Discrimination of genotoxic and non-genotoxic hepatocarcinogens by statistical analysis based on gene expression profiling in the mouse liver as determined by quantitative real-time PCR

Evaluation of functional candidate biomarkers of non-genotoxic hepatocarcinogenicity in human liver spheroid co-cultures

Validated in vitro assays for testing non-genotoxic carcinogenic potential of chemicals are currently not available. Consequently, the two-year rodent bioassay remains the gold standard method for the identification of these chemicals. Transcriptomic and proteomic analyses have provided a comprehensive understanding of the non-genotoxic carcinogenic processes, however, functional changes induced by effects at transcriptional and translational levels have not been addressed. The present study was set up to test a number of proposed in vitro biomarkers of non-genotoxic hepatocarcinogenicity at the functional level using a translational 3-dimensional model. Spheroid cultures of human hepatocytes and stellate cells were exposed to 5 genotoxic carcinogenic, 5 non-genotoxic carcinogenic, and 5 non-carcinogenic chemical compounds and assessed for oxidative stress, mitochondrial dysfunction, endoplasmic reticulum stress, apoptosis, and inflammation. The spheroid model could capture many of these events triggered by the genotoxic carcinogenic chemicals, particularly aflatoxin B1 and hydroquinone. Nonetheless, no clear distinction could be made between genotoxic and non-genotoxic hepatocarcinogenicity. Therefore, spheroid cultures of human liver cells may be appropriate in vitro tools for mechanistic investigation of chemical-induced hepatocarcinogenicity, however, these mechanisms and their read-outs do not seem to be eligible biomarkers for detecting non-genotoxic carcinogenic chemicals.

Short-term in vivo testing to discriminate genotoxic carcinogens from non-genotoxic carcinogens and non-carcinogens using next-generation RNA sequencing, DNA microarray, and qPCR

Next-generation RNA sequencing (RNA-Seq) has identified more differentially expressed protein-coding genes (DEGs) and provided a wider quantitative range of expression level changes than conventional DNA microarrays. JEMS·MMS·Toxicogenomics group studied DEGs with targeted RNA-Seq on freshly frozen rat liver tissues and on formalin-fixed paraffin-embedded (FFPE) rat liver tissues after 28 days of treatment with chemicals and quantitative real-time PCR (qPCR) on rat and mouse liver tissues after 4 to 48 h treatment with chemicals and analyzed by principal component analysis (PCA) as statics. Analysis of rat public DNA microarray data (Open TG-GATEs) was also performed. In total, 35 chemicals were analyzed [15 genotoxic hepatocarcinogens (GTHCs), 9 non-genotoxic hepatocarcinogens (NGTHCs), and 11 non-genotoxic non-hepatocarcinogens (NGTNHCs)]. As a result, 12 marker genes (Aen, Bax, Btg2, Ccnf, Ccng1, Cdkn1a, Gdf15, Lrp1, Mbd1, Phlda3, Plk2, and Tubb4b) were proposed to discriminate GTHCs from NGTHCs and NGTNHCs. U.S. Environmental Protection Agency studied DEGs induced by 4 known GTHCs in rat liver using DNA microarray and proposed 7 biomarker genes, Bax, Bcmp1, Btg2, Ccng1, Cdkn1a, Cgr19, and Mgmt for GTHCs. Studies involving the use of whole-transcriptome RNA-Seq upon exposure to chemical carcinogens in vivo have also been performed in rodent liver, kidney, lung, colon, and other organs, although discrimination of GTHCs from NGTHCs was not examined. Candidate genes published using RNA-Seq, qPCR, and DNA microarray will be useful for the future development of short-term in vivo studies of environmental carcinogens using RNA-Seq.

Quinoline is more genotoxic than 4-methylquinoline in hiHeps cells and rodent liver

Environmental pollutants, such as quinoline (QN) and 4-methylquinoline (4-MeQ), may be genotoxic and carcinogenic. Earlier studies, including in vitro genotoxicity tests, indicated that 4-MeQ is more mutagenic than QN. However, we hypothesized that the methyl group of 4-MeQ favors detoxication over bioactivation, and this factor may be overlooked in in vitro tests that do not incorporate supplementation with cofactors for enzymes that catalyze conjugation reactions. We used human induced hepatocyte cells (hiHeps), which express such enzymes, and compared the genotoxicity of 4-MeQ and QN. We also carried out an in vivo micronucleus (MN) test in rat liver, since 4-MeQ is not genotoxic in rodent bone marrow. In the Ames test and the Tk gene mutation assay, with rat S9 activation, 4-MeQ was more mutagenic than QN. However, QN induced significantly higher MN frequencies in hiHeps and rat liver than did 4-MeQ. Furthermore, QN upregulated genotoxicity marker genes much more than did 4-MeQ. We also investigated the roles of two important detoxication enzymes, UDP-glucuronosyltransferases (UGTs) and cytosolic sulfotransferases (SULTs). When hiHeps were preincubated with hesperetin (UGT inhibitor) and 2,6-dichloro-4-nitrophenol (SULT inhibitor), MN frequencies were elevated approximately 1.5-fold for 4-MeQ, whereas no significant effects were seen for QN. This study shows that QN is more genotoxic than 4-MeQ, when the roles of SULTs and UGTs in detoxication are considered and our results may improve understanding the structure-activity relationships of quinoline derivatives.

