In-situ polymerization-mediated glycan density measurement on extracellular vesicle surface for acute myeloid leukemia diagnosis.
Extracellular vesicles (EVs) have emerged as promising circulating biomarkers for diverse pathologies, yet clinical adoption remains limited due to inter-patient variability in blood EV concentrations
APA
Wu X, Long W, et al. (2026). In-situ polymerization-mediated glycan density measurement on extracellular vesicle surface for acute myeloid leukemia diagnosis.. Journal of nanobiotechnology. https://doi.org/10.1186/s12951-026-04400-7
MLA
Wu X, et al.. "In-situ polymerization-mediated glycan density measurement on extracellular vesicle surface for acute myeloid leukemia diagnosis.." Journal of nanobiotechnology, 2026.
PMID
41981648
Abstract
Extracellular vesicles (EVs) have emerged as promising circulating biomarkers for diverse pathologies, yet clinical adoption remains limited due to inter-patient variability in blood EV concentrations, which introduces inconsistent biomarker signals and reduces diagnostic reliability. To address this, we developed an in-situ dopamine polymerization method for precise glycan density quantification on EVs expressing a specific membrane protein. EV membrane proteins were labeled using streptavidin-horseradish peroxidase-conjugated aptamers, while surface lipids and glycans were simultaneously tagged with fluorescent cholesterol and lectin, respectively. Controlled dopamine polymerization spatially restricted fluorescence quenching to EV membranes, enabling glycan density calculation via attenuation profiles of cholesterol- and lectin-bound fluorophores. The method was miniaturized into a microfluidic platform for rapid (< 1 h), wash-free point-of-care analysis. In 47 clinical specimens (16 patients with acute myeloid leukemia, 15 patients with benign hematological diseases, and 16 healthy donors), glycan density normalization reduced inter-patient variability compared to absolute measurements. Multi-lectin analysis of CD133 EV glycan density achieved superior diagnostic accuracy (AUC = 0.904) in distinguishing acute myeloid leukemia from benign hematological diseases, outperforming direct glycan quantification. By integrating surface biophysical normalization, this platform enhances EV biomarker consistency, providing a rapid, blood-based diagnostic tool with clinical translatability for acute myeloid leukemia.
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