Comparison of the expression profiles induced by genotoxic and nongenotoxic carcinogens in rat liver

Review and meta-analysis of gene expression biomarkers predictive of chemical-induced genotoxicity in vivo

There is growing recognition across broad sectors of the toxicology community that gene expression biomarkers have the potential to identify genotoxic and nongenotoxic carcinogens through a weight-of-evidence approach, providing opportunities to reduce reliance on the 2-year bioassay to identify carcinogens. In August 2022, a workshop within the International Workshops on Genotoxicity Testing (IWGT) was held to critically review current methods to identify genotoxicants using various 'omics profiling methods. Here, we describe the findings of a workshop subgroup focused on the state of the science regarding the use of biomarkers to identify chemicals that act as genotoxicants in vivo. A total of 1341 papers were screened to identify those that were most relevant. While six published biomarkers with characterized accuracy were initially examined, four of the six were not considered further, because they had not been tested for classification accuracy using additional sets of chemicals or other transcript profiling platforms. Two independently derived biomarkers used in conjunction with standard computational techniques can identify genotoxic chemicals in vivo (rat liver or both rat and mouse liver) on different gene expression profiling platforms. The biomarkers have predictive accuracies of ≥92%. These biomarkers have the potential to be used in conjunction with other biomarkers in integrated test strategies using short-term rodent exposures to identify genotoxic and nongenotoxic chemicals that cause cancer.

Consensus findings of an International Workshops on Genotoxicity Testing workshop on using transcriptomic biomarkers to predict genotoxicity

Gene expression biomarkers have the potential to identify genotoxic and non-genotoxic carcinogens, providing opportunities for integrated testing and reducing animal use. In August 2022, an International Workshops on Genotoxicity Testing (IWGT) workshop was held to critically review current methods to identify genotoxicants using transcriptomic profiling. Here, we summarize the findings of the workgroup on the state of the science regarding the use of transcriptomic biomarkers to identify genotoxic chemicals in vitro and in vivo. A total of 1341 papers were examined to identify the biomarkers that show the most promise for identifying genotoxicants. This analysis revealed two independently derived in vivo biomarkers and three in vitro biomarkers that, when used in conjunction with standard computational techniques, can identify genotoxic chemicals in vivo (rat or mouse liver) or in human cells in culture using different gene expression profiling platforms, with predictive accuracies of ≥92%. These biomarkers have been validated to differing degrees but typically show high reproducibility across transcriptomic platforms and model systems. They offer several advantages for applications in different contexts of use in genotoxicity testing including: early signal detection, moderate-to-high-throughput screening capacity, adaptability to different cell types and tissues, and insights on mechanistic information on DNA-damage response. Workshop participants agreed on consensus statements to advance the regulatory adoption of transcriptomic biomarkers for genotoxicity. The participants agreed that transcriptomic biomarkers have the potential to be used in conjunction with other biomarkers in integrated test strategies in vitro and using short-term rodent exposures to identify genotoxic and non-genotoxic chemicals that may cause cancer and heritable genetic effects. Following are the consensus statements from the workgroup. Transcriptomic biomarkers for genotoxicity can be used in Weight of Evidence (WoE) evaluation to: determine potential genotoxic mechanisms and hazards; identify misleading positives from in vitro genotoxicity assays; serve as new approach methodologies (NAMs) integrated into the standard battery of genotoxicity tests. Several transcriptomic biomarkers have been developed from sufficiently robust training data sets, validated with external test sets, and have demonstrated performance in multiple laboratories. These transcriptomic biomarkers can be used following established study designs and models designated through existing validation exercises in WoE evaluation. Bridging studies using a selection of training and test chemicals are needed to deviate from the established protocols to confirm performance when a transcriptomic biomarker is being applied in other: tissues, cell models, or gene expression platforms. Top dose selection and time of gene expression analysis are critical and should be established during transcriptomic biomarker development. These conditions are the only ones suited for transcriptomic biomarker use unless additional bridging or pharmacokinetic studies are conducted. Temporal effects for genotoxicants that operate via distinct mechanisms should be considered in data interpretation. Fixed transcriptomic biomarker gene sets and analytical processes do not need to be independently rederived in biomarker validation. Validation should focus on the performance of the gene set in external test sets. Robust external testing should ensure a minimum of additional chemicals spanning genotoxic and non-genotoxic modes of action. Genes in the transcriptomic biomarker do not need to be known to be mechanistically involved in genotoxicity responses. Existing frameworks described for NAMs could be applied for validation of transcriptomic biomarkers. Reproducibility of bioinformatic analysis is critical for the regulatory application of transcriptomic biomarkers. A bioinformatics expert should be involved with creating reproducible methods for the qualification and application of each transcriptomic biomarker.

