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Integrated chemical array and SERS profiling of plasma small extracellular vesicles for breast cancer diagnosis

Xin Feng, Wei Zhang, Simon Chang-Hao Tsao, Chao Shen, Lianghai Hu*, Yuling Wang*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Small extracellular vesicles (sEVs) are nanoscale vesicles carrying biomolecules reflective of their cellular origin, making them attractive biomarkers for cancer diagnosis. In this study, we present a high-throughput strategy integrating amphiphile–dendrimer supramolecular probe (ADSP)-based sEV capture with surface-enhanced Raman scattering (SERS) for sensitive, multiplexed detection of breast cancer (BC)-related surface proteins. Plasma-derived sEVs from BC patients at different clinical stages were analyzed, focusing on CD9, EpCAM, and HER2 as key proteins linked to vesicle identity and tumor progression. Gold nanoparticle-based SERS nanotags conjugated with specific antibodies enabled precise detection. Statistical and machine learning analyses of protein profiles allowed accurate discrimination among healthy donors, ductal carcinoma in situ (Stage 0), early stage BC (Stage I–II), and metastatic-stage BC (Stage IV). This integrated platform provides a powerful tool for BC diagnosis and highlights the potential of sEV-based liquid biopsy strategies for clinical application.

Original languageEnglish
Pages (from-to)15331–15339
Number of pages9
JournalNano letters
Volume25
Issue number42
Early online date14 Oct 2025
DOIs
Publication statusPublished - 22 Oct 2025

Keywords

  • Small extracellular vesicles
  • Surface-enhanced Raman scattering
  • High-throughput detection strategy
  • Machine learning
  • Breast cancer diagnosis

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