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Updated: Jun 20, 2026

Creating Matched In vivo/In vitro Patient-Derived Model Pairs of PDX and PDX-Derived Organoids for Cancer Pharmacology Research
Published on: May 5, 2021
Engineering cell ring organoids for efficient establishment of patient-derived orthotopic xenotransplantation
Yan Xu1, Zhicheng Tong2, Xian'an Li1
1Department of Thoracic Internal Medicine, Hunan Cancer Hospital and The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, 410013, China.
Abstract:
Patient-derived orthotopic xenotransplantation (PDOX) models have recently emerged as a potential approach for experimental therapeutics and precision medicine in malignant disease. However, the clinical application of PDOX models was restricted by the varying success rate of the animal models, long generation time, limited number of patient tumor cells and distinct stromal environments. To address this critical barrier, we developed an innovative patient-derived cell ring organoid platform using scaffold-free tumor cell rings. By co-culturing primary sarcoma cells with human skin fibroblasts (HSFs), functional tumor microenvironment (TME) -incorporated organoids were generated within 48 h without exogenous matrices. These organoids enabled rapid establishment of orthotopic xenografts (r-PDOX) in ≤7 days with 100% engraftment efficiency while requiring 50% fewer cells than conventional methods. Crucially, integrated HSFs replicated desmoplastic stroma and vascular networks, preserving patient-specific molecular profiles (transcriptomic correlation r = 0.87) and biological processes. As a preliminary proof-of-concept, the r-PDOX models showed encouraging concordance with patient responses to first-line therapeutics, including ifosfamide and anlotinib, though validation in larger cohorts is required. This platform overcomes key limitations of existing sarcoma models - including cell leakage, phenotypic drift, and protracted timelines, offering a physiologically relevant tool for personalized therapy exploration. The platform represents a promising methodological foundation for rapid sarcoma preclinical modeling in the era of precision oncology.