RAID: Regression Analysis–Based Inductive DNA Microarray for Precise Read-Across

Chemical structure-based read-across represents a promising method for chemical toxicity evaluation without the need for animal testing; however, a chemical structure is not necessarily related to toxicity. Therefore, in vitro studies were often used for read-across reliability refinement; however, their external validity has been hindered by the gap between in vitro and in vivo conditions. Thus, we developed a virtual DNA microarray, regression analysis–based inductive DNA microarray (RAID), which quantitatively predicts in vivo gene expression profiles based on the chemical structure and/or in vitro transcriptome data. For each gene, elastic-net models were constructed using chemical descriptors and in vitro transcriptome data to predict in vivo data from in vitro data (in vitro to in vivo extrapolation; IVIVE). In feature selection, useful genes for assessing the quantitative structure–activity relationship (QSAR) and IVIVE were identified. Predicted transcriptome data derived from the RAID system reflected the in vivo gene expression profiles of characteristic hepatotoxic substances. Moreover, gene ontology and pathway analysis indicated that nuclear receptor-mediated xenobiotic response and metabolic activation are related to these gene expressions. The identified IVIVE-related genes were associated with fatty acid, xenobiotic, and drug metabolisms, indicating that in vitro studies were effective in evaluating these key events. Furthermore, validation studies revealed that chemical substances associated with these key events could be detected as hepatotoxic biosimilar substances. These results indicated that the RAID system could represent an alternative screening test for a repeated-dose toxicity test and toxicogenomics analyses. Our technology provides a critical solution for IVIVE-based read-across by considering the mode of action and chemical structures.

Activation of the hypothalamic-pituitary-adrenal axis by exogenous and endogenous GDF15

An acute increase in the circulating concentration of glucocorticoid hormones is essential for the survival of severe somatic stresses. Circulating concentrations of GDF15, a hormone that acts in the brain to reduce food intake, are frequently elevated in stressful states. We now report that GDF15 potently activates the hypothalamic-pituitary-adrenal (HPA) axis in mice and rats. A blocking antibody to the GDNF-family receptor α-like receptor completely prevented the corticosterone response to GDF15 administration. In wild-type mice exposed to a range of stressful stimuli, circulating levels of both corticosterone and GDF15 rose acutely. In the case of Escherichia coli or lipopolysaccharide injections, the vigorous proinflammatory cytokine response elicited was sufficient to produce a near-maximal HPA response, regardless of the presence or absence of GDF15. In contrast, the activation of the HPA axis seen in wild-type mice in response to the administration of genotoxic or endoplasmic reticulum toxins, which do not provoke a marked rise in cytokines, was absent in Gdf15 ^-/- mice. In conclusion, consistent with its proposed role as a sentinel hormone, endogenous GDF15 is required for the activation of the protective HPA response to toxins that do not induce a substantial cytokine response. In the context of efforts to develop GDF15 as an antiobesity therapeutic, these findings identify a biomarker of target engagement and a previously unrecognized pharmacodynamic effect, which will require monitoring in human studies.

Linking Coregulated Gene Modules with Polycyclic Aromatic Hydrocarbon-Related Cancer Risk in the 3D Human Bronchial Epithelium

Exposure to polycyclic aromatic hydrocarbons (PAHs) often occurs as complex chemical mixtures, which are linked to numerous adverse health outcomes in humans, with cancer as the greatest concern. The cancer risk associated with PAH exposures is commonly evaluated using the relative potency factor (RPF) approach, which estimates PAH mixture carcinogenic potential based on the sum of relative potency estimates of individual PAHs, compared to benzo[a]pyrene (BAP), a reference carcinogen. The present study evaluates molecular mechanisms related to PAH cancer risk through integration of transcriptomic and bioinformatic approaches in a 3D human bronchial epithelial cell model. Genes with significant differential expression from human bronchial epithelium exposed to PAHs were analyzed using a weighted gene coexpression network analysis (WGCNA) two-tiered approach: first to identify gene sets comodulated to RPF and second to link genes to a more comprehensive list of regulatory values, including inhalation-specific risk values. Over 3000 genes associated with processes of cell cycle regulation, inflammation, DNA damage, and cell adhesion processes were found to be comodulated with increasing RPF with pathways for cell cycle S phase and cytoskeleton actin identified as the most significantly enriched biological networks correlated to RPF. In addition, comodulated genes were linked to additional cancer-relevant risk values, including inhalation unit risks, oral cancer slope factors, and cancer hazard classifications from the World Health Organization's International Agency for Research on Cancer (IARC). These gene sets represent potential biomarkers that could be used to evaluate cancer risk associated with PAH mixtures. Among the values tested, RPF values and IARC categorizations shared the most similar responses in positively and negatively correlated gene modules. Together, we demonstrated a novel manner of integrating gene sets with chemical toxicity equivalence estimates through WGCNA to understand potential mechanisms.

Classifying polycyclic aromatic hydrocarbons by carcinogenic potency using in vitro biosignatures

One of the most difficult challenges for risk assessment is evaluation of chemicals that predominately co-occur in mixtures like polycyclic aromatic hydrocarbons (PAHs). We previously developed a classification model in which systems biology data collected from mice short-term after chemical exposure accurately predict tumor outcome. The present study demonstrates translation of this approach into a human in vitro model in which chemical-specific bioactivity profiles from 3D human bronchial epithelial cells (HBEC) classify PAHs by carcinogenic potency. Gene expression profiles were analyzed from HBEC exposed to carcinogenic and non-carcinogenic PAHs and classification accuracies were identified for individual pathway-based gene sets. Posterior probabilities of best performing gene sets were combined via Bayesian integration resulting in a classifier with four gene sets, including aryl hydrocarbon receptor signaling, regulation of epithelial mesenchymal transition, regulation of angiogenesis, and cell cycle G2-M. In addition, transcriptional benchmark dose modeling of benzo[a]pyrene (BAP) showed that the most sensitive gene sets to BAP regulation were largely dissimilar from those that best classified PAH carcinogenicity challenging current assumptions that BAP carcinogenicity (and subsequent mode of action) is reflective of overall PAH carcinogenicity. These results illustrate utility of using systems toxicology approaches to analyze global gene expression towards carcinogenic hazard assessment.

