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整合代谢组学作为诊断甲状腺恶性肿瘤的潜在方法。

Integrative metabonomics as potential method for diagnosis of thyroid malignancy.

作者信息

Tian Yuan, Nie Xiu, Xu Shan, Li Yan, Huang Tao, Tang Huiru, Wang Yulan

机构信息

CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Centre for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, Wuhan, 430071, P.R. China.

Department of Pathology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, P.R. China.

出版信息

Sci Rep. 2015 Oct 21;5:14869. doi: 10.1038/srep14869.

Abstract

Thyroid nodules can be classified into benign and malignant tumors. However, distinguishing between these two types of tumors can be challenging in clinics. Since malignant nodules require surgical intervention whereas asymptomatic benign tumors do not, there is an urgent need for new techniques that enable accurate diagnosis of malignant thyroid nodules. Here, we used (1)H NMR spectroscopy coupled with pattern recognition techniques to analyze the metabonomes of thyroid tissues and their extracts from thyroid lesion patients (n = 53) and their adjacent healthy thyroid tissues (n = 46). We also measured fatty acid compositions using GC-FID/MS techniques as complementary information. We demonstrate that thyroid lesion tissues can be clearly distinguishable from healthy tissues, and malignant tumors can also be distinguished from the benign tumors based on the metabolic profiles, both with high sensitivity and specificity. In addition, we show that thyroid lesions are accompanied with disturbances of multiple metabolic pathways, including alterations in energy metabolism (glycolysis, lipid and TCA cycle), promotions in protein turnover, nucleotide biosynthesis as well as phosphatidylcholine biosynthesis. These findings provide essential information on the metabolic features of thyroid lesions and demonstrate that metabonomics technology can be potentially useful in the rapid and accurate preoperative diagnosis of malignant thyroid nodules.

摘要

甲状腺结节可分为良性和恶性肿瘤。然而,在临床上区分这两种类型的肿瘤可能具有挑战性。由于恶性结节需要手术干预,而无症状的良性肿瘤则不需要,因此迫切需要能够准确诊断恶性甲状腺结节的新技术。在此,我们使用氢核磁共振波谱结合模式识别技术来分析甲状腺病变患者(n = 53)及其相邻健康甲状腺组织(n = 46)的甲状腺组织及其提取物的代谢组。我们还使用气相色谱 - 火焰离子化检测/质谱技术测量脂肪酸组成作为补充信息。我们证明,基于代谢谱,甲状腺病变组织可以与健康组织明显区分,恶性肿瘤也可以与良性肿瘤区分,两者都具有高灵敏度和特异性。此外,我们表明甲状腺病变伴随着多种代谢途径的紊乱,包括能量代谢(糖酵解、脂质和三羧酸循环)的改变、蛋白质周转的促进、核苷酸生物合成以及磷脂酰胆碱生物合成。这些发现提供了关于甲状腺病变代谢特征的重要信息,并证明代谢组学技术在恶性甲状腺结节的快速准确术前诊断中可能具有潜在用途。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/371c/4613561/56ef47547296/srep14869-f1.jpg

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