ReviewCells2025
Advancing Glioblastoma Research with Innovative Brain Organoid-Based Models.
Review in Cells, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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
12 citing papers in PubMed.
- TREM2 in glioma: Reprogramming the immune microenvironment from mechanistic understanding to clinical translation (Review).Molecular medicine reports · 2026Review
- Organoids as brain tumour models: bridging the translational gap.Disease models & mechanisms · 2026Review
- Organoids as next-generation models for investigating intracranial tumours.Molecular brain · 2026Review
- Organoids to Model Tumor Microenvironment in Progression of Pathogenesis and Treatment Resistance in Glioblastoma Multiforme.Brain sciences · 2026Review
- Review
- Progress in the study of molecular markers in the prognosis assessment and recurrence patterns of glioblastoma.Cancer biology & therapy · 2025Review
- Modeling Glioblastoma with Brain Organoids: New Frontiers in Oncology and Space Research.International journal of molecular sciences · 2025Review
- Review
- Review
- Gene- and cell-based therapy in cardiovascular diseases.Journal of cardiovascular pharmacology · 2025Article
- Kinase-Targeted Therapies for Glioblastoma.International journal of molecular sciences · 2025Review
- Advanced deep learning-based brain tumor classification using a novel customized CNN and optimized residual network.PloS one · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Glioblastoma (GBM) is a relatively rare but highly aggressive form of brain cancer characterized by rapid growth, invasiveness, and resistance to standard therapies. Despite significant progress in understanding its molecular and cellular mechanisms, GBM remains one of the most challenging cancers to treat due to its high heterogeneity and complex tumor microenvironment. To address these obstacles, researchers have employed a range of models, including in vitro cell cultures and in vivo animal models, but these often fail to replicate the complexity of GBM. As a result, there has been a growing focus on refining these models by incorporating human-origin cells, along with advanced genetic techniques and stem cell-based bioengineering approaches. In this context, a variety of GBM models based on brain organoids were developed and confirmed to be clinically relevant and are contributing to the advancement of GBM research at the preclinical level. This review explores the preparation and use of brain organoid-based models to deepen our understanding of GBM biology and to explore novel therapeutic approaches. These innovative models hold significant promise for improving our ability to study this deadly cancer and for advancing the development of more effective treatments.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.