Detection and characterization of ponatinib reactive metabolites by liquid chromatography tandem mass spectrometry and elucidation of bioactivation pathways. Issue 76 (1st August 2016)

• Record Type: Journal Article
• Authors: Kadi, Adnan A.; Darwish, Hany W.; Attwa, Mohamed W.; Amer, Sawsan M.
• Is Part Of: RSC advances. Volume 6:Issue 76(2016)
• Page Start: 72575
• Page End: 72585
• Publication Date: 2016-08-01
• Subjects: Chemistry -- Periodicals; 540.5
• DOI: 10.1039/c6ra09985h
• Languages: English
• ISSNs: 2046-2069

Abstract

Abstract : This study involved the identification and characterization of ponatinib by LC-MS/MS. Additionally ponatinib reactive metabolites were also investigated using KCN as a trapping agent, showing the formation of four reactive cyano adducts. Abstract : Ponatinib (PNT), as a multi-targeted tyrosine kinase inhibitor, is active against T315I and other BCR-ABL mutants. PNT is registered in the U.S. and EU under the trade name of Iclusig®. The current study reports the identification and characterization of in vitro metabolites of PNT, which were produced by its incubation with rat liver microsomes (RLMs). PNT and its metabolites were extracted from the incubation mixture by the protein precipitation procedure and the supernatants were injected into high performance liquid chromatography tandem mass spectrometry (LC-MS/MS) equipment. Reversed phase liquid chromatography resolved seven in vitro PNT metabolites. Each metabolite displayed one or more metabolic reaction pathways including N -demethylation, N -oxide formation, oxidation, reduction and hydroxylation. Structures of the PNT metabolites showed high liability to form reactive metabolites. Since bioactivation is often speculated to be responsible for observed idiosyncratic toxicities including hepatotoxicity, incubation of PNT with RLMs was carried out in the presence of 1.0 mM GSH or 1.0 mM KCN to check its reactive metabolites. No GSH adduct was found while four cyano adduct metabolites were determined and their structures were proposed based on the mass scan and product ion data for each metabolite.