Using FFPE RNA-Seq with 12 marker genes to evaluate genotoxic and non-genotoxic rat hepatocarcinogens

Introduction

Various challenges have been overcome with regard to applying 'omics technologies for chemical risk assessments. Previously we published results detailing targeted mRNA sequencing (RNA-Seq) on a next generation sequencer using intact RNA derived from freshly frozen rat liver tissues. We successfully discriminated genotoxic hepatocarcinogens (GTHCs) from non-genotoxic hepatocarcinogens (NGTHCs) using 11 selected marker genes. Based on this, we next attempted to use formalin-fixed paraffin-embedded (FFPE) pathology specimens for RNA-Seq analyses.

Findings

In this study we performed FFPE RNA-Seq to compare a typical GTHC, 2-acetylaminofluorene (AAF) to genotoxicity equivocal p-cresidine (CRE). CRE is used as a synthetic chemical intermediate, and this compound is classified as an IARC 2B carcinogen and is mutagenic in S. typhimurium, which is non-genotoxic to rat livers as assessed by single strand DNA damage analysis. RNA-Seq was used to examine liver FFPE samples obtained from groups of five 10-week-old male F344 rats that were fed with chemicals (AAF: 0.025% and CRE: 1% in food) for 4 weeks or from controls that were fed a basal diet. We extracted RNAs from FFPE samples and RNA-Seq was performed on a MiniSeq (Illumina) using the TruSeq custom RNA panel. AAF induced remarkable differences in the expression of eight genes (Aen, Bax, Btg2, Ccng1, Gdf15, Mbd1, Phlda3 and Tubb4b) from that in the control group, while CRE only induced expression changes in Gdf15, as shown using Tukey's test. Gene expression profiles for nine genes (Aen, Bax, Btg2, Ccng1, Cdkn1a, Gdf15, Mbd1, Phlda3, and Plk2) differed.between samples treated with AAF and CRE. Finally, principal component analysis (PCA) of 12 genes (Aen, Bax, Btg2, Ccnf, Ccng1, Cdkn1a, Gdf15, Lrp1, Mbd1, Phlda3, Plk2, and Tubb4b) using our previous Open TG-GATE data plus FFPE-AAF and FFPE-CRE successfully differentiated FFPE-AAF, as GTHC, from FFPE-CRE, as NGHTC.

Conclusion

Our results suggest that FFPE RNA-Seq and PCA are useful for evaluating typical rat GTHCs and NGTHCs.

A toxicogenomic approach for the risk assessment of the food contaminant acetamide

Acetamide (CAS 60-35-5) is detected in common foods. Chronic rodent bioassays led to its classification as a group 2B possible human carcinogen due to the induction of liver tumors in rats. We used a toxicogenomics approach in Wistar rats gavaged daily for 7 or 28 days at doses of 300 to 1500 mg/kg/day (mkd) to determine a point of departure (POD) and investigate its mode of action (MoA). Ki67 labeling was increased at doses ≥750 mkd up to 3.3-fold representing the most sensitive apical endpoint. Differential gene expression analysis by RNA-Seq identified 1110 and 1814 differentially expressed genes in male and female rats, respectively, following 28 days of treatment. Down-regulated genes were associated with lipid metabolism while up-regulated genes included cell signaling, immune response, and cell cycle functions. Benchmark dose (BMD) modeling of the Ki67 labeling index determined the BMD10 lower confidence limit (BMDL10) as 190 mkd. Transcriptional BMD modeling revealed excellent concordance between transcriptional POD and apical endpoints. Collectively, these results indicate that acetamide is most likely acting through a mitogenic MoA, though specific key initiating molecular events could not be elucidated. A POD value of 190 mkd determined for cell proliferation is suggested for risk assessment purposes.

Twenty years of metabonomics: so what has metabonomics done for toxicology?

In 1999 the journal Xenobiotica published a perspective article detailing the new concept of metabonomics and its application to toxicology. The approach was to apply analytical chemistry techniques, and in particular ¹H NMR spectroscopy, to profile biofluids and tissues to assess the metabolic effects of xenobiotics. Metabonomics has been shown to be sensitive not only to organ specific toxicity but also provides information on the cells, tissues and mechanisms involved, as well as their interactions with the host's sex, age, diet and environment. This review assesses the impact of metabonomics on drug toxicology over the past twenty years and its future prospects. These applications include:Pharmacometabonomics - the prediction of drug effects through the analysis of predose, biofluid metabolite profiles, which reflect both genetic and environmental influences on physiology.The microbiomes role in toxicology - understanding how xenobiotics can be modified by the microbiome dramatically changing their impact on the host.Development of expert systems for toxicity prediction.Data fusion of different omics to better understand the underlying mechanisms of drug toxicity.Metabonomics and exposome - understanding how multiple environmental toxicants might interact with the host organism to produce their overall phenotype. While there has been huge growth in the use of metabonomics within toxicology these applications are set to increase as the tools become more sensitive and robust, as well as the increased use of both experimental and in silico databases to aid prediction of toxicology.

Dysfunctional Mechanism of Liver Cancer Mediated by Transcription Factor and Non-coding RNA

Background:

There have been numerous experiments and studies on liver cancer by biomedical scientists, while no comprehensive and systematic exploration has yet been conducted. Therefore, this study aimed to systematically dissect the transcriptional and non-coding RNAmediated mechanisms of liver cancer dysfunction.

Method:

At first, we collected 974 liver cancer associated genes from the Online Mendelian Inheritance in Man (OMIM). Afterwards, their interactors were recruited from STRING database so as to identify 18 co-expression modules in liver cancer patient expression profile. Crosstalk analysis showed the interactive relationship between these modules. In addition, core drivers for modules were identified, including 111 transcription factors (STAT3, JUN and NFKB1, etc.) and 1492 ncRNAs (FENDRR and miR-340-5p, etc.).