New approach methodologies to facilitate and improve the hazard assessment of non-genotoxic carcinogens-a PARC project

Carcinogenic chemicals, or their metabolites, can be classified as genotoxic or non-genotoxic carcinogens (NGTxCs). Genotoxic compounds induce DNA damage, which can be detected by an established in vitro and in vivo battery of genotoxicity assays. For NGTxCs, DNA is not the primary target, and the possible modes of action (MoA) of NGTxCs are much more diverse than those of genotoxic compounds, and there is no specific in vitro assay for detecting NGTxCs. Therefore, the evaluation of the carcinogenic potential is still dependent on long-term studies in rodents. This 2-year bioassay, mainly applied for testing agrochemicals and pharmaceuticals, is time-consuming, costly and requires very high numbers of animals. More importantly, its relevance for human risk assessment is questionable due to the limited predictivity for human cancer risk, especially with regard to NGTxCs. Thus, there is an urgent need for a transition to new approach methodologies (NAMs), integrating human-relevant in vitro assays and in silico tools that better exploit the current knowledge of the multiple processes involved in carcinogenesis into a modern safety assessment toolbox. Here, we describe an integrative project that aims to use a variety of novel approaches to detect the carcinogenic potential of NGTxCs based on different mechanisms and pathways involved in carcinogenesis. The aim of this project is to contribute suitable assays for the safety assessment toolbox for an efficient and improved, internationally recognized hazard assessment of NGTxCs, and ultimately to contribute to reliable mechanism-based next-generation risk assessment for chemical carcinogens.

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.

StemPanTox: A fast and wide-target drug assessment system for tailor-made safety evaluations using personalized iPS cells

An alternative model that reliably predicts human-specific toxicity is necessary because the translatability of effects on animal models for human disease is limited to context. Previously, we developed a method that accurately predicts developmental toxicity based on the gene networks of undifferentiated human embryonic stem (ES) cells. Here, we advanced this method to predict adult toxicities of 24 chemicals in six categories (neurotoxins, cardiotoxins, hepatotoxins, two types of nephrotoxins, and non-genotoxic carcinogens) and achieved high predictability (AUC = 0.90-1.00) in all categories. Moreover, we screened for an induced pluripotent stem (iPS) cell line to predict the toxicities based on the gene networks of iPS cells using transfer learning of the gene networks of ES cells, and predicted toxicities in four categories (neurotoxins, hepatotoxins, glomerular nephrotoxins, and non-genotoxic carcinogens) with high performance (AUC = 0.82-0.99). This method holds promise for tailor-made safety evaluations using personalized iPS cells.

Evaluation of Growth Performance, Nitrogen Balance and Blood Metabolites of Mutton Sheep Fed an Ammonia-Treated Aflatoxin B1-Contaminated Diet

Experiments were conducted to evaluate the effects of an aflatoxin B1 (AFB1)-contaminated diet treated with ammonia on the diet detoxification and growth performance, nutrient digestibility, nitrogen utilization, and blood metabolites in sheep. Twenty-four female mutton sheep with an initial body weight of 50 ± 2.5 kg were randomly assigned to one of three groups: (1) control diet (C); (2) aflatoxin diet (T; control diet supplemented with 75 μg of AFB1/kg of dry matter); and (3) ammoniated diet (AT; ammoniated aflatoxin diet). The results showed decreases (p < 0.05) in average daily feed intake, nutrient digestibility of dry matter, crude protein and ether extract, and retained nitrogen, and an increase (p < 0.05) in urine nitrogen excretion in sheep fed diet T compared with those fed the other diets. In comparison to C and AT, feeding T decreased (p < 0.05) the concentrations of total protein, immunoglobulin A, immunoglobulin G, immunoglobulin M, superoxide dismutase, and total antioxidants and increased (p < 0.05) the concentrations of alanine amino transferase, malondialdehyde, and interleukin-6. In summary, ammonia treatment has the potential to decrease the concentration of AFB1 and alleviate the adverse effects of AFB1.

