4.8 Article

Precise Identification and Profiling of Surface Proteins of Ultra Rare Tumor Specific Extracellular Vesicle with Dynamic Quantitative Plasmonic Imaging

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ACS NANO
卷 17, 期 17, 页码 16656-16667

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AMER CHEMICAL SOC
DOI: 10.1021/acsnano.3c02853

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Single-EV analysis; dynamicimmunoassay; liquidbiopsy; surface plasmon resonance microscopy; pancreaticcancer

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This study presents a kinetic assay called DISEP, which utilizes surface plasmon resonance microscopy (SPRM) to accurately identify tumor-derived EVs (tEVs) and profile their surface protein expression in clinical plasma. DISEP shows high sensitivity and specificity in detecting tEVs, and it has been successfully used to discriminate between pancreatic cancer patients and healthy donors with a panel of biomarker signatures.
Specific detection of tumor-derived EVs (tEVs) in plasma is complicated by nontumor EVs and non-EV particles. To accurately identify tEVs and profile their surface protein expression at single tEV resolution directly with clinical plasma is still an unmet need. Here, we present a Dynamic Immunoassay for Single tEV surface protein Profiling (DISEP), a kinetic assay based on surface plasmon resonance microscopy (SPRM) for specific single tEV profiling. DISEP adopts a pair of low-affinity oligonucleotide probes to respectively label EV surface proteins and functionalize an SPRM biosensor interface. tEVs labeled with the oligonucleotide probes possess distinctive binding kinetics from nonspecific particles in plasma, which permits accurate digital plasmonic counting of single EVs. We demonstrate DISEP for recognizing target EVs among 350-fold background plasma particles with high sensitivity (4677 EVs per mu L). Clinical plasma samples were analyzed to discriminate between pancreatic cancer patients (n = 40) and healthy donors (n = 45). With a panel of biomarker signatures (EpCAM, HER2, and GPC1), DISEP only requires 10 mu L primary sample from each donor to classify tumor patients with an area under the curve of 0.98. DISEP provides a highly specific EV detection and surface protein profiling strategy for early cancer diagnosis.

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