Ultra-Sensitive Automated Profiling of EpCAM Expression on Tumor-Derived Extracellular Vesicles

Pouya Amrollahi, Meryl Rodrigues, Christopher J. Lyon, Ajay Goel, Haiyong Han, Tony Y. Hu

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

Extracellular vesicles (EVs) are abundant in most biological fluids and considered promising biomarker candidates, but the development of EV biomarker assays is hindered, in part, by their requirement for prior EV purification and the lack of standardized and reproducible EV isolation methods. We now describe a far-field nanoplasmon-enhanced scattering (FF-nPES) assay for the isolation-free characterization of EVs present in small volumes of serum (< 5 µl). In this approach, EVs are captured with a cancer-selective antibody, hybridized with gold nanorods conjugated with an antibody to the EV surface protein CD9, and quantified by their ability to scatter light when analyzed using a fully automated dark-field microscope system. Our results indicate that FF-nPES performs similarly to EV ELISA, when analyzing EV surface expression of epithelial cell adhesion molecule (EpCAM), which has clinical significant as a cancer biomarker. Proof-of-concept FF-nPES data indicate that it can directly analyze EV EpCAM expression from serum samples to distinguish early stage pancreatic ductal adenocarcinoma patients from healthy subjects, detect the development of early stage tumors in a mouse model of spontaneous pancreatic cancer, and monitor tumor growth in patient derived xenograft mouse models of pancreatic cancer. FF-nPES thus appears to exhibit strong potential for the direct analysis of EV membrane biomarkers for disease diagnosis and treatment monitoring.

Original languageEnglish (US)
Article number1273
JournalFrontiers in Genetics
Volume10
DOIs
StatePublished - Dec 17 2019

Keywords

  • EpCAM
  • automated microscopy
  • biomarker profiling
  • exosome
  • extracellular vesicles
  • liquid biopsy

ASJC Scopus subject areas

  • Molecular Medicine
  • Genetics
  • Genetics(clinical)

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