Issue 10, 2023

Rapid exosome isolation and in situ multiplexed detection of exosomal surface proteins and microRNAs on microfluidic platform

Abstract

Exosomes are considered as promising biomarkers for early cancer diagnosis and prognosis. However, the majority of the research studies focused on a single type of exosomal biomarkers, which cannot comprehensively reflect the state of cancer for accurate diagnosis. To address this problem, we presented a ship-shaped microfluidic device containing a microcolumn array for simultaneous in situ detection of exosomal surface proteins and miRNAs. Exosomes were first captured in the microchannels modified with CD63 protein aptamer. Exosomal surface proteins and miRNAs were simultaneously detected in four parallel channels to avoid the interference of fluorescent signals using specific aptamers labeled by Cy5 and catalytic hairpin assembly (CHA) based signal amplification strategy. The limit of detection for multiplexed markers in exosomes was 83 exosomes per μL, which is comparable to previously reported methods. Through quantitative analysis of two disease-specific surface proteins and miRNAs derived from different cancer cells and clinical serum samples, different cancer subtypes as well as cancer patients and healthy people could be significantly distinguished. These results suggest that this simple, highly sensitive, and more accurate analytical strategy by simultaneous in situ profiling of different types of exosomal biomarkers has potential applications in cancer diagnosis and stage monitoring.

Graphical abstract: Rapid exosome isolation and in situ multiplexed detection of exosomal surface proteins and microRNAs on microfluidic platform

Supplementary files

Article information

Article type
Paper
Submitted
03 Mar 2023
Accepted
16 Apr 2023
First published
19 Apr 2023

Analyst, 2023,148, 2387-2394

Rapid exosome isolation and in situ multiplexed detection of exosomal surface proteins and microRNAs on microfluidic platform

Y. Chen, D. Gao, Q. Zhu, B. Chu, J. Peng, J. Wang, L. Liu and Y. Jiang, Analyst, 2023, 148, 2387 DOI: 10.1039/D3AN00335C

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