Prostate cancer (PrCa) remains one of the most prevalent malignancies among aging male populations worldwide. Despite favorable primary disease control achieved through radical prostatectomy and/or radiotherapy, a substantial proportion of patients—estimated at approximately 20–40%—experience biochemical recurrence (BCR) within 10 years following initial treatment. Clinically, BCR is a key early indicator of disease relapse and is associated with increased risk of subsequent progression to metastatic disease.
Current recurrence research in PrCa has predominantly relied on bulk-tissue transcriptomic signatures. While informative, bulk-level analyses are intrinsically limited in their ability to resolve cell-type-specific programs and spatially organized interactions within the tumor microenvironment. Increasing evidence across solid tumors indicates that tissue architecture, cellular composition, and intercellular communication patterns provide orthogonal and potentially superior prognostic information compared with genomic features alone.
In this context, the present project is designed to systematically characterize recurrence-associated biological determinants in PrCa through integrated single-cell and spatial omics analyses. Our objectives are to: (i) identify recurrence-related molecular features at cell-type resolution; (ii) define recurrence-associated cell–cell communication networks within the tumor ecosystem; and (iii) develop spatially and cell-type informed models for recurrence prediction and biological interpretation. Collectively, this work aims to advance mechanistic understanding of PrCa recurrence and to support the discovery of clinically actionable vulnerabilities.