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Serum metabolomics reveals an innovative diagnostic model for salivary gland tumors.

Authors :
Wu, Mengmeng
Li, Bing
Zhang, Xingwei
Sun, Guowen
Source :
Analytical Biochemistry. Oct2022, Vol. 655, pN.PAG-N.PAG. 1p.
Publication Year :
2022

Abstract

An early diagnosis of salivary gland tumors (SGTs) and determination of their malignancy are conducive to developing individualized therapeutic strategies and thus improving prognosis. The aim of this study was to investigate the difference of serum metabolic profiles in patients with SGTs to better understand the mechanism of this disease and disease risk stratification. We used ultrahigh-performance liquid chromatography Q Exactive mass spectrometry and multivariate statistical analyses to conduct a comprehensive analysis of serum metabolites in a population with normal control and SGTs. 32 differentially expressed metabolites were identified, while the level of serine and lactic acid were investigated to gradually upregulate in benign SGTs and malignant SGTs. Then, the expression of serine and lactic acid were assessed in validation cohort using multiple reaction monitoring (MRM) based targeted metabolite analysis. A risk score formula based on the amount of serine and lactic acid was developed and explored to be significantly related to benign SGTs and malignant SGTs in discovery and validation cohort. Our work highlights the possible use of the risk score assessment based on the serum metabolites not only reveal in the early diagnosis of SGTs but also assist in enhancing current therapeutic strategies in the clinic. [Display omitted] • Non-targeted metabolomics revealed metabolic profiles in serum of salivary gland tumors. • Serine and lactic acid was assessed to gradually elevate in benign salivary gland tumors and malignant salivary gland tumors. • The expression of serine and lactic acid were assessed in validation cohort using MRM based targeted metabolite analysis. • A risk score formula based on serine and lactic acid was developed and assessed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00032697
Volume :
655
Database :
Academic Search Index
Journal :
Analytical Biochemistry
Publication Type :
Academic Journal
Accession number :
158931244
Full Text :
https://doi.org/10.1016/j.ab.2022.114853