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Cited 3 time in webofscience Cited 4 time in scopus
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Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies

Authors
Shin, HyunkuSeo, DongkwonChoi, Yeonho
Issue Date
11월-2020
Publisher
MDPI
Keywords
extracellular vesicles; surface-enhanced Raman spectroscopy; nanostructures; signal analysis
Citation
MOLECULES, v.25, no.21
Indexed
SCIE
SCOPUS
Journal Title
MOLECULES
Volume
25
Number
21
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/51940
DOI
10.3390/molecules25215209
ISSN
1420-3049
Abstract
Extracellular vesicles (EVs) have been widely investigated as promising biomarkers for the liquid biopsy of diseases, owing to their countless roles in biological systems. Furthermore, with the notable progress of exosome research, the use of label-free surface-enhanced Raman spectroscopy (SERS) to identify and distinguish disease-related EVs has emerged. Even in the absence of specific markers for disease-related EVs, label-free SERS enables the identification of unique patterns of disease-related EVs through their molecular fingerprints. In this review, we describe label-free SERS approaches for disease-related EV pattern identification in terms of substrate design and signal analysis strategies. We first describe the general characteristics of EVs and their SERS signals. We then present recent works on applied plasmonic nanostructures to sensitively detect EVs and notable methods to interpret complex spectral data. This review also discusses current challenges and future prospects of label-free SERS-based disease-related EV pattern identification.
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