4.7 Article

Diagnostic approach to thyroid cancer based on amino acid metabolomics in saliva by ultra-performance liquid chromatography with high resolution mass spectrometry

期刊

TALANTA
卷 235, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.talanta.2021.122729

关键词

Saliva; Thyroid cancer; Diagnostic; Metabolomics; Amino acid

资金

  1. Northwest University
  2. National Key Research and Development Project [2018YFC1800903]
  3. Key Research and Development Pro-gram of Shaanxi Province of China [2019ZDLSF01-03]

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This study developed a UPLC-HRMS method to determine the metabolic levels of 10 amino acids in saliva for the early diagnosis of thyroid cancer. Results showed that a combination of alanine, valine, proline, and phenylalanine could improve the accuracy of thyroid cancer diagnosis. Salivary amino acid biomarkers have the potential for non-invasive early diagnosis of thyroid cancer.
Thyroid cancer is a malignant disease with dramatically low advanced-stage 10-year survival. Meanwhile, the metabolites in saliva are becoming a wealthy source of disease biomarkers. However, there is a lack of noninvasive analytical methods for the identification of biomarkers in saliva for the preoperative diagnosis of thyroid cancer. Therefore, we developed an ultra-high performance liquid chromatography-high resolution mass spectrometry (UPLC-HRMS) method to simultaneously determine the metabolic levels of 10 amino acids in saliva, aiming to study the amino acid metabolism profile to promote early diagnosis of thyroid cancer. We tested unstimulated whole saliva from patients with papillary thyroid carcinoma (PTC; n = 61) and healthy controls (HC; n = 61), and used receiver operating characteristic (ROC) curves to establish the diagnostic value of potential markers. The method validation results showed good precision, linearity (R2 0.99), recovery (92.2 %- 110.3 %), intra- and inter-day precision (RSD < 7 % and RSD < 9 %, respectively). The concentration of 10 amino acids was significantly different between PTC and HC in human salivary analysis (P < 0.05), the area under the curve (AUC) values of a single marker for the diagnosis of PTC were ranging from 0.678 to 0.833. A panel of alanine, valine, proline, phenylalanine was selected in combination yielded the AUC of 0.936, which will improve the accuracy of early diagnosis of thyroid cancer (sensitivity: 91.2 %; specificity: 85.2 %). This study proved the possibility of salivary amino acid biomarkers for PTC early diagnosis, providing a simple auxiliary way for the non-invasive diagnosis of thyroid cancer.

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