Issue 7, 2025

Recent advances in SERS assays for detection of multiple extracellular vesicles biomarkers for cancer diagnosis

Abstract

As the prevalence of cancer is escalating, there is an increased demand for early and sensitive diagnostic tools. A major challenge in early detection is the lack of specific biomarkers, and a readily accessible, sensitive and rapid detection method. To meet these challenges, cancer-derived small extracellular vesicles (sEVs) have been discovered as a new promising cancer biomarker due to the high abundance of sEVs in body fluids and their extensive cargo of biomarkers. Additionally, surface-enhanced Raman scattering (SERS) presents a sensitive, multiplexed, and rapid method that has gained attraction with recent studies showing promising results from patient samples for the multiplex detection of cancer sEVs. Various label-based SERS multiplex assays have been developed in the field of SERS including bead assays, lateral flow immunoassays, microfluidic devices, and artificial intelligence (AI)-based label-free SERS chips, targeting multiple surface proteins to ensure comprehensive multiplex diagnostics. These assays hold promise for enabling early detection, quantification, and subtyping of cancer-derived sEVs for cancer diagnostic applications. This review aims to provide a summary of the recent advances in the field of SERS multiplex assays for detection, quantification, and subtyping of sEVs to facilitate cancer diagnosis. This review further provides unique insights into the use of sEVs as a biomarker and aims to address the issues surrounding their translation from laboratories to clinics.

Graphical abstract: Recent advances in SERS assays for detection of multiple extracellular vesicles biomarkers for cancer diagnosis

Article information

Article type
Review Article
Submitted
01 Oct 2024
Accepted
05 Dec 2024
First published
07 Dec 2024

Nanoscale, 2025,17, 3635-3655

Recent advances in SERS assays for detection of multiple extracellular vesicles biomarkers for cancer diagnosis

C. Duffield, L. M. Rey Gomez, S. C. Tsao and Y. Wang, Nanoscale, 2025, 17, 3635 DOI: 10.1039/D4NR04014G

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