Cancer protein biomarker identification and quantification using nanoforest substrate and hand-held Raman spectrometer
- Authors
- Kim, Hyun Soo; Lee, Taeha; Yun, Jongsu; Lee, Gyudo; Hong, Yoochan
- Issue Date
- 1월-2021
- Publisher
- ELSEVIER
- Keywords
- Nanoforest; Surface enhanced Raman scattering; Cancer protein biomarker; Hand-held Raman spectrometer; Cancer cell identification; Cancer diagnostics
- Citation
- MICROCHEMICAL JOURNAL, v.160
- Indexed
- SCIE
SCOPUS
- Journal Title
- MICROCHEMICAL JOURNAL
- Volume
- 160
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/50193
- DOI
- 10.1016/j.microc.2020.105632
- ISSN
- 0026-265X
- Abstract
- Cancer biomarkers, an indication of cancer cells in the body, can play an important role in diagnosis, prognosis, and the prediction of treatment efficacy as well as recurrence. Here, we developed a simple Raman spectroscopic method that utilized a silver nanoforest (SNF) substrate and a hand-held Raman spectrometer for identifying cancer protein biomarkers with very high sensitivity. First, various concentrations of ethanol solutions were analyzed using the hand-held Raman spectrometer to confirm its performance. Next, the functionality of the SNF substrate, in other words, the effect of the surface enhanced Raman scattering was characterized by measuring varying, known concentrations of rhodamine 6G. The novel structure of the SNF substrate can provide the enhancement factor of 1.13 x 10(7). Following the characterization, the Raman spectra of cancer biomarkers, epithelial cell adhesion molecule (EpCAM) and carcinoembryonic antigen (CEA), were examined using the handheld Raman spectrometer with the SNF substrate. As low as 0.2 picomoles of the protein were successfully detected with very tiny amount of sample solutions (similar to 2 mu l) containing cancer biomarkers. The developed technique allows for the simple, convenient measurement of cancer protein biomarkers using the SNF substrate and hand-held Raman spectrometer. We believe these findings will motivate the creation of Raman libraries for cancer biomarkers.
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Collections - Graduate School > Department of Biotechnology and Bioinformatics > 1. Journal Articles
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