Aug 2026· Biopreservation and Biobanking· pp.
19475535261472214
· 0 citations· 25 references
Medicine
TL;DR
This review summarizes representative Chinese resources and enterprise platform types, discusses international benchmark functions for model-biobank maturity, and emphasizes quality transparency for external verification and resource discovery.
Abstract
Tumor-derived model biobanks comprise patient-derived xenografts, organoids, cell models or cultures, and selected paired derivatives linked to clinical, pathological, molecular, and functional data. In China, patient-derived organoid and xenograft resources have expanded through clinical and academic studies, enterprise-operated platforms, and conventional hospital biobank support for clinical sourcing and quality management. Published studies demonstrate disease-focused living resources in common tumors as well as selected premalignant and less common settings. Clinical and academic groups provide clinically annotated specimens and outcome context, whereas enterprise-operated platforms describe model-generation workflows, functional testing modules, database interfaces, and preclinical service capacity. Together, these activities suggest a transition from project-based model collections toward translational research infrastructure. However, public catalogues, model-level quality descriptors, case-model-data linkage, and access mechanisms remain uneven. This review summarizes representative Chinese resources and enterprise platform types, discusses international benchmark functions for model-biobank maturity, and emphasizes quality transparency for external verification and resource discovery. Future development should strengthen minimum information fields, quality reporting, and governance mechanisms that allow model resources to be discovered and used under appropriate access control.
Prostate cancer ranks among the most prevalent male malignancies worldwide, with castration-resistant prostate cancer (CRPC) and drug resistance representing major clinical challenges. Conventional preclinical models fail to faithfully recapitulate tumor heterogeneity and the tumor microenvironment (TME). Patient-deriv...
Jing-Zhen Zhu, Sheng Wang, Fu-Rong Du et al.· Frontiers in Oncology· 0 citations
Background/Aim: The present study aimed to establish patient-derived organoid (PDO) and patient-derived xenograft (PDX) models from clinical gastric cancer (GC) tissue samples and analyze their drug sensitivity data to evaluate their translational value in GC research. The present study investigated the integrated cons...
UniCure is presented, a multi-modal model that combines biological and chemical foundation models to predict drug-induced transcriptomic responses across diverse cell and tissue contexts, enabling individualized drug ranking.
Ze-Xi Chen, Saisai Tian, Jia-Zheng Pei et al.· Cancer Cell· 0 citations
Hepatobiliary cancers are highly heterogeneous malignant tumors, and the drug resistance frequently emerges at advanced stages. Patient-derived organoids (PDOs) are three-dimensional ex vivo cultures. They can reproduce essential biological aspects of primary tumors, and play a key role in personalized oncology. With a...
Senyan Wang, Yi-Xuan Liu, Qi Liu et al.· Cancer Letters· 0 citations
Summary Cancer cell lines (CLs) are widely used to study tumor biology and drug response, yet their translational relevance is often limited by inaccurate subtype annotations. Existing CL-tumor matching approaches are frequently constrained by flat classification schemes, weak subtype definitions, and the exclusion of...
Juho Mikkonen, T. Rintala, V. Fortino· iScience· 0 citations
Patient-derived organoids (PDOs) are widely used platforms for cancer modeling and precision oncology because they preserve patient-specific genetic backgrounds, recapitulate aspects of native tissue architecture, and allow long-term expansion, repeated functional interrogation, and drug screening. Accordingly, multi-o...
J. Lim, Yeju Kim, Jin-Ku Lee· Organoid· 0 citations
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