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Free keywords:
diagnostics, exosome-like vesicles, gold nanoparticles, multivariate statistical analysis, surface enhanced Raman spectroscopy
Abstract:
Exosome-like vesicles (ELVs) are a novel class of biomarkers that are receiving a lot of attention for the detection of cancer at an early stage. In this study the feasibility of using a surface enhanced Raman spectroscopy (SERS) based method to distinguish between ELVs derived from different cellular origins is evaluated. A gold nanoparticle based shell is deposited on the surface of ELVs derived from cancerous and healthy cells, which enhances the Raman signal while maintaining a colloidal suspension of individual vesicles. This nanocoating allows the recording of SERS spectra from single vesicles. By using partial least squares discriminant analysis on the obtained spectra, vesicles from different origin can be distinguished, even when present in the same mixture. This proof-of-concept study paves the way for noninvasive (cancer) diagnostic tools based on exosomal SERS fingerprinting in combination with multivariate statistical analysis.
