In vitro characterization of the human biotransformation and CYP reaction phenotype of ET-743 (Yondelis(C), Trabectidin(C)), a novel marine anti-cancer drug.
Brandon, Esther F. A. 1; Sparidans, Rolf W. 1; Guijt, Kees-Jan 1; Lowenthal, Sjoerd 1; Meijerman, Irma 1; Beijnen, Jos H. 1,2; Schellens, Jan H. M. 1,3
[Article]
Investigational New Drugs.
24(1):3-14, January 2006.
(Format: HTML, PDF)
Summary: ET-743 is a potent marine anti-cancer drug and is currently being investigated in phase I and II clinical trials, e.g. in combination with other anti-cancer agents. To assess the biotransformation and CYP reaction phenotype and their potential implications for human pharmacology and toxicology, the in vitro metabolism of ET-743 was characterized using incubations with human liver preparations, cytochrome P450 (CYP) and uridine diphosphoglucuronosyl transferase (UGT) supersomes.
CYP supersomes and liver microsomes showed that ET-743 was metabolized mainly by CYP3A4, but also by CYP2C9, 2C19, 2D6, and 2E1. ET-743 showed the highest affinity for CYP3A4 and the highest maximal metabolic rate for CYP2D6 among the CYPs shown to metabolize ET-743. In addition, the Km value of ET-743 in female microsomes was significantly lower compared to male microsomes, while the Vmax values did not differ. ET-743 glucuronidation, catalyzed by UGT2B15, was observed in microsomes and S9 fraction. In addition, conjugation by glutathione-S-transferase and no sulphation was observed for ET-743 in cytosol and S9 fraction. ET-743 was more extensively metabolized when CYP activity was combined with phase II enzymes UGT and glutathione-S-transferase (GST), indicating that CYP, UGT, and GST simultaneously metabolize ET-743 in the S9 fraction.
These results provide evidence that CYP3A4 has a major role in the metabolism of ET-743 in vitro with additional involvement of CYP2C9, 2C19, 2D6, and 2E1. Furthermore, ET-743 is conjugated by UGT and GST. This information could be important for interpretation of the pharmacokinetic data of clinical trials and prediction of drug-drug interactions.
(C)2006 Kluwer Academic Publishers
