Dataset Information

Cancer diagnosis using label-free SERS-based exosome analysis.

ABSTRACT: 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.

SUBMITTER: Liu Y

PROVIDER: S-EPMC10945334 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature

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Cancer diagnosis using label-free SERS-based exosome analysis.

Liu Yajuan Y Li Mei M Liu Haisha H Kang Chao C Wang Cheng C

Theranostics 20240224 5

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 is ...[more]

PMID: 38505618

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Dataset Information

Cancer diagnosis using label-free SERS-based exosome analysis.

Publications

Cancer diagnosis using label-free SERS-based exosome analysis.

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