基于癌相关成纤维细胞（CAFs）在肿瘤进展中的关键作用，我们的研究旨在发展一个与膀胱癌（BLCA）患者生存结局和治疗反应相关的CAFs基因特征（CRG）来预测。我们收集了来自公共数据库（包括癌症基因组图谱（TCGA）和基因表达综合库（GEO）数据集）的BLCA转录组数据和相关临床信息。我们采用加权基因共表达网络分析方法来发现与CAFs相关的核心基因，并进而使用LASSO-Cox回归构建了一个生存预后的风险模型。我们使用ESTIMATE、CIBERSORT、TIDE和oncoPredict算法来研究免疫微环境、免疫浸润、免疫治疗反应和药物敏感性。为了验证CRGs的表达情况，我们还使用了在线数据库（HPA、CCLE、TIMER、cBioPortal和TISCH）进行了额外的分析。我们的研究开发了一个CRG特征并构建了一个预后模型。两个风险分层之间的总体生存差异显著。风险评分随着CAFs浸润和肿瘤分期的进展而增加，并且与免疫检查点的表达和CD8 T细胞、滤泡助T细胞、调节性T细胞、活化树突状细胞、M0巨噬细胞、M2巨噬细胞和休眠肥大细胞的浸润密切相关。此外，低风险分层中的患者对免疫治疗的响应性更高，并且两个风险分层之间多种化疗药物的敏感性存在显著差异。基于CRG特征的风险模型的构建为BLCA的预后评估和个体化治疗策略的开发提供了新途径。© 2023. 作者，由意大利肿瘤学会（FESEO）独家授权。

Due to the pivotal role cancer-associated fibroblasts (CAFs) play in tumor progression, our study aimed to develop a signature of CAFs-related gene (CRG) to predict the survival outcomes and treatment response of bladder cancer (BLCA).The transcriptome data and relevant clinical information about BLCA were collected from publicly available databases, including The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets. Weighted gene co-expression network analysis was utilized to uncover CAFs-associated hub genes, and subsequently, a risk model for survival prognosis was constructed using LASSO-Cox regression. The immune microenvironment, immune infiltration, immunotherapy response, and drug sensitivity were explored using ESTIMATE, CIBERSORT, TIDE, and oncoPredict algorithms. To verify the expression of the CRGs, additional analyses were performed using online databases (HPA, CCLE, TIMER, cBioPortal, and TISCH).Our study developed a CRG signature and constructed a prognostic model. Significant differences in overall survival were observed between the two risk stratifications. The risk score increased with the infiltration of CAFs and tumor staging progression, while closely correlating with immune checkpoint expression and infiltration of CD8 T cells, follicular helper T cells, regulatory T cells, activated dendritic cells, M0 macrophages, M2 macrophages, and resting mast cells. Furthermore, a higher proportion of patients in the low-risk stratification exhibited responsiveness to immunotherapy, and significant variances in sensitivity to multiple chemotherapy medications were observed between the two risk stratifications.The construction of the risk model based on the CRG signature offers new avenues for the prognosis evaluation and development of personalized treatment strategies for BLCA.© 2023. The Author(s), under exclusive licence to Federación de Sociedades Españolas de Oncología (FESEO).