Papillary thyroid carcinoma (PTC) is the most common pathological type of thyroid cancer. Our study was to construct a tissue-targeted metabolomics analysis method based on untargeted and targeted metabolic multi-platforms to identify a comprehensive PTC metabolic network in clinical samples. We applied untargeted gas chromatography-time of-flight mass spectrometry (GC-TOF-MS) for preliminary screening of potential biomarkers. With diagnostic models constructed using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal partial least squares discriminant analysis (OPLS-DA), 45 differentially abundant metabolites with a variable importance in the projection (VIP) value greater than 1 and a P value less than 0.05 were identified, and we show that our approach was able to discriminate PTC tissues from healthy tissues. We then performed validation experiments based on targeted GCTOF-MS combined with ultra-high-performance liquid chromatography-triple-quadrupole mass spectrometry (UHPLC-QqQ-MS) through constructing linear standard curves of analytes. Ultimately, galactinol, melibiose, and melatonin were validated as significantly altered metabolites (p 0.05). These three metabolites were defined as a combinatorial biomarker to assist needle biopsy for PTC diagnosis as demonstrated by receiver operating characteristic (ROC) curve analysis, which revealed an area under the ROC curve (AUC) value of 0.96. Based on the metabolite enrichment analysis results, the galactose metabolism pathway was regarded as an important factor influencing PTC development by affecting energy metabolism. Alpha-galactosidase (GLA) was considered to be a potential target for PTC therapy.
乳头状甲状腺肿瘤诊断和治疗的潜在生物标志物研究对象:分析检测平台:GC-TOF/MS和UHPLC-QqQ-MS(BIOTREE)期刊:Tumor Biology影响因子:2.926发表时间:2016摘要:Papillary thyroid carcinoma (PTC) is the most common pathological type of thyroid cancer. Our study was to construct a tissue-ta