A metabolic discrimination model for nasopharyngeal carcinoma and its potential role in the therapeutic evaluation of radiotherapy

Nasopharyngeal carcinoma (NPC) is one of the most common malignancies in Southeast Asia and radiotherapy or radiotherapy, in combination with chemotherapy is the primary treatment strategy. In this study, we adopted a metabolomic method to investigate the metabolic disorders in NPC and evaluate the effect of radiotherapy on metabolic profile alterations in NPC patients. To generate the NPC metabolic profiles, 402 serum samples were collected from 100 newly-diagnosed NPC patients and 100 healthy volunteers. Based on gas chromatography–mass spectrometry (GC–MS) metabolomics coupled with partial least squares-discriminant analysis, a NPC discrimination model was constructed with a sensitivity of 88 % (88/100) and a specificity of 92 % (92/100). Seven metabolites, including glucose, linoleic acid, stearic acid, arachidonic acid, proline, β-hydroxy butyrate and glycerol 1-hexadecanoate, were identified as contributing mostly to the discrimination of NPC serum from healthy controls. To validate if the model can be applied for therapeutic evaluation, 202 serum samples were collected from 20 patients receiving standard radiotherapy for up to a 3-year follow-up period. The metabolic footprints of 20 NPC patients treated with standard radiotherapy are visually presented. Based on the footprint trends of the sera samples in irradiation-treated NPC patients who were gradually closer to healthy controls or not, patients were divided into positive and negative groups, respectively. The coincident rate of the trends of metabolic footprints to the actual clinical prognosis trend was approximately 80 %. This study demonstrates that a GC–MS-based metabolic profiling approach as a novel strategy may be capable to delineating the potential of metabolite alterations in discrimination and therapeutic evaluation of NPC patients.