Fingerprint Profiling of Glycans on Extracellular Vesicles via Lectin-Induced Aggregation Strategy for Precise Cancer Diagnostics
Extracellular vesicles (EVs) harbor abundant glycans that mediate various functions, such as intercellular communication and disease advancement, which play significant roles in disease progression. However, the presence of EV heterogeneity in body fluids and the complex nature of the glycan structu...
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| Published in | Journal of the American Chemical Society Vol. 146; no. 42; pp. 29053 - 29063 |
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| Main Authors | , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
American Chemical Society
23.10.2024
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0002-7863 1520-5126 1520-5126 |
| DOI | 10.1021/jacs.4c10390 |
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| Summary: | Extracellular vesicles (EVs) harbor abundant glycans that mediate various functions, such as intercellular communication and disease advancement, which play significant roles in disease progression. However, the presence of EV heterogeneity in body fluids and the complex nature of the glycan structures have posed challenges for the detection of EV glycans. In this study, we provide a streamlined method integrated, membrane-specific separation with lectin-induced aggregation strategy (MESSAGE), for multiplexed profiling of EV glycans. By leveraging a rationally designed lectin-induced aggregation strategy, the expression of EV glycans is converted to size-based signals. With the assistance learning machine algorithms, the MESSAGE strategy with high sensitivity, specificity, and simplicity can be used for early cancer diagnosis and classification, as well as monitoring cancer metastasis via 20 μL plasma sample within 2 h. Furthermore, our platform holds promise for advancing the field of EV-based liquid biopsy for clinical applications, opening new possibilities for the profiling of EV glycan signatures in various disease states. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 0002-7863 1520-5126 1520-5126 |
| DOI: | 10.1021/jacs.4c10390 |