新辅助化疗（NAC）和免疫检查点治疗（ICT）在膀胱癌（BCa）治疗方面产生了革命性的影响。然而，如何准确判断患者是否适合接受这些治疗仍然是一个主要的临床挑战。本研究使用单细胞RNA测序技术评估高表达角蛋白13（KRT13）上皮细胞群体的预测能力，以评估BCa的治疗反应。KRT13富集肿瘤的存在表明，在NAC后有良好的临床预后，并且在接受ICT治疗的BCa患者中具有更强的治疗反应。此外，KRT13细胞群体的特征似乎与其周围的免疫微环境变化密切相关。我们采用基于KRT13群体中的基因签名构建的人工神经网络 prognostic model；该模型表现出较强的稳健性和优越性。此外，我们开发了一个用户友好的、开放获取的网络应用程序，命名为BCa数据库，供研究人员使用，以通过挖掘关联映射数据库研究BCa。Copyright © 2023. Elsevier Ltd. 发布。

Neoadjuvant chemotherapy (NAC) prior to surgery and immune checkpoint therapy (ICT) has revolutionized bladder cancer (BCa) treatment. Patients likely to benefit from these therapies need to be accurately stratified; however, this remains a major clinical challenge. In the present study, single-cell RNA sequencing was used to evaluate the predictive ability of an epithelial cell population highly expressing keratin 13 (KRT13) to assess therapeutic response in BCa. The presence of KRT13-enriched tumors indicated favorable outcomes after NAC and superior response to ICT in patients with BCa. Furthermore, KRT13 population characteristics appeared to be closely related to changes in the immune microenvironment in the vicinity of this cell population. We constructed a prognostic model using an artificial neural network based on the gene signatures in the KRT13 population; the model demonstrated strong robustness and superiority. Additionally, a user-friendly and open-access web application named BCa database was developed for researchers to study BCa by mining the connective map database.Copyright © 2023. Published by Elsevier Ltd.