Gene Expression Dose-Response of Liver with a Genotoxic and Nongenotoxic Carcinogen

Distinguishing between genotoxic and non-genotoxic hepatocarcinogens by gene expression profiling and bioinformatic pathway analysis

A rapid and sensitive method to determine the characteristics of carcinogens is needed. In this study, we used a microarray-based genomics approach, with a short-term in vivo model, in combination with insights from statistical and mechanistic analyses to determine the characteristics of carcinogens. Carcinogens were evaluated based on the different mechanisms involved in the responses to genotoxic carcinogens and non-genotoxic carcinogens. Gene profiling was performed at two time points after treatment with six training and four test carcinogens. We mapped the DEG (differentially expressed gene)-related pathways to analyze cellular processes, and we discovered significant mechanisms that involve critical cellular components. Classification results were further supported by Comet and Micronucleus assays. Mechanistic studies based on gene expression profiling enhanced our understanding of the characteristics of different carcinogens. Moreover, the efficiency of this study was demonstrated by the short-term nature of the animal experiments that were conducted.

Network-based analysis of multivariate gene expression data

Multivariate microarray gene expression data are commonly collected to study the genomic responses under ordered conditions such as over increasing/decreasing dose levels or over time during biological processes, where the expression levels of a give gene are expected to be dependent. One important question from such multivariate gene expression experiments is to identify genes that show different expression patterns over treatment dosages or over time; these genes can also point to the pathways that are perturbed during a given biological process. Several empirical Bayes approaches have been developed for identifying the differentially expressed genes in order to account for the parallel structure of the data and to borrow information across all the genes. However, these methods assume that the genes are independent. In this paper, we introduce an alternative empirical Bayes approach for analysis of multivariate gene expression data by assuming a discrete Markov random field (MRF) prior, where the dependency of the differential expression patterns of genes on the networks are modeled by a Markov random field. Simulation studies indicated that the method is quite effective in identifying genes and the modified subnetworks and has higher sensitivity than the commonly used procedures that do not use the pathway information, with similar observed false discovery rates. We applied the proposed methods for analysis of a microarray time course gene expression study of TrkA- and TrkB-transfected neuroblastoma cell lines and identified genes and subnetworks on MAPK, focal adhesion, and prion disease pathways that may explain cell differentiation in TrkA-transfected cell lines.

Implications of the solvent vehicles dimethylformamide and dimethylsulfoxide for establishing transcriptomic endpoints in the zebrafish embryo toxicity test

Current aquatic chemical testing guidelines recognize that solvents can potentially interfere with the organism or environmental conditions of aquatic ecotoxicity tests and therefore recommend concentration limits for their use. These recommendations are based on evidence of adverse solvent effects in apical level tests. The growing importance of subapical and chronic endpoints in future test strategies, however, suggests that the limits may need reassessment. To address this concern, microarrays were used to determine the effects of organic solvents, dimethylformamide (DMF) and dimethylsulfoxide (DMSO), on the transcriptome of zebrafish (Danio rerio) embryos. Embryos were exposed for 48 h to a range of concentrations between 0.025 and 32.0 ml/L. Effects on survival and development after 24 and 48 h were assessed microscopically, with no effects on mortality or morphology up to 2.0 and 16.0 ml/L for DMF and DMSO. However, analysis of 48-h embryonic RNA revealed large numbers of differentially expressed genes at concentrations well below the 0.1 ml/L solvent limit level. The enrichment of differentially expressed genes was found for metabolic, developmental, and other key biological processes, some of which could be linked to observed morphological effects at higher solvent concentrations. These findings emphasize the need to remove or lower as far as possible the concentrations of solvent carriers in ecotoxicology tests.

Global liver proteomics of rats exposed for 5 days to phenobarbital identifies changes associated with cancer and with CYP metabolism

A global proteomics approach was applied to model the hepatic response elicited by the toxicologically well-characterized xenobiotic phenobarbital (PB), a prototypical inducer of hepatic xenobiotic metabolizing enzymes and a well-known nongenotoxic liver carcinogen in rats. Differential detergent fractionation two-dimensional liquid chromatography electrospray ionization tandem mass spectrometry and systems biology modeling were used to identify alterations in toxicologically relevant hepatic molecular functions and biological processes in the livers of rats following a 5-day exposure to PB at 80 mg/kg/day or a vehicle control. Of the 3342 proteins identified, expression of 121 (3.6% of the total proteins) was significantly increased and 127 (3.8%) significantly decreased in the PB group compared to controls. The greatest increase was seen for cytochrome P450 (CYP) 2B2 (167-fold). All proteins with statistically significant differences from control were then analyzed using both Gene Ontology (GO) and Ingenuity Pathways Analysis (IPA, 5.0 IPA-Tox) for cellular location, function, network connectivity, and possible disease processes, especially as they relate to CYP-mediated metabolism and nongenotoxic carcinogenesis mechanisms. The GO results suggested that PB's mechanism of nongenotoxic carcinogenesis involves both increased xenobiotic metabolism, especially induction of the 2B subfamily of CYP enzymes, and increased cell cycle activity. Apoptosis, however, also increased, perhaps, as an attempt to counter the rising cancer threat. Of the IPA-mapped proteins, 41 have functions which are procarcinogenic and 14 anticarcinogenic according to the hypothesized nongenotoxic mechanism of imbalance between apoptosis and cellular proliferation. Twenty-two additional IPA nodes can be classified as procarcinogenic by the competing theory of increased metabolism resulting in the formation of reactive oxygen species. Since the systems biology modeling corresponded well to PB effects previously elucidated via more traditional methods, the global proteomic approach is proposed as a new screening methodology that can be incorporated into future toxicological studies.

