ReviewCancers2025
Choice of Animal Models to Investigate Cell Migration and Invasion in Glioblastoma.
Review in Cancers, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Integrated 3D light sheet and 2D multiplex imaging for deep histological characterization of somatic mouse glioblastoma.iScience · 2026Article
- Organoids as next-generation models for investigating intracranial tumours.Molecular brain · 2026Review
- Glioblastoma invasion into different organoid hosts reveals cell-intrinsic and proliferative migratory programs.iScience · 2026Article
- Emerging In Vivo Imaging Modalities for Improved Glioblastoma Surgery and Monitoring.Biomedicines · 2026Review
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Glioblastoma is an aggressive and prevalent form of brain cancer characterized by rapid tumor cell migration and invasion into surrounding healthy tissues, making it resistant to conventional treatments. Despite advances in therapeutic approaches, patient prognosis remains poor, with a median survival of approximately 15 months. Tumor cell infiltration along perivascular spaces and white matter tracts is a major driver of recurrence, underscoring the need for experimental models that accurately capture these invasive behaviors. Animal models remain indispensable for this purpose, offering insights that cannot be fully replicated in vitro. This review focuses on applying animal models to elucidate the mechanisms underlying glioblastoma cell migration and invasion, which remain critical to improving therapeutic outcomes. By comparing the advantages of animal models with in vitro systems, we highlight the unique insights animal models provide, particularly in capturing the intricate dynamics of tumor cell motility. In particular, patient-derived xenograft (PDX) models preserve patient-specific heterogeneity and invasion patterns, such as white matter tract and perivascular infiltration, enabling clinically relevant drug testing. Zebrafish xenografts provide real-time, high-resolution visualization of tumor-vascular interactions, facilitating rapid assessment of invasion dynamics and early-stage drug screening. Genetically engineered models (GEM) allow precise discrimination of how defined genetic alterations drive specific invasive routes in the brain. Furthermore, we explore the use of advanced imaging techniques in these models to monitor tumor progression in real time. Moreover, we discuss the major drawbacks of these animal models, such as incomplete immune components and tumor microenvironment recapitulation. Ultimately, animal models are essential for bridging the gap between basic research and clinical application, offering a powerful platform for developing targeted strategies to combat glioblastoma's relentless progression.
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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.