Lu Jinghui, Hu Sanyuan, Miccoli Paolo, Zeng Qingdong, Liu Shaozhuang, Ran Lin, Hu Chunxiao
Department of General Surgery, Qilu Hospital of Shandong University, Jinan 250012, P.R. China.
Department of General Surgery, University of Pisa, Pisa 56126, Italy.
Oncotarget. 2016 Dec 6;7(49):81768-81777. doi: 10.18632/oncotarget.13178.
Papillary thyroid microcarcinoma (PTMC) is a subtype of papillary thyroid carcinoma (PTC). Because its diameter is less than 10 mm, diagnosing it accurately is difficult with traditional methods such as image examinations and FNA (Fine Needle Aspiration). Investigating the metabolic changes induced by PTMC may enhance the understanding of its pathogenesis and provide important information for a new diagnosis method and treatment plan. In this study, high resolution magic angle spin (HRMAS) spectroscopy and 1H-nuclear magnetic resonance (1H-NMR) spectroscopy were used to screen metabolic changes in thyroid tissues and plasma from PTMC patients respectively. The results revealed reduced levels of fatty acids and elevated levels of several amino acids (phenylalanine, tyrosine, lactate, serine, cystine, lysine, glutamine/glutamate, taurine, leucine, alanine, isoleucine and valine) in thyroid tissues, as well as reduced levels of amino acids such as valine, tyrosine, proline, lysine, leucine and elevated levels of glucose, mannose, pyruvate and 3-hydroxybutyrate in plasma, are involved in the metabolic alterations in PTMC. In addition, a receiver operating characteristic (ROC) curve model for PTMC prediction was able to classify cases with good sensitivity and specificity using 9 significant changed metabolites in plasma. This work illustrates that the NMR-based metabolomics approach is capable of providing more sensitive diagnostic results and more systematic therapeutic information for PTMC.
甲状腺微小乳头状癌（PTMC）是甲状腺乳头状癌（PTC）的一种亚型。由于其直径小于10毫米，使用传统方法如影像检查和细针穿刺抽吸活检（FNA）很难准确诊断。研究PTMC诱导的代谢变化可能会增进对其发病机制的理解，并为新的诊断方法和治疗方案提供重要信息。在本研究中，分别使用高分辨率魔角旋转（HRMAS）光谱和1H核磁共振（1H-NMR）光谱来筛选PTMC患者甲状腺组织和血浆中的代谢变化。结果显示，甲状腺组织中脂肪酸水平降低，几种氨基酸（苯丙氨酸、酪氨酸、乳酸、丝氨酸、胱氨酸、赖氨酸、谷氨酰胺/谷氨酸、牛磺酸、亮氨酸、丙氨酸、异亮氨酸和缬氨酸）水平升高，以及血浆中缬氨酸、酪氨酸、脯氨酸、赖氨酸、亮氨酸等氨基酸水平降低，葡萄糖、甘露糖、丙酮酸和3-羟基丁酸水平升高，这些都参与了PTMC的代谢改变。此外，基于血浆中9种显著变化的代谢物建立的PTMC预测的受试者工作特征（ROC）曲线模型能够以良好的敏感性和特异性对病例进行分类。这项工作表明，基于核磁共振的代谢组学方法能够为PTMC提供更敏感的诊断结果和更系统的治疗信息。
