单细胞 RNA 测序 (scRNAseq) 的最新进展促进了前列腺癌 (PCa) 中以前未被识别的亚型的发现，为癌症异质性和进展提供了新的见解。在这项研究中，我们整合了多项研究的 scRNAseq 数据，包括公开可用的队列和我们研究团队生成的数据，并建立了人类前列腺单细胞图谱 (HuPSA) 和小鼠前列腺单细胞图谱 (MoPSA) 数据集。通过综合分析，我们鉴定了两个新的双阴性 PCa 群体：以 KRT7 表达升高为特征的 KRT7 细胞和以 SOX2 和 FOXA2 表达为特征的祖样细胞，与 NEPCa 不同，并显示干细胞/祖细胞特征。此外，基于 HuPSA 的反卷积对人类 PCa 样本进行了重新分类，验证了这些新亚型的存在。然后，我们开发了一个用户友好的网络应用程序“HuPSA-MoPSA”（https://pcatools.shinyapps.io/HuPSA-MoPSA/），用于可视化所有新建立的数据集中的基因表达。我们的研究为 PCa 研究提供了全面的工具，并发现了可为临床诊断和治疗策略提供信息的新型癌症亚型。© 2024。作者。

Recent advancements in single-cell RNA sequencing (scRNAseq) have facilitated the discovery of previously unrecognized subtypes within prostate cancer (PCa), offering new insights into cancer heterogeneity and progression. In this study, we integrated scRNAseq data from multiple studies, comprising publicly available cohorts and data generated by our research team, and established the Human Prostate Single cell Atlas (HuPSA) and Mouse Prostate Single cell Atlas (MoPSA) datasets. Through comprehensive analysis, we identified two novel double-negative PCa populations: KRT7 cells characterized by elevated KRT7 expression and progenitor-like cells marked by SOX2 and FOXA2 expression, distinct from NEPCa, and displaying stem/progenitor features. Furthermore, HuPSA-based deconvolution re-classified human PCa specimens, validating the presence of these novel subtypes. We then developed a user-friendly web application, "HuPSA-MoPSA" ( https://pcatools.shinyapps.io/HuPSA-MoPSA/ ), for visualizing gene expression across all newly established datasets. Our study provides comprehensive tools for PCa research and uncovers novel cancer subtypes that can inform clinical diagnosis and treatment strategies.© 2024. The Author(s).