ArticleMolecular cancer2025
Exploring personalized prediction of clinical chemotherapy efficacy and revealing tumor heterogeneity using patient-derived 3D bioprinting gastric cancer models.
Article in Molecular cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed.
- Emerging organoids and organoids-on-chip platforms for translational development of antibody‒drug conjugates and next-generation bioconjugates.Acta pharmaceutica Sinica. B · 2026Review
- Spatial architecture and dynamic surveillance: 3D bioprinting and microfluidics converge to overcome digestive malignancies.Hepatobiliary surgery and nutrition · 2026Article
- Cancer Heterogeneity and Cancer Cell Plasticity: Molecular Mechanisms and Precision Therapy.MedComm · 2026Review
- 3D bioprinting for cancer modeling and drug screening.Biomarker research · 2026Review
- Deconstructing cancer in 3D: models, mechanisms, and personalized solutions.Molecular cancer · 2026Review
- 3D bioprinted in vitro models in cancer metabolism research.Magyar onkologia · 2026Review
- Patient-Derived 3D-Bioprinted Intrahepatic Cholangiocarcinoma Models Recapitulate Tumor Autologous Traits and Predict Personalized Adjuvant Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Convergent bioprinting and microfluidics: toward next-generation biomimetic tumor models.Hepatobiliary surgery and nutrition · 2026Article
- Organoids glimpse: the nexus for diverse tumor heterogeneity.Frontiers in cell and developmental biology · 2026Review
- Patient-derived organoids in gastric cancer: bridging the tumor microenvironment to functional precision oncology.Frontiers in bioengineering and biotechnology · 2026Review
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Authors and funding
15 authors.
Funding
Abstract
backgroundThe pronounced chemotherapeutic heterogeneity observed in gastric cancer (GC) poses significant challenges to personalized treatment strategies, with current approaches lacking reliable predictive modalities for chemotherapy efficacy and postoperative prognosis. While patient-derived organoid (PDO) and xenograft (PDX) models serve as established three-dimensional platforms, their prohibitive costs and inherent batch effect limit faithful replication of native tumor extracellular matrix (ECM) complexity.
methodsWe utilized patient-derived GC tissues to construct individualized 3D bioprinting (3DP)-GC models. After screening bioinks for optimal mechanical properties and biocompatibility, we successfully and efficiently constructed 3DP-GC models of 33 patients, and performed histopathological and genomic analyses to determine that the 3DP-GC model effectively preserved the histological architecture, biomarker expression abundance and genetic mutation profiles of the parental tumors. Drug screening on the 3DP-GC models was conducted using clinical gastric cancer therapies. Retrospective analysis of patients’ post-neoadjuvant therapy and follow-up of those post-adjuvant therapies were performed to evaluate the model’s potential in predicting and selecting chemotherapeutic agents for gastric cancer patients.
resultsIn this study, we successfully and efficiently constructed 3D in vitro models of 33 GC patients using 3D bioprinting technology, and performed histopathological and genomic validation to find that the 3DP-GC model well preserved the expression abundance and mutation profiles of markers in the parental tumors. A significant correlation was observed in drug sensitivity between the 3DP-GC platform and the actual clinical efficacy observed in patients.
conclusionOur study establishes a robust and stable 3DP-GC model. Crucially, drug testing of 3DP-GC model can accurately predict the clinical chemotherapy of patients in a shorter time and at a lower cost, offering a promising tool for high-throughput drug screening and personalized treatment decision-making.
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