ArticlePloS one2025
Identification of distinct profiles of glioblastoma through the immunocapture of extracellular vesicles from patient plasma.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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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.
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Who cites it
4 citing papers in PubMed.
- Extracellular Vesicles as Master Regulators of Immune Modulation in Multiple Myeloma.International journal of molecular sciences · 2026Review
- Extracellular Vesicles From Glioblastoma Cells Reflect 2D vs. 3D Culture Adaptation and Resistance to Temozolomide.Molecular & cellular proteomics : MCP · 2026Article
- 'Molecular and Cellular Neuroscience': Impacts of Eight Highly Cited Articles Published in This Section ofBrain sciences · 2026Article
- The glioblastoma GBMdrug1000 dataset resource provides directions for future small molecule drug discovery.Neuro-oncology advancesArticle
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Glioblastoma (GBM), a primary brain tumor, exhibits intratumoral heterogeneity and dynamic spatial-temporal changes. GBM-derived extracellular vesicles (EVs), reflecting tumor characteristics, present potential as liquid-biopsy markers for early diagnosis and monitoring. This study aims to evaluate molecular signatures of plasma-derived EVs from GBM patients using a conventional flow cytometer. EVs have been isolated from glioma patients and healthy controls (HCs) plasma using density gradient ultracentrifugation (DGU). EVs were evaluated by bead-based multiplex analysis in a conventional flow cytometer. Principal component analysis (PCA), hierarchical clustering, and correlation analysis provided comprehensive insights into EV characteristics. EVs successfully isolated were visualized in transmission and scanning electron microscopy (STEM). Bead-based multiplex analysis in flow cytometer detected the level of 37 EV surface markers, including tumor-related, cancer stem cell, endothelial cell, and immune cell- specific antigens. PCA identified the EV surface markers that are most significant for differentiating the subjects, and hierarchical clustering revealed four distinct clusters based on EV surface marker levels. EV molecular signature demonstrated considerable heterogeneity across patient clusters. The presence of CD29 emerged not only as a defining factor for a cluster of patients, but also served as a marker to differentiate patients from HCs.
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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.