Biomedical subjects

Michael McMillian

Publications and source records attributed to Michael McMillian.

7 recordsLinked to original sources

PubMed2006

Predictive toxicogenomics approaches reveal underlying molecular mechanisms of nongenotoxic carcinogenicity.

Toxicogenomics technology defines toxicity gene expression signatures for early predictions and hypotheses generation for mechanistic studies, which are important approaches for evaluating toxicity of drug candidate compounds. A large gene expression database built using cDNA microarrays and liver samples treated with over one hundred paradigm compounds was mined to determine gene expression signatures for nongenotoxic carcinogens (NGTCs). Data were obtained from male rats treated for 24 h. Training/testing sets of 24 NGTCs and 28 noncarcinogens were used to select genes. A semiexhaustive, nonredundant gene selection algorithm yielded six genes (nuclear transport factor 2, NUTF2; progesterone receptor membrane component 1, Pgrmc1; liver uridine diphosphate glucuronyltransferase, phenobarbital-inducible form, UDPGTr2; metallothionein 1A, MT1A; suppressor of lin-12 homolog, Sel1h; and methionine adenosyltransferase 1, alpha, Mat1a), which identified NGTCs with 88.5% prediction accuracy estimated by cross-validation. This six genes signature set also predicted NGTCs with 84% accuracy when samples were hybridized to commercially available CodeLink oligo-based microarrays. To unveil molecular mechanisms of nongenotoxic carcinogenesis, 125 differentially expressed genes (P<0.01) were selected by Student's t-test. These genes appear biologically relevant, of 71 well-annotated genes from these 125 genes, 62 were overrepresented in five biochemical pathway networks (most linked to cancer), and all of these networks were linked by one gene, c-myc. Gene expression profiling at early time points accurately predicts NGTC potential of compounds, and the same data can be mined effectively for other toxicity signatures. Predictive genes confirm prior work and suggest pathways critical for early stages of carcinogenesis.

Animals↗

PubMed2006

Application of genomics in preclinical drug safety evaluation.

Understanding the response of biological systems to xenobiotics is fundamental to the evaluation of drug safety. Toxicologists have traditionally gathered pathological, morphological, chemical and biochemical information from in vivo studies of preclinical species in order to assess drug safety and to determine how new drugs can be safely administered to the human patient population. In recent years the emerging "-omics" technologies have been developed and integrated into preclinical studies in order to better assess drug safety by gaining information on the cellular and molecular events underlying adverse drug reactions. Genomics approaches in particular have become readily available and are being applied in several stages of drug development. The burgeoning literature on what has become known as "toxicogenomics" has for the most part highlighted successful applications of gene expression profiling in predictive toxicology, enabling decisions to be made on the developability of a compound early in the drug development process. It is also becoming apparent that toxicogenomic approaches are good starting points to develop experiments designed to gain a mechanistic insight into drug toxicities within and across species. Gene expression arrays permit the measurement of responses of essentially all the genes in the entire genome to be monitored, and knowledge of the function of the genes affected can identify the potential mechanisms to then be confirmed using conventional biochemical, toxicological and pathological approaches. As toxicologists put these technologies into practice they build up a knowledge base to better characterize toxicities at the molecular level and to make the search for much needed, novel biomarkers of toxicity more achievable.

Drug Evaluation, Preclinical↗

PubMed2005

Drug-induced oxidative stress in rat liver from a toxicogenomics perspective.

Macrophage activators (MA), peroxisome proliferators (PP), and oxidative stressors/reactive metabolites (OS/RM) all produce oxidative stress and hepatotoxicity in rats. However, these three classes of hepatotoxicants give three distinct gene transcriptional profiles on cDNA microarrays, an indication that rat hepatocytes respond/adapt quite differently to these three classes of oxidative stressors. The differential gene responses largely reflect differential activation of transcription factors: MA activate Stat-3 and NFkB, PP activate PPARa, and OS/RM activate Nrf2. We have used gene signature profiles for each of these three classes of hepatotoxicants to categorize over 100 paradigm (and 50+ in-house proprietary) compounds as to their oxidative stress potential in rat liver. In addition to a role for microarrays in predictive toxicology, analyses of small subsets of these signature profiles, genes within a specific pathway, or even single genes often provide important insights into possible mechanisms involved in the toxicities of these compounds.

Animals↗

PubMed2005

Class prediction in toxicogenomics.

The intent of this article is to discuss some of the complexities of toxicogenomics data and the statistical design and analysis issues that arise in the course of conducting a toxicogenomics study. We also describe a procedure for classifying compounds into various hepatotoxicity classes based on gene expression data. The methodology involves first classifying a compound as toxic or nontoxic and subsequently classifying the toxic compounds into the hepatotoxicity classes, based on votes by binary classifiers. The binary classifiers are constructed by using genes selected to best elicit differences between the two classes. We show that the gene selection strategy improves the misclassification error rates and also delivers gene pathways that exhibit biological relevance.

