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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：
Abstract 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-q-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.
 
一、研究背景：
甲状腺肿瘤的发病率逐年升高，通过早期的诊断和治疗可有效降低其复发率和致死率。目前甲状腺肿瘤主要通过超声和超声介导的穿刺活体切片（FNAB）进行诊断，但其特异性等仍有待提高。肿瘤生物标志物可与FNAB方法结合使用，以更准确地进行恶性肿瘤诊断。乳突状甲状腺肿瘤（PTC）是常见的恶性甲状腺肿瘤的亚型之一。如整合目前代谢组学研究中的非靶向（GC-TOF-MS）和靶向（UHPLC--MS）两种研究平台可更加高效和可靠地进行潜在生物标志物的筛选。

二、方法流程：
 

三、研究结果与讨论：
1 不同组织代谢指纹图谱：
1）检测到686个内源性代谢物峰
2）肿瘤组织和正常组织代谢物出现明显区别
3）通过OPLS-DA模型筛选得到45个标志性差异物
4）半乳糖代谢途径在肿瘤组织中发生显著改变
 
 
图1非靶标实验结果
 
2 通过靶标代谢组学对潜在生物标志物的验证
1）通过UHPLC-Q-MS对前期筛到的潜在标志物通过标准曲线进行精确定量，其中11个可测定；
2）精确定量物质中，3个在前列腺肿瘤（PTC）中浓度高，8个在PTC中浓度低；
3）半乳糖代谢途径上的代谢物经过T检验表现出统计学显著性差异
4）结合靶标、非靶标实验确定的生物标志物：肌醇半乳糖苷、蜜二糖、褪黑激素
 图2 靶标实验获得标志性物质获得的ROC曲线3 PTC中代谢途径的特征1） 乳糖代谢途径减弱与PTC癌变过程可能有关2） PTC中褪黑激素含量降低，该物质可能具有抑制肿瘤作用3） 不饱和脂肪酸合成途径减弱可能与PTC发病相关

图3结合非靶标和靶标代谢组学信息获得的PTC可能相关途径四、亮点和展望l 非靶标代谢组学实验之后用靶标实验对标志性差异物进行精确定量，为建立生物标志物提供了更加坚实的基础；

 通过靶标实验更精确地定位癌细胞中发生变化的代谢通路，为后续研究提供更可靠的线索
l 展望：针对精确定量得到的生物标志物可通过大样本进行验证和推进
l 展望：针对乳糖代谢途径进行多角度研究，研究其细致的调节机制