Results:

In view of the results of enrichment, we found that these core drivers were significantly involved in Notch signaling, Wnt / β-catenin pathways, cell proliferation, apoptosis-related functions and pathways, suggesting they can affect the development of liver cancer. Furthermore, a global effect on bio-network associated with liver cancer has been integrated from the ncRNA and TF pivot network, module crosstalk network, module-function/pathways network. It involves various development and progression of cancer.

Conclusion:

Overall, our analysis further suggests that comprehensive network analysis will help us to not only understand in depth the molecular mechanisms, but also reveal the influence of related gene dysfunctional modules on the occurrence and progression of liver cancer. It provides a valuable reference for the design of liver cancer diagnosis and treatment.

Evaluation of 12 mouse marker genes in rat toxicogenomics public data, Open TG-GATEs: Discrimination of genotoxic from non-genotoxic hepatocarcinogens

Previously, we proposed 12 marker genes (Aen, Bax, Btg2, Ccnf, Ccng1, Cdkn1a, Gdf15, Lrp1, Mbd1, Phlda3, Plk2 and Tubb4b) to discriminate mouse genotoxic hepatocarcinogens (GTHC) from non-genotoxic hepatocarcinogens (NGTHC). This was determined by qPCR and principal component analysis (PCA), as the aim of an in vivo short-term screening for genotoxic hepatocarcinogens. For this paper, we conducted an application study of the 12 mouse marker genes to rat data, Open TG-GATEs (public data). We analyzed five typical rat GTHC (2-acetamodofluorene, aflatoxin B1, 2-nitrofluorene, N-nitrosodiethylamine and N-nitrosomorpholine), and not only seven typical rat NGTHC (clofibrate, ethanol, fenofibrate, gemfibrozil, hexachlorobenzene, phenobarbital and WY-14643) but also 11 non-genotoxic non-hepatocarcinogens (NGTNHC; allyl alcohol, aspirin, caffeine, chlorpheniramine, chlorpropamide, dexamethasone, diazepam, indomethacin, phenylbutazone, theophylline and tolbutamide) from Open TG-GATEs. The analysis was performed at 3, 6, 9 and 24 h after a single administration and 4, 8, 15 and 29 days after repeated administrations. We transferred Open TG-GATEs DNA microarray data into log₂ data using the "R Project for Statistical Computing". GTHC-specific dose-dependent gene expression changes were observed and significance assessed with the Williams test. Similar significant changes were observed during 3-24 h and 4-29 days, assessed with Welch's t-test, except not for NGTHC or NGTNHC. Significant differential changes in gene expression were observed between GTHC and NGTHC in 11 genes (except not Tubb4b) and between GTHC and NGTNHC in all 12 genes at 24 h and 10 genes (except Ccnf and Mbd1) at 29 days, per Tukey's test. PCA successfully discriminated GTHC from NGTHC and NGTNHC at 24 h and 29 days. The results demonstrate that 12 previously proposed mouse marker genes are useful for discriminating rat GTHC from NGTHC and NGTNHC from Open TG-GATEs.

Using RNA-Seq with 11 marker genes to evaluate 1,4-dioxane compared with typical genotoxic and non-genotoxic rat hepatocarcinogens

It has long been unclear whether 1,4-dioxane (DO) is a genotoxic hepatocarcinogen (GTHC). Therefore, the present study aimed to evaluate rat GTHCs and non-genotoxic hepatocarcinogens (NGTHCs) via selected gene expression patterns in the liver, as determined by next generation sequencing-targeted mRNA sequencing (RNA-Seq) and principal component analysis (PCA). Previously, we selected 11 marker genes (Aen, Bax, Btg2, Ccnf, Ccng1, Cdkn1a, Lrp1, Mbd1, Phlda3, Plk2, and Tubb4b) to discriminate GTHCs and NGTHCs. In the present study, we quantified changes in the expression of these genes following DO treatment, and compared them with treatment with two typical rat GTHCs, N-nitrosodiethylamine (DEN) and 3,3'-dimethylbenzidine·2HCl (DMB), and a typical rat NGTHC, di(2-ethylhexyl)phthalate (DEHP). RNA-Seq was conducted on liver samples from groups of five male, 10-week-old F344 rats after 4 weeks' feeding of chemicals in the water or the food. Rats in the control group were given water and a basal diet. Significant changes in gene expression in experimental groups compared with the control group were observed in eight genes (Aen, Bax, Btg2, Ccnf, Ccng1, Cdkn1a, Phlda3 and Plk2), as shown by Tukey's test. Gene expression profiles of the 11 genes under DO treatment differed significantly from those with DEN and DMB, as well as DEHP. Gene expression profiles with DO treatment differed partially from those with typical GTHCs for five genes (Bax, Btg2, Cdkn1a, Lrp1 and Plk2) and were substantially different from treatment with a typical NGTHC (DEHP) for nine genes (Aen, Bax, Btg2, Ccnf, Ccng1, Cdkn1a, Mbd1, Phlda3 and Tubb4b) as determined by Tukey's test. Finally, PCA successfully differentiated GTHCs from DEHP and DO with the 11 genes. The present results suggest that RNA-Seq and PCA are useful to evaluate rat typical GTHCs and typical NGTHCs. DO was suggested to result in a different intermediate gene expression profile from typical GTHCs and NGTHC.