Algorithms↗

PubMed2004

A gene expression signature for oxidant stress/reactive metabolites in rat liver.

Formation of free radicals and other reactive molecules is responsible for the adverse effects produced by a number of hepatotoxic compounds. cDNA microarray technology was used to compare transcriptional profiles elicited by training and testing sets of 15 oxidant stressors/reactive metabolite treatments to those produced by approximately 85 other paradigm compounds (mostly hepatotoxicants) to determine a shared signature profile for oxidant stress-associated hepatotoxicity. Initially, 100 genes were chosen that responded significantly different to oxidant stressors/reactive metabolites (OS/RM) compared to other samples in the database, then a 25-gene subset was selected by multivariate analysis. Many of the selected genes (e.g., aflatoxin aldehyde reductase, diaphorase, epoxide hydrolase, heme oxgenase and several glutathione transferases) are well-characterized oxidant stress/Nrf-2-responsive genes. Less than 10 other compounds co-cluster with our training and testing set compounds and these are known to generate OS/RMs as part of their mechanisms of toxicity. Using OS/RM signature gene sets, compounds previously associated with macrophage activation formed a distinct cluster separate from OS/RM and other compounds. A 69-gene set was chosen to maximally separate compounds in control, macrophage activator, peroxisome proliferator and OS/RM classes. The ease with which these 'oxidative stressor' classes can be separated indicates a role for microarray technology in early prediction and classification of hepatotoxicants. The ability to rapidly screen the oxidant stress potential of compounds may aid in avoidance of some idiosyncratic drug reactions as well as overtly toxic compounds.

Animals↗

PubMed2004

Inverse gene expression patterns for macrophage activating hepatotoxicants and peroxisome proliferators in rat liver.

Macrophage activation contributes to adverse effects produced by a number of hepatotoxic compounds. Transcriptional profiles elicited by two macrophage activators, LPS and zymosan A, were compared to those produced by 100 paradigm compounds (mostly hepatotoxicants) using cDNA microarrays. Several hepatotoxicants previously reported to activate liver macrophages produced transcriptional responses similar to LPS and zymosan, and these were used to construct a gene signature profile for macrophage activators in the liver. Measurement of cytokine mRNAs in the same liver samples by RT-PCR independently confirmed that these compounds are associated with macrophage activation. In addition to expected effects on acute phase proteins and metabolic pathways that are regulated by LPS and inflammation, a strong induction was observed for many endoplasmic reticulum-associated stress/chaperone proteins. Additionally, many genes in our macrophage activator signature profile were well-characterized PPARalpha-induced genes which were repressed by macrophage activators. A shared gene signature profile for peroxisome proliferators was determined using a training set of clofibrate, WY 14643, diethylhexylphthalate, diisononylphthalate, perfluorodecanoic acid, perfluoroheptanoic acid, and perfluorooctanoic acid. The signature profile included macrophage activator-induced genes that were repressed by peroxisome proliferators. NSAIDs comprised an interesting pharmacological class in that some compounds, notably diflunisal, co-clustered with peroxisome proliferators whereas several others co-clustered with macrophage activators, possibly due to endotoxin exposure secondary to their adverse effects on the gastrointestinal system. While much of these data confirmed findings from the literature, the transcriptional patterns detected using this toxicogenomics approach showed relationships between genes and biological pathways requiring complex analysis to be discerned.

Animals↗

PubMed2004

Determination of cytochrome P450 1A2 and cytochrome P450 3A4 induction in cryopreserved human hepatocytes.

Freshly prepared human hepatocytes are considered as the 'gold standard' for in vitro testing of drug candidates. However, several disadvantages are associated with the use of this model system. The availability of hepatocytes is often low and consequently the planning of the experiments rendered difficult. In addition, the quality of the available cells is in some cases poor. As an alternative, cryopreserved human hepatocytes were validated as a model to study cytochrome P450 1A2 (CYP1A2) and cytochrome P450 3A4 (CYP3A4) induction. In a single blinded experiment, hepatocytes from three separate lots were incubated with three concentrations of different compounds, and compared to non-treated cells and cells incubated with omeprazole or rifampicin. CYP1A2 and CYP3A4 induction was determined by measuring 7-ethoxyresorufin-O-deethylation activity and 6beta-hydroxytestosterone formation, respectively. CYP1A2 and CYP3A4 mRNA and protein expression were analyzed by TaqMan QRT-PCR and immunodetection. Cells responded well to the prototypical inducers with a mean 38.8- and 6.2-fold induction of CYP1A2 and CYP3A4 activity, respectively. Similar as with fresh human hepatocytes, high batch-to-batch variation of CYP1A2 and CYP3A4 induction was observed. Except for 1 and 10 microM rosiglitazone, the glitazones did not significantly affect CYP1A2. A similar result was observed for CYP3A4 activity although CYP3A4 mRNA and protein expression were dose-dependently upregulated. In conclusion, cryopreserved human hepatocytes may be a good alternative to fresh hepatocytes to study CYP1A and 3A induction.

Cells, Cultured↗