High-Resolution Spatial Transcriptomics Reveals Pathological Microregion-Specific Luminal Subset Plasticity and Core Signaling Networks Underlying Prostate Cancer Malignancy

Background: Prostate cancer (PCa) exhibits strong multidimensional heterogeneity. The dynamic evolution of Luminal subsets and their crosstalk with the tumor microenvironment (TME) during malignant progression remain poorly understood. Conventional single-cell transcriptomics lacks spatial context, while low-resolution spatial technologies cannot resolve single-cell and subcellular interactions. This study aimed to map a high-resolution spatial transcriptomic atlas to characterize Luminal subset heterogeneity and stromal crosstalk across progressive PCa lesions. Methods: We used high-resolution CosMx spatial molecular imaging (SMI) to profile 6 treatment-naive PCa patients and constructed a single-cell spatial transcriptomic atlas covering 385 fields of view and 154,168 high-quality cells. Unsupervised clustering, functional enrichment, cell–cell communication analysis, and flow cytometry were performed. Results: We identified 28 cell clusters, including 8 Luminal subsets (0–7) and 9 Fibroblast subsets (0–8). Pathological microregion-specific spatial distribution was observed: Luminal 0–2 dominated in BPH/PIN, while Luminal 3–7 were enriched in poorly differentiated PCa and vacuolated adenocarcinoma. These subsets were functionally linked to androgen resistance, EMT, and immune regulation. COLLAGEN, FN1, and LAMININ were identified as key pathways mediating pathological-specific tumor–stromal crosstalk. Flow cytometry verified T-cell exhaustion and immunosuppression in the TME. Conclusions: This study delineated pathological microregion-specific Luminal subset plasticity and dynamic epithelial–stromal communication across the full spectrum of PCa lesions. The uncovered molecular signatures offered mechanistic clues linking EMT, hormone resistance, and local immune status during lesion evolution. Our spatial atlas provided preliminary molecular evidence to support pathological stratification and targeted precision therapeutic strategies for PCa.