4.7 Article

Nanoconfined liquid phase nanoextraction combined with in-fiber derivatization for simultaneous quantification of seventy amino-containing metabolites in plasma by LC-MS/MS: Exploration of lung cancer screening model

期刊

TALANTA
卷 245, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.talanta.2022.123452

关键词

Nanoconfined liquid phase nanoextraction; Metabolomics; In-fiber derivatization; Cancer biomarkers

资金

  1. National Natural Science Funds of China [81973464/H3203, 21775134, 82104126/H3410]
  2. Liaoning Distinguished Professor Project for Qing Li
  3. Shenyang Science and Technology Innovation Project for Young, Middle-aged Talents [RC190505]
  4. Liaoning BaiQianWan Talents Program [A-37]
  5. Liaoning Provincial Doctoral Research Start-up Fund Project for Qian Zhang

向作者/读者索取更多资源

A nanoconfined liquid phase nanoextraction (NLPNE) combined with in-fiber derivatization (IFD) strategy was proposed for simultaneous quantification of seventy amino-containing analytes in plasma. This method offers advantages of broad coverage, high sensitivity, time-and solvent-saving, and is applicable for cancer diagnosis.
Targeted metabolomics with absolute quantification is widely applied in biomarker identification and drug screening. However, due to the complexity of biological matrix and trace amount of metabolites in plasma, simultaneous quantification of highly polar metabolites in plasma with broad coverage in short time is still challenging. Herein, we proposed a nanoconfined liquid phase nanoextraction (NLPNE) combined with in-fiber derivatization (IFD) strategy that enabled simultaneous quantification of seventy amino-containing analytes in plasma, including amines, nucleosides and their metabolites. Methanol-water (2:1, v/v) was selected as nano confined solvent (NCS) to quickly extract highly polar analytes based on the nanoconfinement effect, followed by IFD process directly performed by adding the derivatization reagent benzoyl chloride (BzCl) within 5 min. Besides saving time, this combination strategy was environment-friendly with little organic solvent consumption and cost-effective by using reusable carbon nanofibers. Furthermore, the sensitivity was increased up to 4.92-fold compared with protein precipitation (PP) based conventional derivatization method. Key factors that affected derivatization efficiency including the derivatization time, the amount of derivatization reagent, desorption solution and CNFs, were optimized by response surface methodology (RSM). After systematical method validation, this methodology was applied to determine the multi-metabolites index in plasma of lung cancer using an integrated data processing workflow. Then lung cancer diagnosis model was established through binary logistic regression analysis to make a reference for quick lung cancer screening clinically. Taken together, the NLPNE-IFD LC-MS/MS method for targeted metabolomics enables simultaneous quantification of seventy amino-containing analytes with advantages of broad coverage, high sensitivity, time-and solvent-saving, which could be used on cancer diagnosis clinically.

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