[Show abstract][Hide abstract] ABSTRACT: All new pharmaceutical agents must be screened for potential toxicity in humans. This process includes a series of genotoxic screens in the discovery phase, and in the event the drug is designed for chronic use, a 2-year non-genotoxicity rodent study. Such non-genotoxicity studies are very expensive because of their duration, the amount of compound required, and the number of rodents required. Models capable of predicting genotoxicity during discovery would reduce these costs and increase favorable outcomes for drugs in a pipeline of development by reducing the rate of attrition. To that end, we have used gene expression data and evolved neural networks to classify compounds by their carcinogenicity or genotoxicity. 60 compounds were used for the training and testing of classifiers relative to gene expression from rat liver cells. Genes related to xenobiotic metabolism, proliferation, apoptosis, and DNA damage were identified. Our study demonstrates that evolved neural networks can be used to classify compounds as carcinogenic or genotoxic with reasonable accuracy.
Evolutionary Computation (CEC), 2011 IEEE Congress on; 07/2011
[Show abstract][Hide abstract] ABSTRACT: Belinostat is a hydroxamate-type histone deactylase inhibitor (HDACi), which has recently entered phase I and II clinical trials. Microarray-based analysis of belinostat-treated cell lines showed an impact on genes associated with the G2/M phase of the cell cycle and downregulation of the aurora kinase pathway. Expression of 25 dysregulated genes was measured in eight differentially sensitive cell lines using a novel high-throughput assay that combines multiplex reverse transcriptase-PCR and fluorescence capillary electrophoresis. Sensitivity to belinostat and the magnitude of changes in overall gene modulation were significantly correlated. A belinostat-gene profile was specific for HDACi in three cell lines when compared with equipotent concentrations of four mechanistically different chemotherapeutic agents: 5-fluorouracil, cisplatin, paclitaxel, and thiotepa. Belinostat- and trichostatin A (HDACi)-induced gene responses were highly correlated with each other, but not with the limited changes in response to the other non-HDACi agents. Moreover, belinostat treatment of mice bearing human xenografts showed that the preponderance of selected genes were also modulated in vivo, more extensively in a drug-sensitive tumor than a more resistant model. We have demonstrated a gene signature that is selectively regulated by HDACi when compared with other clinical agents allowing us to distinguish HDACi responses from those related to other mechanisms.
[Show abstract][Hide abstract] ABSTRACT: Peroxisome proliferator-activated receptor gamma (PPARgamma) agonists of the thiazolidinedione family are used for the treatment of type 2 diabetes mellitus due to their ability to reduce glucose and lipid levels in patients with this disease. Three thiazolidinediones that were approved for treatment are Rezulin (troglitazone), Avandia (rosiglitazone), and Actos (pioglitazone). Troglitazone was withdrawn from the market due to idiosyncratic drug toxicity. Rosiglitazone and pioglitazone are still on the market for the treatment of type 2 diabetes. The authors present data from a gene expression screen that compares the impact these three compounds have in rats, in rat hepatocytes, and in the clone 9 rat liver cell line. The authors monitored the changes in expression in multiple genes, including those related to xenobiotic metabolism, proliferation, DNA damage, oxidative stress, apoptosis, and inflammation. Compared to the other two compounds, troglitazone had a significant impact on many of the pathways monitored in vitro although no major perturbation was detected in vivo. The changes detected predict not only general toxicity but potential mechanisms of toxicity. Based on gene expression analysis, the authors propose there is not just one but multiple ways troglitazone could be toxic, depending on a patient's environment and genetic makeup, including immune response-related toxicity.
International Journal of Toxicology 01/2006; 25(2):85-94. · 1.35 Impact Factor