Unveiling novel double-negative prostate cancer subtypes through single-cell RNA sequencing analysis.
Siyuan ChengLin LiYunshin YehYingli ShiOmar FrancoEva CoreyXiuping YuPublished in: NPJ precision oncology (2024)
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.
Keyphrases
- single cell
- rna seq
- prostate cancer
- high throughput
- gene expression
- radical prostatectomy
- endothelial cells
- poor prognosis
- papillary thyroid
- electronic health record
- palliative care
- stem cells
- big data
- dna methylation
- induced apoptosis
- small molecule
- squamous cell
- squamous cell carcinoma
- binding protein
- induced pluripotent stem cells
- long non coding rna
- oxidative stress
- data analysis
- signaling pathway
- benign prostatic hyperplasia
- deep learning
- young adults
- single molecule