Can systems toxicology identify common biomarkers of non-genotoxic carcinogenesis?

For the rapid development of safe, efficacious chemicals it is important that any potential liabilities are identified as early as possible in the discovery/development pipeline. Once identified it is then possible to make rational decisions on whether to progress a chemical and/or series further; one such liability is chemical carcinogenesis, a highly undesirable characteristic in a novel chemical entity. Chemical carcinogens may be roughly divided into two classes, those that elicit their actions through direct damage to DNA (genotoxic carcinogens) and those that cause carcinogenesis through mechanisms that involve direct damage of the DNA by the agent (non-genotoxic carcinogens). Whereas the former group can be identified by in vitro screens to a good degree of accuracy, the latter group are far more problematic due to their diverse modes of action. This review will focus on the latter class of chemical carcinogens, examining how modern '-omic' technologies have begun to identify signatures that may represent sensitive, early markers for these processes. In addition to their use in signature generation the role of -omic level approaches to delineating molecular mechanisms of action will also be discussed.

Fish 'n' chips: the use of microarrays for aquatic toxicology

Gene expression analysis is changing the way that we look at toxicity, allowing toxicologists to perform parallel analyses of entire transcriptomes. While this technology is not as advanced in aquatic toxicology as it is for mammalian models, it has shown promise for determining modes of action, identifying biomarkers and developing "signatures" of chemicals that can be used for field and mixture studies. A major hurdle for the use of microarrays in aquatic toxicology is the lack of sequence information for non-model species. Custom arrays based on gene libraries enriched for genes that are expressed in response to specific contaminants have been used with excellent success for some non-model species, suggesting that this approach will work well for ecotoxicology and spurring on the sequencing of cDNA libraries for species of interest. New sequencing technology and development of repositories for gene expression data will accelerate the use of microarrays in aquatic toxicology. Notwithstanding the preliminary successes that have been achieved even with partial cDNA libraries printed on arrays, ecological samples present elevated challenges for this technology due to the high degree of variation of the samples. Furthermore, recent studies that show nonlinear toxic responses for ecological species underscore the necessity of establishing time and dose dependence of effects on gene expression and comparing these results with traditional markers of toxicity. To realize the full potential of microarrays, researchers must do the experiments required to bridge the gap between the 'omics' technologies and traditional toxicology to demonstrate that microarrays have predictive value in ecotoxicology.

Delayed expression of apoptotic and cell-cycle control genes in carcinogen-exposed bladders of mice lacking p53.S389 phosphorylation

Mice with non-phosphorylated serine 389 in p53 are susceptible for bladder tumors induced by 2-acetylaminofluorene (2-AAF). Since p53 is a transcription factor, this might well be preceded by differences in the regulation of gene expression. Microarray analysis was used to determine early transcriptional changes that might underlie this cancer-prone phenotype. Interestingly, lack of Ser389 phosphorylation led to endogenously different gene expression levels. The number of genes affected was, however, rather small. Conversely, after short-term exposure to 2-AAF, wild-type and p53.S389A bladders demonstrated a significant number of differentially expressed genes. Differences between wild-type and p53.S389A could mainly be attributed to a delayed, rather than complete absence of, transcriptional response of a group of genes, including well-known p53 target genes involved in apoptosis and cell-cycle control like Bax, Perp and P21. An analysis of differentially expressed genes in non-tumorigenic tissue and bladder tumors of p53.S389A after long-term exposure to 2-AAF revealed 319 genes. Comparison of these with those found after short-term exposure resulted in 23 transcripts. These possible marker genes might be useful for the early prediction of bladder tumor development. In conclusion, our data indicate that lack of Ser389 phosphorylation results in aberrant expression of genes needed to execute vital responses to DNA damage. Post-translational modifications, like Ser389 phosphorylation, seem crucial for fine-tuning the transcription of a specific set of genes and do not appear to give rise to major changes in transcription patterns. As such, Ser389 phosphorylation is needed for some, but certainly not all, p53 functions.