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Investigation of the content differences of arachidonic acid metabolites in a mouse model of breast cancer by using LC–MS/MS.

Authors :
Chen, Ang
Zhang, Yuanjin
Sun, Dongyi
Xu, Yeye
Guo, Yuanqing
Wang, Xin
Source :
Journal of Pharmaceutical & Biomedical Analysis. Feb2021, Vol. 194, pN.PAG-N.PAG. 1p.
Publication Year :
2021

Abstract

• LC–MS/MS analysis method was developed for arachidonic acid metabolome. • The method was firstly applied for eicosanoids determination in a mouse model of breast cancer. • Significant content differences of arachidonic acid and its metabolites were found. • Eicosanoids may be used as new biomarkers to assist for breast cancer diagnosis. Arachidonic acid (AA) is closely associated with breast cancer. In addition to the two metabolic pathways regulated by cyclooxygenase and lipoxygenase, AA has a third metabolic pathway through which cytochrome P450 (CYP) enzymes produce hydroxyeicosatetraenoic acids (HETEs) and epoxyeicosatrienoic acids (EETs). The targeted CYP-mediated pathway of AA can not only kill cancer cells but also inhibit the interstitial microenvironment around a tumor. Therefore, it makes sense to identify potential biomarkers from the AA metabolome for the diagnosis and treatment of breast cancer. This study established a liquid chromatography-tandem mass spectrometry (LC–MS/MS) method for the analysis of AA and its main metabolites, EETs and HETEs, in MMTV-PyMT mice, a spontaneous breast cancer mouse model. The results showed that there were significant differences in the concentrations of AA, 12-HETE, 19-HETE and 8,9-EET in plasma and tumor tissues between normal and MMTV-PyMT mice. Therefore, the eicosanoids mentioned above may be used as new biomarkers for breast cancer diagnosis. This study provides a new perspective for the recognition and diagnosis of breast cancer. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
07317085
Volume :
194
Database :
Academic Search Index
Journal :
Journal of Pharmaceutical & Biomedical Analysis
Publication Type :
Academic Journal
Accession number :
147909764
Full Text :
https://doi.org/10.1016/j.jpba.2020.113763