This study set out to create and evaluate an integrated preclinical platform combining patient-derived organoid (PDO) and patient-derived xenograft (PDX) models generated from the same gastric cancer (GC) patient specimens. The primary objective was to determine whether paired PDOs and PDXs can preserve key tumor characteristics and reliably predict drug sensitivity in a way that correlates with actual clinical therapeutic responses, thereby supporting precision chemotherapy decisions for GC.
Clinical gastric cancer specimens obtained by endoscopy and surgery were processed synchronously to produce matched PDO and PDX models from identical patient tissues. The work included establishing organoid cultures and engrafting tumor tissue to generate xenografts, followed by a series of fidelity and drug testing assays. The models underwent histopathological and molecular validation before drug sensitivity experiments.
Model fidelity and identity were examined using hematoxylin and eosin (H&E) staining for morphology, immunohistochemistry (IHC) to compare protein expression profiles, and short tandem repeat (STR) profiling to confirm genetic matching between the derived models and the originating tumors. Drug sensitivity was assessed using in vitro assays on PDOs and in vivo pharmacodynamic evaluations in PDXs. Predicted responses from these assays were compared to the patients’ real-world clinical treatment outcomes to evaluate translational concordance.
Both PDOs and PDXs were evaluated for preservation of the original tumor’s histopathological features. H&E staining demonstrated that the derived models recapitulated the morphological characteristics of the primary GC specimens. IHC profiling confirmed that key antigen expression patterns remained consistent between the source tumor tissue and both model types.
STR analysis was used to verify genetic identity and showed greater than 90% matching between the models and the source tissues, supporting the conclusion that the PDOs and PDXs maintained a high degree of genetic fidelity to the original tumors.
The integrated platform combined in vitro drug-sensitivity assays on PDOs with in vivo pharmacodynamic validation in corresponding PDX models. Multiple antineoplastic agents were tested across the platform, allowing the authors to evaluate whether drug responses observed in organoid cultures translated to drug efficacy in xenograft-bearing animals and to the clinical responses of the patients from whom the models were derived.
Model-derived sensitivity profiles were compared directly with clinical therapeutic responses, enabling assessment of the platform’s predictive accuracy for individual patient treatments.
The study found that PDOs and PDXs from the same patient effectively preserved the histological and molecular features of the original gastric tumors, as evidenced by concordant H&E and IHC findings and STR genetic matching exceeding 90%.
Drug sensitivity results from PDOs and PDXs were highly correlated with each other and aligned closely with the actual clinical responses of the patients. The integrated PDO–PDX approach therefore demonstrated substantial translational value: it could reproduce tumor biology and provide concordant predictions of drug sensitivity that matched patient outcomes, supporting its potential utility for guiding precision chemotherapy in GC.
The integrated PDO–PDX platform achieved clinical concordance in predicting drug sensitivity for gastric cancer, indicating it can serve as a translational tool to support individualized chemotherapy selection. By combining rapid in vitro organoid screening with in vivo PDX validation, the approach offers a complementary strategy to inform therapeutic decisions and to bridge preclinical testing with clinical treatment responses.
The abstract reports overall design, validation methods (H&E, IHC, STR) and broad outcomes (model fidelity, >90% STR match, high concordance with clinical responses), but does not provide several details in the PubMed abstract. Specific items not reported in the source abstract include:
Because these items were not included in the abstract text provided, they could not be summarized here. The full publication would need to be consulted for precise experimental numbers, drug lists, timelines, and statistical evidence.
Within the scope reported, the integrated PDO–PDX strategy offers a translationally relevant platform for precision medicine in gastric cancer. When models faithfully mirror tumor histology, immunophenotype and genetics—and when model drug-response profiles align with clinical outcomes—the combined organoid/xenograft pipeline can help prioritize chemotherapy options tailored to individual patients. Further details from the full text would clarify operational timelines, throughput, and the platform’s readiness for routine clinical application.