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Park, Jaena,Hwang, Miyeon,Choi, ByeongHyeon,Jeong, Hyesun,Jung, Jik-han,Kim, Hyun Koo,Hong, Sunghoi,Park, Ji-ho,Choi, Yeonho American Chemical Society 2017 ANALYTICAL CHEMISTRY - Vol.89 No.12
<P>Owing to the role of exosome as a cargo for intercellular communication, especially in cancer metastasis, the evidence has been consistently accumulated that exosomes can be used as a noninvasive indicator of cancer. Consequently, several studies applying exosome have been proposed for cancer diagnostic methods such as ELISA assay. However, it has been still challenging to get reliable results due to the requirement of a labeling process and high concentration of exosome. Here, we demonstrate a label-free and highly sensitive classification method of exosome by combining-enhanced (SERS) and statistical surface Raman, scattering pattern analysis. Unlike the conventional method to read different peak positions and amplitudes of a spectrum, whole SERS spectra of exosomes were analyzed by principal component analysis (PCA). By employing this pattern analysis, lung cancer cell derived exosomes were clearly distinguished from normal cell derived exosomes by 95.3% sensitivity and 97.3% specificity. Moreover, by analyzing the PCA result, we could suggest that this difference was induced by 11 different points in SERS signals from lung cancer cell derived exosomes. This result paved the way for new real-time diagnosis and classification of lung cancer by using exosome as a cancer marker.</P>
Lim, Jae-young,Nam, Jung-soo,Shin, Hyunku,Park, Jaena,Song, Hye-in,Kang, Minsung,Lim, Kwang-il,Choi, Yeonho American Chemical Society 2019 ANALYTICAL CHEMISTRY - Vol.91 No.9
<P>Rapid diagnosis and quarantine of influenza virus mutant-infected people is critical to contain the fatal viral infection spread because effective antiviral drugs are normally not available. Conventional methods, however, cannot be used for the diagnosis because these methods need predefined labels, likely also unavailable for just emerging viruses. Here, we propose label-free identification of cells infected with different influenza viruses based on surface-enhanced Raman spectroscopy (SERS) and principal component analysis (PCA). Viral envelope proteins that are displayed on the surface of cells after infection of influenza viruses were targeted for this identification. Cells that expressed the envelope proteins of A/WSN/33 H1N1 or A/California/04/2009 H1N1 influenza viruses produced distinct SERS signals. Cells that displayed combinations of the envelope proteins from these two viral variants, an indication of emergence of a new virus, also generated characteristic SERS patterns. However, the cell’s own surface proteins often hindered the identification of virally infected cells by producing SERS peaks similar to viral ones. PCA of the obtained SERS patterns could effectively capture the virus-specific signal components from the jumbled SERS peaks. Our study demonstrates a potential of combination of SERS and PCA to identify newly emerging influenza viruses through sensing the cells infected with the viruses.</P> [FIG OMISSION]</BR>