Novel miRNA biomarkers for genotoxicity screening in mouse

The genotoxic potential of drugs is a serious problem, and its evaluation is one of the most critical processes of drug development. Although the comet assay of compound-exposed tissue is a frequently used genotoxicity test, its high false-positive rate is a major complication, and we consistently obtained false-positive results using the comet assay of mouse liver for nine hepatotoxic non-genotoxins (NGTXs). To identify novel genotoxin (GTX)-specific biomarkers, we screened the expression of 750 microRNAs (miRNAs) in the livers of mice treated with GTXs or NGTXs. Three miRNAs, miR-22-3p, miR-409-3p, and miR-543-3p, were significantly down-regulated in GTX-treated mouse liver. In contrast, these three miRNAs were significantly up-regulated in plasma. A discrimination model based on the expression levels of these biomarkers successfully identified GTXs and NGTXs. This novel biomarker expression-based discrimination model analysis using both liver and plasma is effective for detecting genotoxicity with high sensitivity and reliability to support drug development.

Chinese herbal formula Fuzheng Huayu alleviates CCl4-induced liver fibrosis in rats: a transcriptomic and proteomic analysis

Liver fibrosis is a consequence of chronic liver disease that can progress to liver cirrhosis or even hepatocarcinoma. Fuzheng Huayu (FZHY), a Chinese herbal formula, has been shown to exert anti-fibrotic effects. To better understand the molecular mechanisms underlying the anti-fibrotic effects of FZHY, we analyzed transcriptomic and proteomic combination profiles in CCl₄-induced liver fibrosis in rats, which were treated with extracted FZHY powder (0.35 g·kg^-1·d^-1, ig) for 3 weeks. We showed that FZHY administration significantly improved liver function, alleviated hepatic inflammatory and fibrotic changes, and decreased the hydroxyproline content in the livers of CCl₄-treated rats. When their liver tissues were examined using microarray and iTRAQ, we found 255 differentially expressed genes (fold change ≥1.5, P<0.05) and 499 differentially expressed proteins (fold change ≥1.2, P<0.05) in the FZHY and model groups. Functional annotation with DAVID (The Database for Annotation, Visualization and Integrated Discovery) showed that 15 enriched gene ontology terms, including drug metabolic process, response to extracellular stimulus, response to vitamins, arachidonic acid metabolic process, response to wounding, and oxidation reduction might be involved in the anti-fibrotic effects of FZHY; whereas KEGG pathway analysis revealed that eight enriched pathways, including arachidonic acid metabolism, retinol metabolism, metabolism of xenobiotics by cytochrome P450, and drug metabolism might also be involved. Moreover, the protein-protein interaction network demonstrated that 10 core genes/proteins overlapped, with Ugt2a3, Cyp2b1 and Cyp3a18 in retinol metabolism pathway overlapped to a higher degree. Compared to the model rats, the livers of FZHY-treated rats had significantly higher mRNA and protein expression levels of Ugt2a3, Cyp2b1 and Cyp3a18. Furthermore, the concentration of retinoic acid was significantly higher in the FZHY-treated rats compared with the model rats. The results suggest that the anti-fibrotic effects of FZHY emerge through multiple targets, multiple functions, and multiple pathways, including FZHY-regulated retinol metabolism, xenobiotic metabolism by cytochrome P450, and drug metabolism through up-regulated Ugt2a3, Cyp2b1, and Cyp3a18. These genes may play important anti-fibrotic roles in FZHY-treated rats.

Mechanism-based risk assessment strategy for drug-induced cholestasis using the transcriptional benchmark dose derived by toxicogenomics

Cholestasis is one of the major causes of drug-induced liver injury (DILI), which can result in withdrawal of approved drugs from the market. Early identification of cholestatic drugs is difficult due to the complex mechanisms involved. In order to develop a strategy for mechanism-based risk assessment of cholestatic drugs, we analyzed gene expression data obtained from the livers of rats that had been orally administered with 12 known cholestatic compounds repeatedly for 28 days at three dose levels. Qualitative analyses were performed using two statistical approaches (hierarchical clustering and principle component analysis), in addition to pathway analysis. The transcriptional benchmark dose (tBMD) and tBMD 95% lower limit (tBMDL) were used for quantitative analyses, which revealed three compound sub-groups that produced different types of differential gene expression; these groups of genes were mainly involved in inflammation, cholesterol biosynthesis, and oxidative stress. Furthermore, the tBMDL values for each test compound were in good agreement with the relevant no observed adverse effect level. These results indicate that our novel strategy for drug safety evaluation using mechanism-based classification and tBMDL would facilitate the application of toxicogenomics for risk assessment of cholestatic DILI.

Animal models as a tool in hepatocellular carcinoma research: A Review

Cancer is the first cause of death in developed countries and the second in developing countries. Concerning the most frequent worldwide-diagnosed cancer, primary liver cancer represents approximately 4% of all new cancer cases diagnosed globally. However, among primary liver cancer, hepatocellular carcinoma is by far the most common histological subtype. Notwithstanding the health promotion and disease prevention campaigns, more than half a million new hepatocellular carcinoma cases are reported yearly, being estimated to growth continuously until 2020. Taking this scenario under consideration and the fact that some aspects concerning hepatocellular carcinoma evolution and metastasize process are still unknown, animal models assume a crucial role to understand this disease. The animal models have also provided the opportunity to screen new therapeutic strategies. The present review was supported on research and review papers aiming the complexity and often neglected chemically induced animal models in hepatocarcinogenesis research. Despite the ongoing debate, chemically induced animal models, namely, mice and rat, can provide unique valuable information on the biotransformation mechanisms against xenobiotics and apprehend the deleterious effects on DNA and cell proteins leading to carcinogenic development. In addition, taking under consideration that no model achieves all hepatocellular carcinoma research purposes, criteria to define the " ideal" animal model, depending on the researchers' approach, are also discussed in this review.

