Li Jingjie,
Liu Shumei,
Wang Dong,
Liu Jiang,
Lv Shuqin ,
Traditional Chinese Medical Hospital of Xinjiang Uygur Autonomous Region, 116 Huanghe Road, Urumqi, Xinjiang 830000, China;
For correspondence:- Lv Shuqin
Email: lvshuqin@126.com
Accepted: 20 February 2021
Published: 31 March 2021
Citation:
Jingjie L, Shumei L, Dong W, Jiang L, Shuqin L,
Urine metabonomic study on primary liver cancer with spleen deficiency and excess dampness syndrome based on ultra-performance LC-MS. Trop J Pharm Res 2021; 20(3):639-647
doi:
10.4314/tjpr.v20i3.29
© 2021 The authors.
This is an Open Access article that uses a funding model which does not charge readers or their institutions for access and distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0) and the Budapest Open Access Initiative (http://www.budapestopenaccessinitiative.org/read), which permit unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited..
Abstract
Purpose: To investigate spleen deficiency and excess dampness syndrome (SDES) in primary liver cancer (PLC) and the underlying mechanism using ultra pressure liquid chromatography-mass spectrometry (UPLC-MS).
Methods: Ultra-performance liquid chromatography coupled with mass spectrometry (UPLC-MS) was used to detect urine metabolites from untreated and IPED-treatment PLC-SDES patients. The metabolites were annotated using Kyoto Encyclopedia of Genes and Genomes (KEGG), Human Metabolome Database (HMDB), and Lipidmaps. Principle component analysis (PCA) and partial least squares to latent structure-discriminant analysis (PLS-DA) models were built to reveal the metabolic differences between untreated, IPED-treated patients and healthy controls. The differential metabolites in PLC-SDES patients were screened according to variables important in the project (VIP) and p-value.
Results: In urine, 537 metabolites (256 in negative and 281 in positive mode) were considered differential in PLC-SDES patients when compared to healthy controls. In untreated patients, 100 metabolites (38 in negative and 62 in positive mode) were differential when compared to IPED-treatment patients. The urine of PLC-SDES patients showed overlap of 32 metabolites.
Conclusion: The results reveal comprehensive urine metabonomic changes in PLC-SDES patients, relative to healthy controls and IPED-treated patients. The identified metabolites may be potential biomarkers for diagnosis and IPED therapy.
Keywords: Metabonomics, Liver cancer, Ultra performance liquid chromatography-mass spectrometry, UPLC-MS, Biomarker, Traditional Chinese medicine