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April 18, 2026ACS Sensors7 citations

Biological Optical Nanocavity-Coupled Electrochemiluminescence Sensor for the Detection of Extracellular Vesicle Glycosylation in Gastric Cancer Diagnosis

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PWPeilin WangZLZhenrun LiWLWenyan Li

Key Points

  • This research aims to develop a sensor that detects glycosylation patterns in extracellular vesicles related to gastric cancer.
  • Developed an electrochemiluminescence sensor coupled with a biological optical nanocavity.
  • Used curvature-sensitive peptide probes for region-specific recognition of EVs.
  • Constructed plasmonic effects by assembling gold nanoparticles on EV membranes.
  • Achieved a detection limit of 3.2 × 10³ particles mL⁻¹ for EVs.
  • Diagnostic accuracy of 95% for detecting peritoneal metastasis in gastric cancer.
  • Identified preferential distribution of MUC1 with terminal sialylation in high curvature EV regions.

Abstract

Biological membrane curvature not only signifies morphological characteristics but also participates in various physiological processes. Analyzing the relationship between membrane curvature and biomolecules of extracellular vesicles (EVs) is crucial for understanding their functions. However, it remains challenging to precisely distinguish the characteristics of EVs in specific membrane regions. Herein, we developed a biological optical nanocavity-coupled electrochemiluminescence (ECL) sensor to reveal the correlation between the glycoprotein and membrane curvature of EVs. A curvature-sensitive peptide probe anchored the high curvature membrane of EVs and conducted the proximity ligation with aptamers, enabling the region-specific recognition. By assembling Au NPs onto the membrane surface of EVs, a biological optical nanocavity was constructed, which provided a plasmon coupling effect to enhance the ECL intensity and regulate the polarized emission. The polarized ECL response clearly distinguished both the specific region and molecular distribution of EVs. Our findings indicated that MUC1 with terminal sialylation exhibited preferential distribution in high curvature regions of EV membranes. Furthermore, the detection of EVs in ascites facilitated the diagnosis of peritoneal metastasis in gastric cancer. The proposed ECL sensor achieved sensitive EVs detection with a limit of detection of 3.2 × 103 particles mL-1 and the diagnostic accuracy of 95%. Overall, the research provided a sensitive strategy for the analysis of EVs' membrane nano-environment and explored the potential of EVs in assisting clinical diagnosis.

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Cite This Study

Wang et al. (2026) studied this question.

synapsesocial.com/papers/69e3211640886becb6540402https://doi.org/10.1021/acssensors.6c00361
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