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A fast UPLC-HILIC method for an accurate quantification of dendrogenin A in human tissues. | LitMetric

A fast UPLC-HILIC method for an accurate quantification of dendrogenin A in human tissues.

J Steroid Biochem Mol Biol

Team "Dose individualization of anticancer drugs », Cancer Research Center of Toulouse, UMR 1037 INSERM-University of Toulouse, Toulouse, France; Institut Claudius Regaud, Institut Universitaire du Cancer-Oncopole, Toulouse, France. Electronic address:

Published: November 2019

AI Article Synopsis

Article Abstract

Dendrogenin A (DDA) is a newly-discovered steroidal alkaloid, which remains to date the first ever found in mammals. DDA is a cholesterol metabolites that induces cancer cell differentiation and death in vitro and in vivo, and thus behave like a tumor suppressor metabolite. Preliminary studies performed on 10 patients with estrogen receptor positive breast cancers (ERBC) showed a strong decrease in DDA levels between normal matched tissue and tumors. This suggests that a deregulation on DDA metabolism is associated with breast carcinogenesis. To further investigate DDA metabolism on large cohorts of patients we have developed an ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS) procedure for the quantification of DDA in liquid and in solid tissues. This method enabled the identification of DDA analogues such as its geometric isomer C17 and dendrogenin B (C26) in human samples showing that other 5,6α-epoxycholesterol conjugation products with biogenic amines exist as endogenous metabolites . We report here the first complete method of quantification of DDA in liquid and solid tissues using hydrophilic interaction liquid chromatography (HILIC). Two different methods of extraction using either a Bligh and Dyer organic extraction or protein precipitation were successfully applied to quantify DDA in solid and liquid tissues. The protein precipitation method was the fastest. The fact that this method is automatable opens up possibilities to study DDA metabolism in large cohorts of patients.

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Source
http://dx.doi.org/10.1016/j.jsbmb.2019.105447DOI Listing

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