Cancer diagnosis using label-free SERS-based exosome analysis

被引：39

作者：

Liu, Yajuan ^{[1
,2
,3
]}

Li, Mei ^{[4
]}

Liu, Haisha ^{[4
]}

Kang, Chao ^{[4
]}

Wang, Cheng ^{[5
]}

机构：

[1] Guangzhou Med Univ, Sch Pharmaceut Sci, Key Lab Mol Target & Clin Pharmacol, Guangzhou 511436, Peoples R China

[2] Guangzhou Med Univ, Sch Pharmaceut Sci, NMPA & State Key Lab Resp Dis, Guangzhou 511436, Peoples R China

[3] Guangzhou Med Univ, Affiliated Hosp 5, Guangzhou 511436, Peoples R China

[4] Guizhou Univ, Sch Chem & Chem Engn, Guiyang 550025, Peoples R China

[5] Trinity Coll Dublin, Smurfit Inst Genet, Dublin, Ireland

来源：

THERANOSTICS | 2024年 / 14卷 / 05期

关键词：

Cancer diagnosis; Exosome; Raman Spectroscopy; SERS; label-free SERS; INFRARED RAMAN-SPECTROSCOPY; EXTRACELLULAR VESICLES; CLASSIFICATION; IDENTIFICATION; PLATFORM; PROGRESS; DEVICE; DAMAGE;

D O I：

10.7150/thno.92621

中图分类号：

R-3 [医学研究方法]; R3 [基础医学];

学科分类号：

1001 ;

摘要：

Exosomes, carrying distinctive biomolecules reflective of their parent cell's status and origin, show promise as liquid biopsy biomarkers for cancer diagnosis. However, their clinical translation remains challenging due to their relatively low concentration in body fluids. Surface-Enhanced Raman spectroscopy (SERS) has recently gained significant attention as a label-free and sensitive technique for exosome analysis. This review explores label-free SERS for exosome detection, covering exosome isolation and characterization methods, advancements in SERS substrates, and fingerprint analysis techniques using machine learning. Furthermore, we emphasize the challenges and offer insights into the future prospects of SERS-based exosome analysis to enhance cancer diagnosis.

引用

页码：1966 / 1981

页数：16

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