Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies

Hyunku Shin, Dongkwon Seo, Yeonho Choi

Research output: Contribution to journalReview articlepeer-review

4 Citations (Scopus)

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.

Original languageEnglish
JournalMolecules (Basel, Switzerland)
Volume25
Issue number21
DOIs
Publication statusPublished - 2020 Nov 9

Keywords

  • extracellular vesicles
  • nanostructures
  • signal analysis
  • surface-enhanced Raman spectroscopy

ASJC Scopus subject areas

  • Analytical Chemistry
  • Chemistry (miscellaneous)
  • Molecular Medicine
  • Pharmaceutical Science
  • Drug Discovery
  • Physical and Theoretical Chemistry
  • Organic Chemistry

Fingerprint

Dive into the research topics of 'Extracellular Vesicle Identification Using Label-Free Surface-Enhanced Raman Spectroscopy: Detection and Signal Analysis Strategies'. Together they form a unique fingerprint.

Cite this