ArticleAdvanced science (Weinheim, Baden-Wurttemberg, Germany)2025
Bioprinted Patient-Derived Organoid Arrays Capture Intrinsic and Extrinsic Tumor Features for Advanced Personalized Medicine.
Article in Advanced science (Weinheim, Baden-Wurttemberg, Germany), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
16 citing papers in PubMed.
- Tissue-derived extracellular matrix hydrogels instruct epigenetic adaptation in metastatic colonization.Bioactive materials · 2027Article
- Biofabrication for spatial control of multiscale biological crosstalk in tissue models.npj biomedical innovations · 2026Review
- Three-dimensional spheroid models in breast cancer: tumor microenvironment complexity, cancer stem cell-driven resistance, and translational model integration.Journal of translational medicine · 2026Review
- Translational insights and clinical challenges of targeting cancer stem cells.Signal transduction and targeted therapy · 2026Review
- Harnessing human tumor organoids for cancer modeling and precision therapy.Protein & cell · 2026Review
- Alveolar organoids: from model systems to applications in respiratory diseases.Journal of translational medicine · 2026Review
- Emerging nano-immunotherapeutic strategies achieve metastatic colorectal cancer precision therapy.Journal of nanobiotechnology · 2026Review
- Organoids glimpse: the nexus for diverse tumor heterogeneity.Frontiers in cell and developmental biology · 2026Review
- Reconstructing the Tumor Mechanical Microenvironment in Organoids: From Mechanical Cues to Biomimetic Modeling and Therapeutic Insights.International journal of medical sciences · 2026Review
- Patient-derived organoids (PDOs) as a promising platform for personalized treatment of colorectal cancer: current applications and future challenges.Cancer biology & therapy · 2025Review
- Three-dimensional bioprinting of patient-derived Gastrointestinal stromal tumor: a novel platform for precision oncology and drug response profiling.Journal of nanobiotechnology · 2025Article
- 3D Bioprinting and Artificial Intelligence for Tumor Microenvironment Modeling: A Scoping Review of Models, Methods, and Integration Pathways.Molecular pharmaceutics · 2025Article
- Bioprinting for drug screening: A path toward reducing animal testing or redefining preclinical research?Bioactive materials · 2025Review
- Innovative strategies for bone organoid: Synergistic application and exploration of advanced technologies.Journal of orthopaedic translation · 2025Review
- Bioprinted Patient-Derived Organoid Arrays Capture Intrinsic and Extrinsic Tumor Features for Advanced Personalized Medicine.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Cancer patient-derived organoids: Novel models for the study of natural products.International journal of biological sciences · 2025Review
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Authors and funding
16 authors.
Funding
Abstract
Heterogeneity and the absence of a tumor microenvironment (TME) in traditional patient-derived organoid (PDO) cultures limit their effectiveness for clinical use. Here, Embedded Bioprinting-enabled Arrayed PDOs (Eba-PDOs) featuring uniformly arrayed colorectal cancer (CRC) PDOs within a recreated TME is presented. This model faithfully reproduces critical TME attributes, including elevated matrix stiffness (≈7.5 kPa) and hypoxic conditions found in CRC. Transcriptomic and immunofluorescence microscopy analysis reveal that Eba-PDOs more accurately represent actual tissues compared to traditional PDOs. Furthermore, Eba-PDO effectively capture the variability of CEACAM5 expression-a critical CRC marker-across different patients, correlating with patient classification and differential responses to 5-fluorouracil treatment. This method achieves an uniform size and shape within PDOs from the same patient while preserving distinct morphological features among those from different individuals. These features of Eba-PDO enable the efficient development of a label-free, morphology-based predictive model using supervised learning, enhancing its suitability for clinical applications. Thus, this approach to PDO bioprinting is a promising tool for generating personalized tumor models and advancing precision medicine.
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Registered trials
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