Procarcinogens - Determination and Evaluation by Yeast-Based Biosensor Transformed with Plasmids Incorporating RAD54 Reporter Construct and Cytochrome P450 Genes

In Vietnam, a great number of toxic substances, including carcinogens and procarcinogens, from industrial and agricultural activities, food production, and healthcare services are daily released into the environment. In the present study, we report the development of novel yeast-based biosensor systems to determine both genotoxic carcinogens and procarcinogens by cotransformation with two plasmids. One plasmid is carrying human CPR and CYP (CYP3A4, CYP2B6, or CYP2D6) genes, while the other contains the RAD54-GFP reporter construct. The three resulting coexpression systems bearing both CPR-CYP and RAD54-GFP expression cassettes were designated as CYP3A4/CYP2B6/CYP2D6 + RAD54 systems, respectively and used to detect and evaluate the genotoxic potential of carcinogens and procarcinogens by selective activation and induction of both CPR-CYP and RAD54-GFP expression cassettes in response to DNA damage. Procarcinogens were shown to be predominantly, moderately or not bioactivated by one of the CYP enzymes and thus selectively detected by the specific coexpression system. Aflatoxin B₁ and benzo(a)pyrene were predominantly detected by the CYP3A4 + RAD54 system, while N-nitrosodimethylamine only moderately activated the CYP2B6 + RAD54 reporter system and none of them was identified by the CYP2D6 + RAD54 system. In contrast, the genotoxic carcinogen, methyl methanesulfonate, was detected by all systems.

Our yeast-reporter system can be performed in 384-well microplates to provide efficient genotoxicity testing to identify various carcinogenic compounds and reduce chemical consumption to about 53% as compared with existing 96-well genotoxicity bioassays. In association with a liquid handling robot, this platform enables rapid, cost-effective, and high-throughput screening of numerous analytes in a fully automated and continuous manner without the need for user interaction.

Collaborative studies in toxicogenomics in rodent liver in JEMS·MMS; a useful application of principal component analysis on toxicogenomics

Toxicogenomics is a rapidly developing discipline focused on the elucidation of the molecular and cellular effects of chemicals on biological systems. As a collaborative study group of Toxicogenomics/JEMS·MMS, we conducted studies on hepatocarcinogens in rodent liver in which 100 candidate marker genes were selected to discriminate genotoxic hepatocarcinogens from non-genotoxic hepatocarcinogens. Differential gene expression induced by 13 chemicals were examined using DNA microarray and quantitative real-time PCR (qPCR), including eight genotoxic hepatocarcinogens [o-aminoazotoluene, chrysene, dibenzo[a,l]pyrene, diethylnitrosamine (DEN), 7,12-dimethylbenz[a]anthracene, dimethylnitrosamine, dipropylnitrosamine and ethylnitrosourea (ENU)], four non-genotoxic hepatocarcinogens [carbon tetrachloride, di(2-ethylhexyl)phthalate (DEHP), phenobarbital and trichloroethylene] and a non-genotoxic non-hepatocarcinogen [ethanol]. Using qPCR, 30 key genes were extracted from mouse livers at 4 h and 28 days following dose-dependent gene expression alteration induced by DEN and ENU: the most significant changes in gene expression were observed at 4 h. Next, we selected key point times at 4 and 48 h from changes in time-dependent gene expression during the acute phase following administration of chrysene by qPCR. We successfully showed discrimination of eight genotoxic hepatocarcinogens [2-acetylaminofluorene, 2,4-diaminotoluene, diisopropanolnitrosamine, 4-dimethylaminoazobenzene, 4-(methylnitsosamino)-1-(3-pyridyl)-1-butanone, N-nitrosomorpholine, quinoline and urethane] from four non-genotoxic hepatocarcinogens [1,4-dichlorobenzene, dichlorodiphenyltrichloroethane, DEHP and furan] using qPCR and principal component analysis. Additionally, we successfully identified two rat genotoxic hepatocarcinogens [DEN and 2,6-dinitrotoluene] from a nongenotoxic-hepatocarcinogen [DEHP] and a non-genotoxic non-hepatocarcinogen [phenacetin] at 4 and 48 h. The subsequent gene pathway analysis by Ingenuity Pathway Analysis extracted the DNA damage response, resulting from the signal transduction of a p53-class mediator leading to the induction of apoptosis. The present review of these studies suggests that application of principal component analysis on the gene expression profile in rodent liver during the acute phase is useful to predict genotoxic hepatocarcinogens in comparison to non-genotoxic hepatocarcinogens and/or non-carcinogenic hepatotoxins.

In vivo Signatures of Genotoxic and Non-genotoxic Chemicals

This chapter reviews the findings from a broad array of in vivo genomic studies with the goal of identifying a general signature of genotoxicity (GSG) that is indicative of exposure to genotoxic agents (i.e. agents that are active in either the bacterial mutagenesis and/or the in vivo micronucleus test). While the GSG has largely emerged from systematic studies of rat and mouse liver, its response is evident across a broad collection of genotoxic treatments that cover a variety of tissues and species. Pathway-based characterization of the GSG indicates that it is enriched with genes that are regulated by p53. In addition to the GSG, another pan-tissue signature related to bone marrow suppression (a common effect of genotoxic agent exposure) is reviewed. Overall, these signatures are quite effective in identifying genotoxic agents; however, there are situations where false positive findings can occur, for example when necrotizing doses of non-genotoxic soft electrophiles (e.g. thioacetamide) are used. For this reason specific suggestions for best practices for generating for use in the creation and application of in vivo genomic signatures are reviewed.

