| Nasopharyngeal carcinoma (NPC) is a malignancy with an unusual geographical and ethnic distribution across the world. It is prevalent in southern China and Southeast Asia, particularly in the Cantonese population, where its incidence has remained high for decades. And it remains a serious healthcare problem in these regions nowadays. Recent studies have demonstrated that the etiology of NPC is complex, involving multiple factors including genetic susceptibility, infection with the Epstein-Barr virus (EBV) and exposure to chemical carcinogens. Although numerous efforts have been made to reveal the molecular mechanism of NPC carcinogenesis and development, it remains poorly understood. Finding effective biomarkers for NPC will benefit its diagnosis, treatment effect, prognosis judgement and mechanism study.High-throughput technologies such as microarrays and proteomics have the potential to find important molecules previously unidentified in NPC. Analysis for gene expression profiles of NPC have been reported using a cDNA array, and revealed that certain genes with aberrant expressions possibly contributed to pathogenesis of NPC. Comparative proteomics has introduced a new approach to cancer research, analysis of NPC cell/tissue has identified differential expression proteins associated with the development and progression of this disease. Metabonomics, defined as the "the quantitative measurement of the dynamic multiparametric response of a living system to pathophysiological stimuli or genetic modification", is a new discipline arise following genomics, transcriptomics and proteomics. Differences at metabolites level can be used to elucidate changes that occur downstream from genomic and proteomic alterations associated with disease-related biochemical reactions. Because these processes precede changes in cell morphology that predict disease, metabolomics approaches may permit early diagnosis or real-time monitoring of the effects of a disease or therapeutic intervention, and providing new opportunities to uncover biomarkers and therapeutic targets for NPC as well as reveal the molecular mechanism underlying this disease.Metabolomics has been successfully applied to many fields such as toxicological screening, nutrition intervention, plant genotype discrimination, disease diagnosis, ect. However, extracting useful information from complex data system of all metabolites, is one of the difficult points existing in metabolomics research. To solve this problem, combination of hyphenated chromatographic instruments and effective chemometric approaches were adopted.In this study, we adopted Gas Chromatography-Mass Spectrometry (GC-MS) technology to analyze the metabolites profiling of sera from 102 cases of NPC at first diagnosis and 107 cases of normal healthy people; acquired the spectrum data of each case, and established the metabolites profiling of NPC and healthy control separately. The spectrum data (totoal ion current, TIC) were input and searched in the NIST107 database, 47 endogenous compounds were identified. And then, Classified Characteristic Variable Method was adopted to find potential biomarkers, results in 4 biomarkers, they are lactic acid, L-Lysine, glycine and glucuronolactone. At the same time, model recognition methods (PCA, PLS-DA and ULDA) were adopted to build recognition models for discriminating between NPC and healthy controls, 10-fold cross validation analysis evaluated the prediction ability of ULDA model. Results turn out to be perfect. Double blind experiment validated the reliability and stability of recognition model ULDA.These results provide a new way for NPC diagnosis and a new idea for finding biomarkers, NPC-associated metabolomic pathways.
|
PDF Full Text Request