This paper introduces a new identification strategy of novel metabolic biomarkers for nasopharyngeal carcinoma (NPC). Here, we combined gas chromatography-mass spectrometry (GC-MS) metabolic profiling with three partial least squares-discriminant analysis (PLS-DA) based variable selection methods to screen the metabolic biomarkers of NPC. We found that the variable importance on projection (VIP) method exhibited better efficiency than the coefficients beta and the loadings plot for the metabolomics data set of 39 NPC patients and 40 healthy controls. In addition, we proved that the area under receiver operating characteristic curve (AUC) was more sensitive than the correct rate to evaluate the discrimination ability of the classical models. Therefore, three novel candidate biomarkers, glucose, glutamic acid and pyroglutamate were identified, with a correct rate of 97.47% and an AUC value of 97.40%. Our results suggested that the metabolic disorders of NPC were mainly reflected in the glycolysis and glutamate metabolism; in addition, metabolic levels of the related metabolic pathways may affect each other, such as the TCA cycle and lipid metabolism. We believe that the findings of these novel metabolites will be very helpful for early-diagnosis and subsequent pathogenesis research of NPC.
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