Absolute Quantification of Serum Exosomes in Patients with an SERS-Lateral Flow Strip Biosensor for Noninvasive Clinical Cancer Diagnosis

ACS Appl Mater Interfaces. 2023 Aug 9;15(31):37130-37142. doi: 10.1021/acsami.3c05039. Epub 2023 Jul 31.

Abstract

Exosomes (exos) widely existing in body fluids show great potential for noninvasive cancer diagnosis. Quantitative analysis of exos is traditionally performed by targeting specific exosomal surface proteins, but it is often imprecise due to the common expression of exosomal proteins and subtle expression differences between different cancer subtypes. Herein, we report quantitative surface-enhanced Raman spectroscopy (SERS) of serum exos through a combination of a paper-based lateral flow strip (LFS) biosensor with multivariate spectral unmixing analysis rather than simply quantifying exosomal proteins. Our SERS-LFS biosensor enables absolute quantification of two different serum exos with a limit of detection down to ∼106 particles/mL for both exos. We further exemplify the application of this strategy in quantitative dual-plex detection of serum exos from breast cancer patients. We find that human epidermal growth factor receptor 2+ (HER2+) and luminal A breast cancer patients undergoing no surgery are enriched in serum exos derived from SKBR-3 cells and MCF-7 cells (denoted as SKBR and MCF exos), respectively. The surgical treatment of these breast cancer patients accompanies an obvious decrease of either SKBR or MCF exos in the serum. These results suggest the great potential of the combination of the SERS-LFS biosensor and multivariate spectral unmixing for breast cancer subtyping and therapeutic surveillance with the powerful quantitative capability of exos in clinical samples.

Keywords: liquid biopsy; multiplex detection; multivariate spectral unmixing; serum exosomes; surface-enhanced Raman spectroscopy.

MeSH terms

  • Biosensing Techniques* / methods
  • Breast Neoplasms* / diagnosis
  • Breast Neoplasms* / metabolism
  • Exosomes* / chemistry
  • Female
  • Humans
  • Serum
  • Spectrum Analysis, Raman / methods