Self-Localized Plasmonic Nanocavity Strategy for the Glycosylation Detection of Glioblastoma Extracellular Vesicles
The protein glycosylation of extracellular vesicles (EVs) is involved in cellular recognition and emerges as a promising biomarker for cancer diagnosis. However, the lack of efficient labeling and high-resolution detection strategies limits their clinical application. Herein, we developed a self-localized plasmonic nanocavity strategy to analyze the glycosylation characteristics of glioblastoma EVs. First, an engineered phospholipid bilayer structure with a Au nanoring array was designed to capture EVs and induce membrane fusion. Relying on the multifunctional proximity labeling process, a peroxidase-induced proximity labeling was designed to label sialic acid on programmed cell death ligand 1 (PD-L1) of EVs. Based on the identification and labeling process of EVs, the plasmonic nanocavity was self-localized with Au nanocubes and achieved the spontaneous location of MoSe<sub>2</sub> QDs. The uniformly enhanced electromagnetic field in the nanocavity resulted in the polarized luminescence signal of MoSe<sub>2</sub> QDs for improving the detection sensitivity and resolution. This system demonstrated the precise distinction and sensitive quantification of EV glycosylation in cerebrospinal fluid to distinguish glioblastoma. This research provided a novel strategy for the glycosylation detection of EVs and promoted the clinical application of EVs in glioblastoma diagnosis.
Authors
- Zihui Liang (ORCID: https://orcid.org/0000-0002-8846-8956)
- Zhenrun Li
- Wenyan Li (ORCID: https://orcid.org/0000-0001-9575-7812)
- Qiang Ma (ORCID: https://orcid.org/0000-0002-9193-9341)
- Peilin Wang
Institutions
- Jilin University (CN)
- Jilin Medical University (CN)
- Czech Academy of Sciences, Institute of Analytical Chemistry (CZ)
Publication Details
- Journal
- Analytical Chemistry
- Published
- 2025-02-21
- DOI
- https://doi.org/10.1021/acs.analchem.4c06670
- Citations
- 3
- Primary Topic
- Advanced biosensing and bioanalysis techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.42
Funders
- National Natural Science Foundation of China
- Jilin University