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Automated disc device for multiplexed extracellular vesicle isolation and labelling from liquid biopsies in cancer diagnostics

  • Hyun Kyung Woo
  • , Changhyun Kim
  • , Yoonjeong Choi
  • , Young Kwan Cho
  • , Luu Ngoc Do
  • , Hyunho Kim
  • , Dae Han Jung
  • , Matt Allen
  • , Jueun Jeon
  • , Seok Chung
  • , Soo Yeun Park
  • , Ilwoo Park
  • , Cesar M. Castro
  • , Jun Seok Park
  • , Hakho Lee
  • Massachusetts General Hospital
  • Harvard University
  • Chonnam National University
  • Korea University
  • Korea Institute of Science and Technology
  • Kyungpook National University

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Circulating extracellular vesicles can be used for tumour diagnostics. However, current isolation methods are time consuming, require manual handling and are prone to contamination. Here we report on SpinEx (separation-processing integration for extracellular vesicles), a compact disc device for automatic isolation and multiplex immunolabelling of whole-blood samples. SpinEx integrates on-disc chromatography, centripetal liquid transfer and bead-based vesicle capture with antibody labelling. The system processes 150 µl of whole blood, enriching and labelling vesicles for 16 protein targets in under 75 minutes. Detection is performed by measuring dual fluorescence signals from labelled extracellular vesicles captured on microbeads. In a pilot clinical study, SpinEx was used to process 221 plasma samples for multiplex profiling of 30 vesicle-associated proteins. Using fluorescence flow cytometry to analyse cancer-specific biomarker expression, we found that vesicles processed by SpinEx distinguished cancer from non-cancer samples with 90% accuracy and 97% specificity, and classified 5 tumour types with 96% accuracy. SpinEx enables automated and multiplex processing of extracellular vesicles from blood, which may support the development of clinically viable assays for cancer detection and classification.

Original languageEnglish
JournalNature Biomedical Engineering
DOIs
StateAccepted/In press - 2026

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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