{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,29]],"date-time":"2026-08-29T06:07:38Z","timestamp":1787983658184,"version":"build-2784847793"},"reference-count":107,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T00:00:00Z","timestamp":1785974400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Immunol."],"abstract":"<jats:p>Prostate cancer is a hormone-driven malignancy, but its clinical behavior cannot be explained by androgen receptor (AR) signaling alone. Single-cell and spatial omics are redefining prostate cancer as an evolving metabolic-immune ecosystem in which malignant epithelial states, stromal niches, myeloid programs, T-cell exclusion, vascular remodeling, and treatment-imposed selection pressures jointly shape progression and resistance. These technologies have resolved the normal prostate epithelial hierarchy, pre-existing castration-resistant-like cells, basal-like, club-like, and hillock-like programs, neuroendocrine transformation states, immunosuppressive macrophage populations, fibroblast states, and spatial neighborhoods that are difficult to detect by bulk sequencing. Treatment-associated changes have been characterized most directly in androgen-axis and immune contexts, whereas evidence related to taxanes, DNA damage response (DDR)-targeted therapy, and radioligand therapy remains emerging or hypothesis-generating. This review synthesizes single-cell and spatial omics evidence for metabolic-immune ecosystems in prostate cancer, emphasizing the transition from androgen dependence to castration resistance, lineage plasticity, metastatic niche adaptation, and therapy resistance. We argue that the next translational step is not simply to catalog additional cell types, but to connect longitudinal cell-state maps, spatially resolved metabolic dependencies, immune-neighborhood biomarkers, and mechanism-matched combination therapies.<\/jats:p>","DOI":"10.3389\/fimmu.2026.1899588","type":"journal-article","created":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T11:31:57Z","timestamp":1786015917000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Single-cell and spatial omics of metabolic-immune ecosystems in prostate cancer: from androgen signaling to therapy resistance"],"prefix":"10.3389","volume":"17","author":[{"given":"Ruiang","family":"Wang","sequence":"first","affiliation":[{"name":"The First Clinical Medical College, Faculty of Medicine, Yangzhou University","place":["Yangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yifan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Urology, The Affiliated Hospital of Yangzhou University, Yangzhou University","place":["Yangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoxiang","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Urology, The Affiliated Hospital of Yangzhou University, Yangzhou University","place":["Yangzhou, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,8,6]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trecan.2020.04.010","article-title":"Advanced prostate cancer: Treatment advances and future directions","volume":"6","author":"Swami","year":"2020","journal-title":"Trends 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