Unveiling novel double-negative prostate cancer subtypes through single-cell RNA sequencing analysis

Area of Science:

• Oncology
• Genomics
• Bioinformatics

Background:

• Single-cell RNA sequencing (scRNAseq) has revolutionized the identification of cellular heterogeneity in complex diseases like prostate cancer (PCa).
• Understanding PCa heterogeneity is crucial for improving diagnosis and treatment strategies.

Purpose of the Study:

• To integrate multiple scRNAseq datasets to create comprehensive atlases of human and mouse prostate cells (HuPSA and MoPSA).
• To identify novel prostate cancer subtypes and characterize their molecular features.
• To develop accessible tools for visualizing and analyzing prostate cancer single-cell data.

Main Methods:

• Integration of publicly available and newly generated scRNAseq data.
• Bioinformatic analysis to identify distinct cell populations and gene expression patterns.
• Development of a web application (HuPSA-MoPSA) for data visualization and exploration.

Main Results:

• Establishment of the Human Prostate Single cell Atlas (HuPSA) and Mouse Prostate Single cell Atlas (MoPSA).
• Discovery of two novel double-negative PCa populations: KRT7+ cells and SOX2/FOXA2+ progenitor-like cells.
• Validation of novel subtypes through HuPSA-based deconvolution of human PCa specimens.
• Launch of the HuPSA-MoPSA web application for interactive gene expression analysis.

Conclusions:

• The study successfully created comprehensive prostate single-cell atlases and identified novel PCa subtypes.
• These newly identified subtypes exhibit distinct molecular characteristics and potential stem/progenitor features.
• The HuPSA-MoPSA tool provides valuable resources for the research community, aiding in PCa research and potentially informing clinical applications.