Normalized data.

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.