A mechanism-based mathematical model of aryl hydrocarbon receptor-mediated CYP1A induction in rats using beta-naphthoflavone as a tool compound.

ß-Naphthoflavone (BNF) is a synthetic flavone that selectively and potently induces CYP1A enzymes via aryl hydrocarbon receptor activation. Mechanism-based mathematical models of CYP1A enzyme induction were developed to predict the time course of enzyme induction and quantitatively evaluate the interrelationship between BNF plasma concentrations, hepatic CYP1A1 and CYP1A2 mRNA levels, and CYP1A enzyme activity in rats in vivo. Male Sprague-Dawley rats received a continuous intravenous infusion of vehicle or 1.5 or 6 mg · kg(-1) · h(-1) BNF for 6 h, with blood and liver sampling. Plasma BNF concentrations were determined by liquid chromatography-tandem mass spectrometry. Hepatic mRNA levels of CYP1A1 and CYP1A2 were determined by TaqMan. Ethoxyresorufin O-deethylation was used to measure the increase in CYP1A enzyme activity as a result of induction. The induction of hepatic CYP1A1/CYP1A2 mRNA and CYP1A activity occurred within 2 h after BNF administration. This caused a rapid increase in metabolic clearance of BNF, resulting in plasma concentrations declining during the infusion. Overall, the enzyme induction models developed in this study adequately captured the time course of BNF pharmacokinetics, CYP1A1/CYP1A2 mRNA levels, and increases in CYP1A enzyme activity data for both dose groups simultaneously. The model-predicted degradation half-life of CYP1A enzyme activity is comparable with previously reported values. The present results also confirm a previous in vitro finding that CYP1A1 is the predominant contributor to CYP1A induction. These physiologically based models provide a basis for predicting drug-induced toxicity in humans from in vitro and preclinical data and can be a valuable tool in drug development.

Phenobarbital and phenytoin increased acetaminophen hepatotoxicity due to inhibition of UDP-glucuronosyltransferases in cultured human hepatocytes.

Here we present a preclinical model to assess drug-drug interactions due to inhibition of glucuronidation. Treatment with the antiepileptics phenobarbital (PB) or phenytoin (PH) has been associated with increased incidence of acetaminophen (APAP) hepatotoxicity in patients. In human hepatocytes, we found that the toxicity of APAP (5 mM) was increased by simultaneous treatment with phenobarbital (2 mM) or phenytoin (0.2 mM). In contrast, pretreatment with PB for 48 h prior to APAP treatment did not increase APAP toxicity unless both drugs were present simultaneously. Cells treated with APAP in combination with PB or PH experienced decreases in protein synthesis as early as 1 h, ultrastructural changes by 24 h, and release of liver enzymes by 48 h. Toxicity correlated with inhibition of APAP glucuronidation. PB or PH also inhibited APAP glucuronidation in rat and human liver microsomes and expressed human UGT1A6, 1A9, and 2B15. As with intact hepatocytes, PB and PH were neither hydroxylated nor glucuronidated, suggesting the direct inhibition of UGTs. Our findings suggest that, in multiple drug therapy, an inhibitory complex between UGT and one of the drugs can lead to decreased glucuronidation and increased systemic exposure and toxicity of a coadministered drug.

Molecular target class is predictive of in vitro response profile.

Preclinical cellular response profiling of tumor models has become a cornerstone in the development of novel cancer therapeutics. As efforts to predict clinical efficacy using cohorts of in vitro tumor models have been successful, expansive panels of tumor-derived cell lines can recapitulate an "all comers" efficacy trial, thereby identifying which tumors are most likely to benefit from treatment. The response profile of a therapy is most often studied in isolation; however, drug treatment effect patterns in tumor models across a diverse panel of compounds can help determine the value of unique molecular target classes in specific tumor cohorts. To this end, a panel of 19 compounds was evaluated against a diverse group of cancer cell lines (n = 311). The primary oncogenic targets were a key determinant of concentration-dependent proliferation response, as a total of five of six, four of four, and five of five phosphatidylinositol 3-kinase (PI3K)/AKT/mammalian target of rapamycin (mTOR) pathway, insulin-like growth factor-I receptor (IGF-IR), and mitotic inhibitors, respectively, clustered with others of that common target class. In addition, molecular target class was correlated with increased responsiveness in certain histologies. A cohort of PI3K/AKT/mTOR inhibitors was more efficacious in breast cancers compared with other tumor types, whereas IGF-IR inhibitors more selectively inhibited growth in colon cancer lines. Finally, specific phenotypes play an important role in cellular response profiles. For example, luminal breast cancer cells (nine of nine; 100%) segregated from basal cells (six of seven; 86%). The convergence of a common cellular response profile for different molecules targeting the same oncogenic pathway substantiates a rational clinical path for patient populations most likely to benefit from treatment. Cancer Res; 70(9); 3677-86. (c)2010 AACR.