Patient-Derived Organoids in Functional Precision Oncology: Tumor Modeling, Drug-Response Prediction, and Clinical Translation.
5 affiliations
- 1College of Medicine, Alfaisal University, Riyadh, Saudi Arabia.
- 2Department of Internal Medicine, Acıbadem MAA University, Istanbul, Turkey.
- 3College of Medicine, AlMaarefa University, Riyadh, Saudi Arabia.
- 4King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.
- 5King Faisal Specialist Hospital and Research Center, Jeddah, Saudi Arabia.
Abstract
Patient-derived organoids (PDOs) have emerged as an effective experimental platform for bridging the long-standing gap between traditional in vitro cancer models and the biological complexity of actual tumors. These three-dimensional 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-specific 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.
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BibTeX
@article{jabri2026patientderived,
title = {{Patient-Derived Organoids in Functional Precision Oncology: Tumor Modeling, Drug-Response Prediction, and Clinical Translation.}},
author = {Abdullah Jabri and Mohamed Alsharif and Abdulaziz Mhannayeh and Bader Taftafa and Dania Sibai and Abdulrahman Elsalti and Raghad Alsharif and Tanveer Ahmad Mir and Mohammed Imran Khan and Jahan Salma and Ahmed Yaqinuddin},
journal = {Cell biochemistry and function},
year = {2026},
month = oct,
doi = {10.1002/cbf.70321},
url = {https://europepmc.org/article/MED/42895119},
note = {CC BY},
}
RIS
TY - JOUR
TI - Patient-Derived Organoids in Functional Precision Oncology: Tumor Modeling, Drug-Response Prediction, and Clinical Translation.
AU - Abdullah Jabri
AU - Mohamed Alsharif
AU - Abdulaziz Mhannayeh
AU - Bader Taftafa
AU - Dania Sibai
AU - Abdulrahman Elsalti
AU - Raghad Alsharif
AU - Tanveer Ahmad Mir
AU - Mohammed Imran Khan
AU - Jahan Salma
AU - Ahmed Yaqinuddin
PY - 2026
DA - 2026/10/01
JO - Cell biochemistry and function
DO - 10.1002/cbf.70321
UR - https://europepmc.org/article/MED/42895119
AB - Patient-derived organoids (PDOs) have emerged as an effective experimental platform for bridging the long-standing gap between traditional in vitro cancer models and the biological complexity of actual tumors. These three-dimensional 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-specific 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.
SN - 0263-6484
SN - 1099-0844
ER -