Back to Search
Start Over
Label-free characterization of exosome via surface enhanced Raman spectroscopy for the early detection of pancreatic cancer
- Source :
- Nanomedicine: Nanotechnology, Biology and Medicine. 16:88-96
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
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.
- Subjects :
- Biomedical Engineering
Pharmaceutical Science
Medicine (miscellaneous)
Bioengineering
02 engineering and technology
Exosomes
Spectrum Analysis, Raman
Exosome
Article
03 medical and health sciences
Microscopy, Electron, Transmission
Pancreatic cancer
Biomarkers, Tumor
medicine
Humans
General Materials Science
Liquid biopsy
Early Detection of Cancer
030304 developmental biology
Label free
Principal Component Analysis
0303 health sciences
Chemistry
Cancer
Surface-enhanced Raman spectroscopy
021001 nanoscience & nanotechnology
medicine.disease
Microvesicles
Pancreatic Neoplasms
Cell culture
Cancer research
Molecular Medicine
0210 nano-technology
Algorithms
Subjects
Details
- ISSN :
- 15499634
- Volume :
- 16
- Database :
- OpenAIRE
- Journal :
- Nanomedicine: Nanotechnology, Biology and Medicine
- Accession number :
- edsair.doi.dedup.....5dd6ff844532ea2c0938090ef291e321