1H NMR-based metabonomic and pattern recognition analysis for detection of oral squamous cell carcinoma

Metabonomic analysis has been increasingly used to monitor metabolic abnormalities in cells and their microenvironment in order to detect the cancer markers recently. We evaluated the feasibility of applying 1H nuclear magnetic resonance ( 1H NMR) based metabonomic method in the early detection of the differences in the plasma from 3 groups, which were patients with oral squamous cell carcinoma (OSCC), patients with oral leukoplakia (OLK), and the healthy control group. 1H NMR spectra were obtained from human plasma samples prior to spectral analysis. The obtained data were processed by both the unsupervised principal component analysis (PCA) and the supervised partial least squares discriminant analysis (PLS-DA) to find out the differences among the three groups. PLS-DA analysis has revealed a good model to detect the NMR data that can differentiate the OSCC patients from the OLK patients and the controls using a test set. The results indicated that the 1H NMR-based metabonomic approach is a feasible and efficient method for differentiating the OSCC patient's plasma from the healthy controls. As a potential novel strategy and a more convenient technique, it deserves a further evaluation for an early detection of oral cancer.