Human Liver Microsomal Metabolism and DNA Adduct Formation of the Tumorigenic Pyrrolizidine Alkaloid, Riddelliine

2003 ◽  
Vol 16 (1) ◽  
pp. 66-73 ◽  
Author(s):  
Qingsu Xia ◽  
Ming W. Chou ◽  
Fred. F. Kadlubar ◽  
Po-Cheun Chan ◽  
Peter P. Fu
2005 ◽  
Vol 226 (1) ◽  
pp. 27-35 ◽  
Author(s):  
Yu-Ping Wang ◽  
Jian Yan ◽  
Richard D. Beger ◽  
Peter P. Fu ◽  
Ming W. Chou

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e3703 ◽  
Author(s):  
Victorien Delannée ◽  
Sophie Langouët ◽  
Nathalie Théret ◽  
Anne Siegel

Background Heterocyclic aromatic amines (HAA) are environmental and food contaminants that are potentially carcinogenic for humans. 2-Amino-3,8-dimethylimidazo[4,5-f]quinoxaline (MeIQx) is one of the most abundant HAA formed in cooked meat. MeIQx is metabolized by cytochrome P450 1A2 in the human liver into detoxificated and bioactivated products. Once bioactivated, MeIQx metabolites can lead to DNA adduct formation responsible for further genome instability. Methods Using a computational approach, we developed a numerical model for MeIQx metabolism in the liver that predicts the MeIQx biotransformation into detoxification or bioactivation pathways according to the concentration of MeIQx. Results Our results demonstrate that (1) the detoxification pathway predominates, (2) the ratio between detoxification and bioactivation pathways is not linear and shows a maximum at 10 µM of MeIQx in hepatocyte cell models, and (3) CYP1A2 is a key enzyme in the system that regulates the balance between bioactivation and detoxification. Our analysis suggests that such a ratio could be considered as an indicator of MeIQx genotoxicity at a low concentration of MeIQx. Conclusions Our model permits the investigation of the balance between bioactivation (i.e., DNA adduct formation pathway through the prediction of potential genotoxic compounds) and detoxification of MeIQx in order to predict the behaviour of this environmental contaminant in the human liver. It highlights the importance of complex regulations of enzyme competitions that should be taken into account in any further multi-organ models.


1998 ◽  
Vol 12 (4) ◽  
pp. 353-364 ◽  
Author(s):  
W. Feser ◽  
R.S. Kerdar ◽  
A. Baumann ◽  
J. Körber ◽  
H. Blode ◽  
...  

2001 ◽  
Vol 14 (1) ◽  
pp. 101-109 ◽  
Author(s):  
Ya-Chen Yang ◽  
Jian Yan ◽  
Daniel R. Doerge ◽  
Po-Cheun Chan ◽  
Peter P. Fu ◽  
...  

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