{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T12:02:04Z","timestamp":1789732924099,"version":"4.0.1"},"reference-count":159,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T00:00:00Z","timestamp":1789689600000},"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>Crohn\u2019s disease and ulcerative colitis are now treated with an expanding set of biologics and small molecules, yet treatment selection remains largely empirical. Primary non-response, secondary loss of response, incomplete mucosal healing, fibrostenosis, and fistulizing disease show that conventional clinical, endoscopic, and bulk molecular markers do not capture how disease is organized within tissue. This review argues that the inflamed intestine is better viewed as a set of spatially structured mucosal immune niches rather than as uniform inflammation, with epithelial, myeloid, lymphoid, stromal, vascular, neural, and microbiome-associated cells communicating through defined cytokine and ligand\u2013receptor circuits. In this framework, mucosal immune niches can be considered functional tissue units that link tissue-resolved mechanisms to therapeutic target discovery, pharmacodynamic assessment, biomarker qualification, and biomarker-enriched trial design. Single-cell atlases and spatial multi-omics, interpreted through computational modeling, can identify disease-driving cellular neighborhoods, ligand\u2013receptor circuits, and compartment-specific vulnerabilities in both diseases. We discuss how these spatial features may inform target discovery, mechanism-of-action validation, patient stratification, response prediction, and trial design, using pathways such as TNF, IL-23, OSM, TL1A, integrins, JAK\u2013STAT, and S1P as examples. At present, the realistic value of spatial data lies in generating mechanistic hypotheses, defining pharmacodynamic endpoints, and enriching trials, not in guiding routine treatment selection. Most candidate spatial biomarkers remain at the discovery or early translational stage and require standardized sampling, harmonized computation, longitudinal assessment, and multicenter validation. A staged translational path is proposed, moving from disease-specific atlases to spatial pharmacodynamic endpoints and adaptive precision trials, while also offering a comparative framework for studying chronic inflammation across mucosal organs.<\/jats:p>","DOI":"10.3389\/fimmu.2026.1951659","type":"journal-article","created":{"date-parts":[[2026,9,18]],"date-time":"2026-09-18T11:07:05Z","timestamp":1789729625000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Spatial multi-omics-guided drug development in inflammatory bowel disease: from mucosal immune niches to precision therapy"],"prefix":"10.3389","volume":"17","author":[{"given":"Hai","family":"Wang","sequence":"first","affiliation":[{"name":"Bazhong Central Hospital, Sichuan Academy of Medical Sciences and Sichuan Provincial People\u2019s Hospital","place":["Bazhong, 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