Oncotarget

Research Papers:

Non-invasive diagnosis of papillary thyroid microcarcinoma: a NMR-based metabolomics approach

Jinghui Lu, Sanyuan Hu _, Paolo Miccoli, Qingdong Zeng, Shaozhuang Liu, Lin Ran and Chunxiao Hu

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Oncotarget. 2016; 7:81768-81777. https://doi.org/10.18632/oncotarget.13178

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Abstract

Jinghui Lu1, Sanyuan Hu1, Paolo Miccoli2, Qingdong Zeng1, Shaozhuang Liu1, Lin Ran3, Chunxiao Hu1

1Department of General Surgery, Qilu Hospital of Shandong University, Jinan 250012, P.R. China

2Department of General Surgery, University of Pisa, Pisa 56126, Italy

3Medical College of Shandong University, Jinan 250012, P.R. China

Correspondence to:

Sanyuan Hu, email: [email protected]

Keywords: papillary thyroid microcarcinoma, metabolomics, diagnosis, NMR

Received: August 20, 2016     Accepted: October 22, 2016     Published: November 07, 2016

ABSTRACT

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.


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