Label-free characterization of exosome via surface enhanced Raman spectroscopy for the early detection of pancreatic cancer

Nanomedicine. 2019 Feb:16:88-96. doi: 10.1016/j.nano.2018.11.008. Epub 2018 Dec 11.

Abstract

Pancreatic cancer is a highly lethal malignancy. Lack of early diagnostic markers makes timely detection of pancreatic cancer a highly challenging endeavor. Exosomes have emerged as information-rich cancer specific biomarkers. However, characterization of tumor-specific exosomes has been challenging. This study investigated the proof of principle that exosomes could be used for the detection of pancreatic cancer. Label-free analysis of exosomes purified from normal and pancreatic cancer cell lines was performed using surface enhanced Raman Spectroscopy (SERS) and principal component differential function analysis (PC-DFA), to identify tumor-specific spectral signatures. This method differentiated exosomes originating from pancreatic cancer or normal pancreatic epithelial cell lines with 90% accuracy. The cell line trained PC-DFA algorithm was next applied to SERS spectra of serum-purified exosomes. This method exhibited up to 87% and 90% predictive accuracy for HC and EPC individual samples, respectively. Overall, our study identified utility of SERS spectral signature for deciphering exosomal surface signature.

Keywords: Exosome; Label-free; Liquid biopsy; Pancreatic cancer; Surface enhanced Raman spectroscopy.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms
  • Biomarkers, Tumor / analysis
  • Early Detection of Cancer / methods*
  • Exosomes / metabolism*
  • Humans
  • Microscopy, Electron, Transmission
  • Pancreatic Neoplasms / diagnosis*
  • Pancreatic Neoplasms / metabolism*
  • Principal Component Analysis
  • Spectrum Analysis, Raman / methods*

Substances

  • Biomarkers, Tumor