An integrative test strategy for cancer hazard identification

Assessment of genotoxic and carcinogenic potential is considered one of the basic requirements when evaluating possible human health risks associated with exposure to chemicals. Test strategies currently in place focus primarily on identifying genotoxic potential due to the strong association between the accumulation of genetic damage and cancer. Using genotoxicity assays to predict carcinogenic potential has the significant drawback that risks from non-genotoxic carcinogens remain largely undetected unless carcinogenicity studies are performed. Furthermore, test systems already developed to reduce animal use are not easily accepted and implemented by either industries or regulators. This manuscript reviews the test methods for cancer hazard identification that have been adopted by the regulatory authorities, and discusses the most promising alternative methods that have been developed to date. Based on these findings, a generally applicable tiered test strategy is proposed that can be considered capable of detecting both genotoxic as well as non-genotoxic carcinogens and will improve understanding of the underlying mode of action. Finally, strengths and weaknesses of this new integrative test strategy for cancer hazard identification are presented.

Synergistic Gene Expression Signature Observed in TK6 Cells upon Co-Exposure to UVC-Irradiation and Protein Kinase C-Activating Tumor Promoters

Activation of stress response pathways in the tumor microenvironment can promote the development of cancer. However, little is known about the synergistic tumor promoting effects of stress response pathways simultaneously induced in the tumor microenvironment. Therefore, the purpose of this study was to establish gene expression signatures representing the interaction of pathways deregulated by tumor promoting agents and pathways induced by DNA damage. Human lymphoblastoid TK6 cells were pretreated with the protein kinase C activating tumor promoter 12-O-tetradecanoylphorbol-13-acetate (TPA) and exposed to UVC-irradiation. The time and dose-responsive effects of the co-treatment were captured with RNA-sequencing (RNA-seq) in two separate experiments. TK6 cells exposed to both TPA and UVC had significantly more genes differentially regulated than the theoretical sum of genes induced by either stress alone, thus indicating a synergistic effect on global gene expression patterns. Further analysis revealed that TPA+UVC co-exposure caused synergistic perturbation of specific genes associated with p53, AP-1 and inflammatory pathways important in carcinogenesis. The 17 gene signature derived from this model was confirmed with other PKC-activating tumor promoters including phorbol-12,13-dibutyrate, sapintoxin D, mezerein, (-)-Indolactam V and resiniferonol 9,13,14-ortho-phenylacetate (ROPA) with quantitative real-time PCR (QPCR). Here we show a novel gene signature that may represent a synergistic interaction in the tumor microenvironment that is relevant to the mechanisms of chemical induced tumor promotion.

The adverse outcome pathway for rodent liver tumor promotion by sustained activation of the aryl hydrocarbon receptor

An Adverse Outcome Pathway (AOP) represents the existing knowledge of a biological pathway leading from initial molecular interactions of a toxicant and progressing through a series of key events (KEs), culminating with an apical adverse outcome (AO) that has to be of regulatory relevance. An AOP based on the mode of action (MOA) of rodent liver tumor promotion by dioxin-like compounds (DLCs) has been developed and the weight of evidence (WoE) of key event relationships (KERs) evaluated using evolved Bradford Hill considerations. Dioxins and DLCs are potent aryl hydrocarbon receptor (AHR) ligands that cause a range of species-specific adverse outcomes. The occurrence of KEs is necessary for inducing downstream biological responses and KEs may occur at the molecular, cellular, tissue and organ levels. The common convention is that an AOP begins with the toxicant interaction with a biological response element; for this AOP, this initial event is binding of a DLC ligand to the AHR. Data from mechanistic studies, lifetime bioassays and approximately thirty initiation-promotion studies have established dioxin and DLCs as rat liver tumor promoters. Such studies clearly show that sustained AHR activation, weeks or months in duration, is necessary to induce rodent liver tumor promotion--hence, sustained AHR activation is deemed the molecular initiating event (MIE). After this MIE, subsequent KEs are 1) changes in cellular growth homeostasis likely associated with expression changes in a number of genes and observed as development of hepatic foci and decreases in apoptosis within foci; 2) extensive liver toxicity observed as the constellation of effects called toxic hepatopathy; 3) cellular proliferation and hyperplasia in several hepatic cell types. This progression of KEs culminates in the AO, the development of hepatocellular adenomas and carcinomas and cholangiolar carcinomas. A rich data set provides both qualitative and quantitative knowledge of the progression of this AOP through KEs and the KERs. Thus, the WoE for this AOP is judged to be strong. Species-specific effects of dioxins and DLCs are well known--humans are less responsive than rodents and rodent species differ in sensitivity between strains. Consequently, application of this AOP to evaluate potential human health risks must take these differences into account.

The glucosinolate metabolite 1-methoxy-3-indolylmethyl alcohol induces a gene expression profile in mouse liver similar to the expression signature caused by known genotoxic hepatocarcinogens

SCOPE

Breakdown products of certain glucosinolates induce detoxifying enzymes and demonstrate preventive activities against chemically induced tumourigenesis in animal models. However, other breakdown products are genotoxic. 1-Methoxy-3-indolylmethyl alcohol (1-MIM-OH) is mutagenic in bacterial and mammalian cells upon activation by sulphotransferases and forms DNA adducts in mouse tissues. This effect is enhanced in mice transgenic for human sulphotransferases 1A1/2 (FVB/N-hSULT1A1/2). Therefore, we explored gene expression changes induced by 1-MIM-OH in mouse liver.

METHODS AND RESULTS

FVB/N-hSULT1A1/2 mice were orally treated with 1-MIM-OH for 21 or 90 days, leading to high levels of hepatic 1-MIM-DNA adducts. Genome-wide expression analyses demonstrated no influence on detoxifying enzymes, but up-regulation of many mediators of the tumour suppressor p53 and down-regulation of Fhit and other long genes. While this p53 response might indicate protection, it was unable to prevent the accumulation of DNA adducts. However, various epidemiological studies reported inverse associations between the intake of cruciferous vegetables and cancer. This association may be due to the presence of other glucosinolates with tumour-preventing influences possibly outweighing adverse effects of some metabolites.

CONCLUSION

1-MIM-OH is a genotoxic substance inducing a gene expression profile similar to the expression signature caused by known genotoxic hepatocarcinogens.

