Issue 23, 2021

Characterization of ovarian cancer-derived extracellular vesicles by surface-enhanced Raman spectroscopy

Abstract

Ovarian cancer is the most lethal gynecological malignancy, owing to the fact that most cases are diagnosed at a late stage. To improve prognosis and reduce mortality, we must develop methods for the early diagnosis of ovarian cancer. A step towards early and non-invasive cancer diagnosis is through the utilization of extracellular vesicles (EVs), which are nanoscale, membrane-bound vesicles that contain proteins and genetic material reflective of their parent cell. Thus, EVs secreted by cancer cells can be thought of as cancer biomarkers. In this paper, we present gold nanohole arrays for the capture of ovarian cancer (OvCa)-derived EVs and their characterization by surface-enhanced Raman spectroscopy (SERS). For the first time, we have characterized EVs isolated from two established OvCa cell lines (OV-90, OVCAR3), two primary OvCa cell lines (EOC6, EOC18), and one human immortalized ovarian surface epithelial cell line (hIOSE) by SERS. We subsequently determined their main compositional differences by principal component analysis and were able to discriminate the groups by a logistic regression-based machine learning method with ∼99% accuracy, sensitivity, and specificity. The results presented here are a great step towards quick, facile, and non-invasive cancer diagnosis.

Graphical abstract: Characterization of ovarian cancer-derived extracellular vesicles by surface-enhanced Raman spectroscopy

Supplementary files

Article information

Article type
Paper
Submitted
02 Leo 2021
Accepted
19 Mph 2021
First published
21 Mph 2021

Analyst, 2021,146, 7194-7206

Characterization of ovarian cancer-derived extracellular vesicles by surface-enhanced Raman spectroscopy

N. M. Ćulum, T. T. Cooper, G. A. Lajoie, T. Dayarathna, S. H. Pasternak, J. Liu, Y. Fu, L. Postovit and F. Lagugné-Labarthet, Analyst, 2021, 146, 7194 DOI: 10.1039/D1AN01586A

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