Raman spectral discrimination in human liquid biopsies of oesophageal transformation to adenocarcinoma

The aim of this study was to determine whether Raman spectroscopy combined with chemometric analysis can be applied to interrogate biofluids (plasma, serum, saliva and urine) towards detecting oesophageal stages through to oesophageal adenocarcinoma (normal/squamous epithelium, inflammatory, Barrett's, low-grade dysplasia [LGD], high-grade dysplasia [HGD], and oesophageal adenocarcinoma [OAC]). The chemometric analysis of the spectral data was performed using principal component analysis (PCA), successive projections algorithm (SPA) or genetic algorithm (GA) followed by quadratic discriminant analysis (QDA). The GA-QDA model using a few selected wavenumbers for saliva and urine samples achieved 100% classification for all classes. For plasma and serum, the GA-QDA model achieved excellent accuracy in all oesophageal stages (>90%). The main GA-QDA features responsible for sample discrimination were: 1012 cm (C-O stretching of ribose), 1336 cm (Amide III and CH wagging vibrations from glycine backbone), 1450 cm (methylene deformation), and 1660 cm (Amide I). The results of this study are promising and support the concept that Raman on biofluids may become a useful and objective diagnostic tool to identify oesophageal disease stages from squamous epithelium to OAC. This article is protected by copyright. All rights reserved. [Abstract copyright: This article is protected by copyright. All rights reserved.