ReviewNeuro-oncology2026
Modeling gliomas with organoids: Classification, fidelity, and guidelines for translational neuro-oncology.
Review in Neuro-oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Modeling gliomas with organoids: reconstructing the human neural microenvironment for translational neuro-oncology.Frontiers in oncology · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
Abstract
Advances in organoid technology have transformed how gliomas are modeled and studied. Recent FDA and NIH initiatives further promote human-relevant organoid platforms for preclinical research. Glioma organoids can be broadly categorized into 3 main classes: Engineered organoids, which enable controlled modeling of gliomagenesis driven by specific mutations; patient-derived organoids, which preserve key molecular and histopathological features of the original tumors; and assembloids, which are designed to model tumor-microenvironment interactions. Together, these systems provide a human cell-relevant framework for investigating glioma biology, tumor-microenvironment crosstalk, and therapeutic responses and resistance. In this review, we provide a comprehensive overview of the spectrum of glioma organoid models, recognizing that different systems offer distinct and complementary strengths, and we offer practical guidance for selecting appropriate models and analytical readouts based on specific basic and translational research objectives. To address increasing methodological heterogeneity and fragmented terminology, we propose a foundational nomenclature framework for glioma organoid models to improve clarity and communication within the field. We highlight applications in technically challenging subtypes, including isocitrate dehydrogenase (IDH)-mutant gliomas and diffuse midline gliomas (DMGs). We also discuss key challenges-including scalability, standardization, microenvironment fidelity, and vascularization-and emerging innovations addressing these limitations. Finally, we call for greater collaboration and standardization within the glioma organoid community to accelerate the integration of organoid models into translational pipelines to redefine and refine preclinical modeling in neuro-oncology.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.