Siyuan Cheng, Lin Li, Yunshin Yeh, Yingli Shi, Omar Franco, Eva Corey, Xiuping Yu
{"title":"通过单细胞 RNA 测序分析揭示新型双阴性前列腺癌亚型","authors":"Siyuan Cheng, Lin Li, Yunshin Yeh, Yingli Shi, Omar Franco, Eva Corey, Xiuping Yu","doi":"10.1038/s41698-024-00667-x","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":19433,"journal":{"name":"NPJ Precision Oncology","volume":null,"pages":null},"PeriodicalIF":6.8000,"publicationDate":"2024-08-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11297170/pdf/","citationCount":"0","resultStr":"{\"title\":\"Unveiling novel double-negative prostate cancer subtypes through single-cell RNA sequencing analysis\",\"authors\":\"Siyuan Cheng, Lin Li, Yunshin Yeh, Yingli Shi, Omar Franco, Eva Corey, Xiuping Yu\",\"doi\":\"10.1038/s41698-024-00667-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":19433,\"journal\":{\"name\":\"NPJ Precision Oncology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":6.8000,\"publicationDate\":\"2024-08-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11297170/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"NPJ Precision Oncology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://www.nature.com/articles/s41698-024-00667-x\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ONCOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"NPJ Precision Oncology","FirstCategoryId":"3","ListUrlMain":"https://www.nature.com/articles/s41698-024-00667-x","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
Unveiling novel double-negative prostate cancer subtypes through single-cell RNA sequencing analysis
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.
期刊介绍:
Online-only and open access, npj Precision Oncology is an international, peer-reviewed journal dedicated to showcasing cutting-edge scientific research in all facets of precision oncology, spanning from fundamental science to translational applications and clinical medicine.