Uncovering genes driving developmental stage progression in prostate cancer through spatial transcriptomics - PubMed
4 hours ago
- #prostate cancer progression
- #gene identification
- #spatial transcriptomics
- The study employed spatial transcriptomics to analyze 12 prostate cancer (PCa) tissue samples, aiming to identify genes associated with progression by examining expression patterns across different histological regions.
- Transcriptomic classification using methods like PCA, UMAP, and Louvain clustering revealed spatially resolved structures, and analyses such as inferCNV, DPT, and PAGA assessed malignancy status, progression stages, and developmental trajectories of glandular epithelial (GE) cells.
- Key oncogenes positively associated with PCa progression, including TFF3, OR51E2, FOLH1, AMACR, FOS, SLC4A4, EGR1, NDUFB9, and H2AFJ, were identified through pairwise comparisons of GE clusters, with IHC validation confirming elevated expression of SLC4A4 and H2AFJ in advanced-stage PCa.
- The study establishes a spatial transcriptomics-based framework for predicting PCa progression and provides insights for identifying progression-associated genes as potential clinical biomarkers.