Identification of specific mRNA signatures as fingerprints for carcinogenesis in mice induced by genotoxic and nongenotoxic hepatocarcinogens

Long-term rodent carcinogenicity studies for evaluation of chemicals and pharmaceuticals concerning their carcinogenic potential to humans are currently receiving critical revision. Additional data from mechanistic studies can support cancer risk assessment by clarifying the underlying mode of action. In the course of the IMI MARCAR project, a European consortium of EFPIA partners and academics, which aims to identify biomarkers for nongenotoxic carcinogenesis, a toxicogenomic mouse liver database was generated. CD-1 mice were orally treated for 3 and 14 days with 3 known genotoxic hepatocarcinogens: C.I. Direct Black 38, Dimethylnitrosamine and 4,4'-Methylenedianiline; 3 nongenotoxic hepatocarcinogens: 1,4-Dichlorobenzene, Phenobarbital sodium and Piperonyl butoxide; 4 nonhepatocarcinogens: Cefuroxime sodium, Nifedipine, Prazosin hydrochloride and Propranolol hydrochloride; and 3 compounds that show ambiguous results in genotoxicity testing: Cyproterone acetate, Thioacetamide and Wy-14643. By liver mRNA expression analysis using individual animal data, we identified 64 specific biomarker candidates for genotoxic carcinogens and 69 for nongenotoxic carcinogens for male mice at day 15. The majority of genotoxic carcinogen biomarker candidates possess functions in DNA damage response (eg, apoptosis, cell cycle progression, DNA repair). Most of the identified nongenotoxic carcinogen biomarker candidates are involved in regulation of cell cycle progression and apoptosis. The derived biomarker lists were characterized with respect to their dependency on study duration and gender and were successfully used to characterize carcinogens with ambiguous genotoxicity test results, such as Wy-14643. The identified biomarker candidates improve the mechanistic understanding of drug-induced effects on the mouse liver that result in hepatocellular adenomas and/or carcinomas in 2-year mouse carcinogenicity studies.

Investigating the different mechanisms of genotoxic and non-genotoxic carcinogens by a gene set analysis

Based on the process of carcinogenesis, carcinogens are classified as either genotoxic or non-genotoxic. In contrast to non-genotoxic carcinogens, many genotoxic carcinogens have been reported to cause tumor in carcinogenic bioassays in animals. Thus evaluating the genotoxicity potential of chemicals is important to discriminate genotoxic from non-genotoxic carcinogens for health care and pharmaceutical industry safety. Additionally, investigating the difference between the mechanisms of genotoxic and non-genotoxic carcinogens could provide the foundation for a mechanism-based classification for unknown compounds. In this study, we investigated the gene expression of HepG2 cells treated with genotoxic or non-genotoxic carcinogens and compared their mechanisms of action. To enhance our understanding of the differences in the mechanisms of genotoxic and non-genotoxic carcinogens, we implemented a gene set analysis using 12 compounds for the training set (12, 24, 48 h) and validated significant gene sets using 22 compounds for the test set (24, 48 h). For a direct biological translation, we conducted a gene set analysis using Globaltest and selected significant gene sets. To validate the results, training and test compounds were predicted by the significant gene sets using a prediction analysis for microarrays (PAM). Finally, we obtained 6 gene sets, including sets enriched for genes involved in the adherens junction, bladder cancer, p53 signaling pathway, pathways in cancer, peroxisome and RNA degradation. Among the 6 gene sets, the bladder cancer and p53 signaling pathway sets were significant at 12, 24 and 48 h. We also found that the DDB2, RRM2B and GADD45A, genes related to the repair and damage prevention of DNA, were consistently up-regulated for genotoxic carcinogens. Our results suggest that a gene set analysis could provide a robust tool in the investigation of the different mechanisms of genotoxic and non-genotoxic carcinogens and construct a more detailed understanding of the perturbation of significant pathways.

p53-Dependent and cell specific epigenetic regulation of the polo-like kinases under oxidative stress

The polo-like kinase (PLKs) family, consisting of five known members, are key regulators of important cell cycle processes, which include mitotic entry, centrosome duplication, spindle assembly, and cytokinesis. The PLKs have been implicated in a variety of cancers, such as hepatocellular carcinoma (HCC), with PLK1 typically overexpressed and PLKs 2-5 often downregulated. Altered expression of the PLKs in malignancy is often correlated with aberrant promoter methylation. Epigenetic marks are dynamic and can be modified in response to external environmental stimuli. The aim of our study was to determine if oxidative stress, a common feature of solid tumours, would induce changes to the promoter methylation of the PLKs resulting in changes in expression. We examined the promoter methylation status via MSP and subsequent expression levels of the PLK family members under exposure to hypoxic conditions or reactive oxygen species (ROS). Interestingly, murine embryonic fibroblasts exposed to hypoxia and ROS displayed significant hypermethylation of Plk1 and Plk4 promoter regions post treatment. Corresponding proteins were also depleted by 40% after treatment. We also examined the HCC-derived cell lines HepG2 and Hep3B and found that for PLK1 and PLK4, the increase in hypermethylation was correlated with the presence of functional p53. In p53 wild-type cells, HepG2, both PLK1 and PLK4 were repressed with treatment, while in the p53 null cell line, Hep3B, PLK4 protein was elevated in the presence of hypoxia and ROS. This was also the case for ROS-treated, p53 null, osteosarcoma cells, Saos-2, where the PLK4 promoter became hypomethylated and protein levels were elevated. Our data supports a model in which the PLKs are susceptible to epigenetic changes induced by microenvironmental cues and these modifications may be p53-dependent. This has important implications in HCC and other cancers, where epigenetic alterations of the PLKs could contribute to tumourigenesis and disease progression.