{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,27]],"date-time":"2026-10-27T11:37:02Z","timestamp":1793101022766,"version":"4.5.0"},"reference-count":75,"publisher":"Wiley","issue":"10","license":[{"start":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T00:00:00Z","timestamp":1792368000000},"content-version":"vor","delay-in-days":18,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,10,1]],"date-time":"2026-10-01T00:00:00Z","timestamp":1790812800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["analyticalsciencejournals.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cell Biochemistry &amp;amp; Function"],"published-print":{"date-parts":[[2026,10]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Patient\u2010derived organoids (PDOs) have emerged as an effective experimental platform for bridging the long\u2010standing gap between traditional in vitro cancer models and the biological complexity of actual tumors. These three\u2010dimensional cultures (3D), derived directly from patient tissues, preserve essential architectural, genomic, and phenotypic characteristics of their tumors of origin, enabling more accurate modeling of tumor heterogeneity and disease evolution. Over the last decade, rapid methodological advances in organoid culture systems, extracellular matrices (ECMs), and growth factor optimization have facilitated the establishment of organoid models for a wide range of malignancies and the development of large living biobanks representing diverse patient populations. These models are increasingly being utilized to study cancer biology, elucidate mechanisms of treatment resistance, and evaluate patient\u2010specific therapeutic responses, highlighting their potential as tools for precision oncology. However, important challenges remain, including incomplete representation of the tumor microenvironment (TME), variability in culture conditions, and limited scalability, and the need for greater standardization and validation. Consequently, although PDOs show considerable promise for translational research and personalized medicine, their routine clinical implementation remains largely investigational, and their clinical utility has not yet been fully established. This review examines the technological foundations of PDO generation, assesses their role as experimental models of tumor biology, and discusses their expanding applications in translational cancer research and precision oncology while highlighting key challenges that must be addressed before their widespread clinical adoption.<\/jats:p>","DOI":"10.1002\/cbf.70321","type":"journal-article","created":{"date-parts":[[2026,10,19]],"date-time":"2026-10-19T10:16:18Z","timestamp":1792404978000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Patient\u2010Derived Organoids in Functional Precision Oncology: Tumor Modeling, Drug\u2010Response Prediction, and Clinical Translation"],"prefix":"10.1002","volume":"44","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-8048-9528","authenticated-orcid":false,"given":"Abdullah","family":"Jabri","sequence":"first","affiliation":[{"name":"College of Medicine, Alfaisal University 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