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Updated: Dec 1, 2025

Multimodal Analytical Platform on a Multiplexed Surface Plasmon Resonance Imaging Chip for the Analysis of Extracellular Vesicle Subsets
Published on: March 17, 2023
A facile, rapid, high-throughput extracellular vesicles analytical platform for cancer detection
Zaian Deng1, Yong Wang2, Liang Hu3
1The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang 325035, China; School of Ophthalmology & Optometry, School of Biomedical Engineering, Wenzhou Medical University, Wenzhou, Zhejiang 325035, China; Wenzhou Institute of Biomaterials & Engineering, Wenzhou Institute, University of Chinese Academy of Sciences, Wenzhou, Zhejiang 325000, China; College of Health Science and Environmental Engineering, Shenzhen Technology University, Shenzhen, Guangdong 518118, China.
Abstract:
Cell-derived nanoparticles, so called Extracellular Vesicles (EVs), can reflect the physiological or pathological conditions of donor cells and can provide promising biomarkers for the non-invasive diagnosis of cancers. Size-based purification method is one of the common strategies for rapid extracting EVs from biosamples, but the downstream clinical studies still remain challenges in EV enrichment with high purity and high yield. Here, such challenges could be fulfilled through the development of an arrayed Exosome Purification and Operation System (Exo-POS) for efficiently isolating EVs from complex biofluids. Human urinary EVs with mean size of approximately 170 nm were isolated successfully from donors within 30 min, and the purification of individual samples were performable in parallel. Samples purified by Exo-POS showed detectable EV-specific biomarkers and less protein impurities than that by ultrafiltration method. The results also demonstrate the great purification ability of Exo-POS to discriminate between the EV-derived proteomic and genomic expressions of cancer patients and healthy controls. The developed platform can easily be adapted to retrieve EVs from biological samples for the downstream analysis, demonstrating its potential for both rapid clinical diagnosis and biomarker discovery.
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