Single cell detection using intracellularly-grown-Au-nanoparticle based surface-enhanced Raman scattering spectroscopy for nasopharyngeal cell line classification

Abstract

The aim of this study was to evaluate the feasibility of applying intracellularly-grown-Au-nanoparticle (IGAuNP)-based surface-enhanced Raman scattering (SERS) technology to classify two types of nasopharyngeal cancer (NPC) cell lines (CNE2 and CNE1). The IGAuNP technology provides excellent delivery efficiency of Au NPs to the cytoplasm and nucleus, thus leading to an extraordinary enhancement of the Raman signals of cells. Compared with normal Raman scattering (NRS) spectra of cells, IGAuNP-based SERS spectra not only have a high signal-to-noise ratio, but also can detect more characteristic Raman peaks, which can be used to explore more differences when comparing the biochemical components of different nasopharyngeal carcinoma cell lines. Based on the linear discriminant analysis (LDA) and support vector machine (SVM) analysis of SERS spectral data, an exciting result with a diagnostic sensitivity of 100%, specificity of 100%, and accuracy of 100%, could be achieved to differentiate CNE2 and CNE1 cells, which is better than the result obtained by NRS spectroscopy. This exploratory study indicated that the SERS technology based on IGAuNPs in conjunction with multivariate statistical analysis methods has great potential in the identification of nasopharyngeal carcinoma cell lines.