Establishment and Characterization of Patient-Derived Xenograft Models for Osteosarcoma Lung Metastases

Da LI , Tao YI , Yuqin YANG

Journal of Donghua University(English Edition) ›› 2026, Vol. 43 ›› Issue (3) : 92 -100.

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Journal of Donghua University(English Edition) ›› 2026, Vol. 43 ›› Issue (3) :92 -100. DOI: 10.19884/j.1672-5220.202503030
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Establishment and Characterization of Patient-Derived Xenograft Models for Osteosarcoma Lung Metastases
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Abstract

This study aims to investigate the feasibility and optimization of patient-derived xenograft (PDX) models for osteosarcoma lung metastases by comparing subrenal capsule and subcutaneous implantation methods. Three osteosarcoma lung metastasis samples meeting the inclusion criteria were implanted into NDG mice using both methods. Tumor growth, histological characteristics, immunohistochemical marker expression, and gene expression profiles were analyzed at eight weeks post-implantation. All three samples successfully established PDX models, with subrenal capsule implantation yielding significantly larger tumor volumes in two cases (p < 0.05). Histopathological and immunohistochemical analyses demonstrated high morphological similarity between the two models, with Ki67, CD99, and PD-L1 expression retained. Transcriptomic sequencing revealed a strong correlation in global gene expression between the two models (R > 0.8), with osteosarcoma-specific genes displaying similar expression patterns. These findings suggest that subrenal capsule implantation provides a stable and efficient approach for generating PDX models from limited osteosarcoma lung metastasis tissues while maintaining key biological characteristics comparable to those of subcutaneous models.

Keywords

osteosarcoma / lung metastasis / patient-derived xenograft (PDX) model / subrenal capsule implantation / subcutaneous implantation

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Da LI, Tao YI, Yuqin YANG. Establishment and Characterization of Patient-Derived Xenograft Models for Osteosarcoma Lung Metastases. Journal of Donghua University(English Edition), 2026, 43 (3) : 92-100 DOI:10.19884/j.1672-5220.202503030

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Science and Technology Innovation Action Plan of Shanghai Science and Technology Commission(23141903200)

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