HuPSA and MoPSA Atlases Reveal Novel Cell Populations and Lineage Plasticity in Prostate Cancer at Single-Cell Level

Through unsupervised clustering and manual annotation, we found that both atlases consisted of previously known cell clusters including prostate adenocarcinoma (AdPCa), neuroendocrine prostate cancer (NEPCa), stromal, and immune cell populations. Our analysis also unearthed the less described populations including MMP7+ prostate club cells and two novel lineage plastic cancerous populations, namely Progenitor-like and KRT7. Immunohistochemical staining analysis confirmed the presence of these populations in both human and mouse PCa tissues, reinforcing their significance in PCa pathobiology. Furthermore, employing HuPSA based deconvolution, we scrutinized 877 high-quality human PCa bulk RNAseq samples and reclassified them into different molecular subtypes, including the newly discovered KRT7 and Progenitor-like categories. Moreover, employing supervised dimensional reduction and label transferring techniques, we projected the scRNAseq data derived from C4-2B xenograft tumors onto HuPSA. Our analysis effectively identified the diverse subpopulations within the tumor, including C4-2B derived AdPCa and NEPCa cells as well as the murine cells in the tumor microenvironment. We launched the “PCaAtlas” app (https://pcatools.shinyapps.io/ProAtlas_dev/) for users to visualize genes expression in re-classified human prostatic tissue samples. In conclusion, our study has successfully integrated multiple scRNAseq datasets and made these data easily accessible to researchers. Our results elucidate a roadmap of PCa progression, showcasing the development of heterogeneous populations and the involvement of lineage plasticity. This understanding holds promise for guiding the development of precision medicine in PCa field. Additionally, the HuPSA and MoPSA provide invaluable blueprints for analyzing and interpreting user-generated PCa single-cell RNAseq data.