Ultra-Sensitive Automated Profiling of EpCAM Expression on Tumor-Derived Extracellular Vesicles.
EpCAM
automated microscopy
biomarker profiling
exosome
extracellular vesicles
liquid biopsy
Journal
Frontiers in genetics
ISSN: 1664-8021
Titre abrégé: Front Genet
Pays: Switzerland
ID NLM: 101560621
Informations de publication
Date de publication:
2019
2019
Historique:
received:
03
06
2019
accepted:
19
11
2019
entrez:
11
1
2020
pubmed:
11
1
2020
medline:
11
1
2020
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 31921310
doi: 10.3389/fgene.2019.01273
pmc: PMC6928048
doi:
Types de publication
Journal Article
Langues
eng
Pagination
1273Subventions
Organisme : NCI NIH HHS
ID : U01 CA214254
Pays : United States
Informations de copyright
Copyright © 2019 Amrollahi, Rodrigues, Lyon, Goel, Han and Hu.
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