Anticancer research · 2026
Integrating Patient-derived Organoid and Patient-derived Xenograft Models to Guide Precision Chemotherapy for Gastric Cancer.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Yan Hezhong, He Xing, Hou Xilu, Liao Guobin, Li Haiqing, Duan Xiaowei, Wang Jiaoxue, Gao Qian, Yu Senyuan, Guo Shicun, Zhang Mingjin, Ma Honglin, Tang Jun
Аннотация
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 construction of PDOs and PDXs from the same patient and evaluated their utility in individualized drug sensitivity prediction and clinical translation.
MATERIALS AND METHODS: By constructing GC PDOs and PDXs, drug sensitivity assays with multiple agents were performed and validated results against clinical therapeutic responses. Endoscopic and surgical GC specimens were synchronously processed to generate paired PDO and PDX models from identical patient tissues. Model fidelity was validated using hematoxylin and zeosin (H&E) staining, immunohistochemistry (IHC) and short tandem repeat (STR) profiling. In vitro drug sensitivity testing and in vivo PDX pharmacodynamic validation were performed and predicted outcomes were compared to clinical treatment responses.
RESULTS: The findings demonstrated that PDOs and PDXs effectively preserve key histopathological and genetic features of the original tumors, with high concordance between drug sensitivity profiles and actual clinical outcomes, providing a platform for precision therapy in GC. Both PDOs and PDXs recapitulated the histological features of primary tumors. IHC confirmed their consistency with the original tissue profiles, while STR analysis demonstrated >90% genetic matching between the models and the source tissues. The integrated PDO-PDX platform showed a high correlation in predicting drug sensitivity.
CONCLUSION: The integrated PDO-PDX platform achieved clinical concordance in predicting drug sensitivity, providing a platform for precision therapy in GC.
MATERIALS AND METHODS: By constructing GC PDOs and PDXs, drug sensitivity assays with multiple agents were performed and validated results against clinical therapeutic responses. Endoscopic and surgical GC specimens were synchronously processed to generate paired PDO and PDX models from identical patient tissues. Model fidelity was validated using hematoxylin and zeosin (H&E) staining, immunohistochemistry (IHC) and short tandem repeat (STR) profiling. In vitro drug sensitivity testing and in vivo PDX pharmacodynamic validation were performed and predicted outcomes were compared to clinical treatment responses.
RESULTS: The findings demonstrated that PDOs and PDXs effectively preserve key histopathological and genetic features of the original tumors, with high concordance between drug sensitivity profiles and actual clinical outcomes, providing a platform for precision therapy in GC. Both PDOs and PDXs recapitulated the histological features of primary tumors. IHC confirmed their consistency with the original tissue profiles, while STR analysis demonstrated >90% genetic matching between the models and the source tissues. The integrated PDO-PDX platform showed a high correlation in predicting drug sensitivity.
CONCLUSION: The integrated PDO-PDX platform achieved clinical concordance in predicting drug sensitivity, providing a platform for precision therapy in GC.