Workflow of this study. (IMAGE)
Caption
(A) Cryosectioned prostate cancer (PCa) tissue samples were mounted on Superfrost slides (VWR) containing a spatial microarray of 4992 barcoded spots (55 μm in diameter, 100 μm center-to-center spacing) to enable spatially resolved gene expression profiling. (B) Transcriptomic read count matrices were generated following the CytAssist ST platform. (C) Dimensionality reduction and clustering of the spatial spots were performed through PCA, UMAP and Louvain clustering analyses. (D) The clusters were annotated as distinct histological structures based on pathological evaluation. (E) Malignancy-associated features of the classified clusters were assessed through inferCNV analysis. (F) Developmental trajectories and progression stages were further characterized using DPT and PAGA analyses. (G) To identify genes associated with PCa progression, DEG analysis was conducted by comparing GE clusters aligned with GS progression patterns that met all predefined criteria. (H) Commonly dysregulated DEGs across 12 PCa samples were identified and summarized. (I) The protein expression of candidate DEGs (H2AFJ, SLC4A4, TFF3) was validated in PCa tissues spanning a spectrum of GSs and PIN using IHC staining.
Credit
Yongjun Quan, Mingdong Wang, Fan Zou, Hong Zhang, Yishan Zhang, Yongchen Jin, Hao Ping
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CC BY-NC-ND