate, LASSO, and multivariate Cox regression analyses were employed to construct the scoring scheme.Four PRGs clusters were identified, samples in cluster C1 were infiltrated with more immune cells than those in others, implying a favorable response to immunotherapy. While the cluster C2, which shows an extremely low level of most immune cells, do not respond to immunotherapy. CXCL9/CXCL10 and SPINK1/DHSR2 were identified as feature genes of cluster C1 and C2, and the specimen with high CXCL9/CXCL10 was characterized by more CD8 + T cells, macrophages and less Tregs. Based on differentially expressed genes (DEGs) among PRGs subtypes, a predictive model (termed as PRGs score) including five genes (CACNA1D, PTK2B, APOL6, CDK6, ANXA2) was built. Survival probability of patients with low-PRGs score was significantly higher than those with high-PRGs score. Moreover, patients with low-PRGs score were more likely to benefit from anti-PD1/PD-L1 regimens.PRGs are closely associated with TME and oncogenic pathways. PRGs score is a promising indicator for predicting clinical outcome and immunotherapy response.Copyright © 2024 Xu, Zhao, Zhang, Liu, Song, Chen, Xiao, Ma and Shi.