Comparative Analysis of Transcriptional Responses to Genotoxic and Non-Genotoxic Agents in the Blood Cell Model TK6 and the Liver Model HepaRG

Transcript signatures are a promising approach to identify and classify genotoxic and non-genotoxic compounds and are of interest as biomarkers or for future regulatory application. Not much data, however, is yet available about the concordance of transcriptional responses in different cell types or tissues. Here, we analyzed transcriptomic responses to selected genotoxic food contaminants in the human p53-competent lymphoblastoid cell line TK6 using RNA sequencing. Responses to treatment with five genotoxins, as well as with four non-genotoxic liver toxicants, were compared with previously published gene expression data from the human liver cell model HepaRG. A significant overlap of the transcriptomic changes upon genotoxic stress was detectable in TK6 cells, whereas the comparison with the HepaRG model revealed considerable differences, which was confirmed by bioinformatic data mining for cellular upstream regulators or pathways. Taken together, the study presents a transcriptomic signature for genotoxin exposure in the human TK6 blood cell model. The data demonstrate that responses in different cell models have considerable variations. Detection of a transcriptomic genotoxin signature in blood cells indicates that gene expression analyses of blood samples might be a valuable approach to also estimate responses to toxic exposure in target organs such as the liver.

Genotoxic Effects of Cylindrospermopsin, Microcystin-LR and Their Binary Mixture in Human Hepatocellular Carcinoma (HepG2) Cell Line

Simultaneous occurrence of cylindrospermopsin (CYN) and microcystin-LR (MCLR) has been reported in the aquatic environment and thus human exposure to such mixtures is possible. As data on the combined effects of CYN/MCLR are scarce, we aimed to investigate the adverse effects related to genotoxic activities induced by CYN (0.125, 0.25 and 0.5 µg/mL) and MCLR (1 µg/mL) as single compounds and their combinations in HepG2 cells after 24 and 72 h exposure. CYN and CYN/MCLR induced DNA double-strand breaks after 72 h exposure, while cell cycle analysis revealed that CYN and CYN/MCLR arrested HepG2 cells in G0/G1 phase. Moreover, CYN and the combination with MCLR upregulated CYP1A1 and target genes involved in DNA-damage response (CDKN1A, GADD45A). Altogether, the results showed that after 72 h exposure genotoxic activity of CYN/MCLR mixture was comparable to the one of pure CYN. On the contrary, MCLR (1 µg/mL) had no effect on the viability of cells and had no influence on cell division. It did not induce DNA damage and did not deregulate studied genes after prolonged exposure. The outcomes of the study confirm the importance of investigating the combined effects of several toxins as the effects can differ from those induced by single compounds.

Application of transcriptomic and microRNA profiling in the evaluation of potential liver carcinogens

Hepatocarcinogens are agents that increase the incidence of liver cancer in exposed animals or humans. It is now established that carcinogenic exposures have a widespread impact on the transcriptome, inducing both adaptive and adverse changes in the activities of genes and pathways. Chemical hepatocarcinogens have also been shown to affect expression of microRNA (miRNA), the evolutionarily conserved noncoding RNA that regulates gene expression posttranscriptionally. Considerable effort has been invested into examining the involvement of mRNA in chemical hepatocarcinogenesis and their potential usage for the classification and prediction of new chemical entities. For miRNA, there has been an increasing number of studies reported over the past decade, although not to the same degree as for transcriptomic studies. Current data suggest that it is unlikely that any gene or miRNA signature associated with short-term carcinogen exposure can replace the rodent bioassay. In this review, we discuss the application of transcriptomic and miRNA profiles to increase mechanistic understanding of chemical carcinogens and to aid in their classification.

Piperonyl butoxide: Mode of action analysis for mouse liver tumour formation and human relevance

In a 79 week bioassay the pesticide synergist piperonyl butoxide (PBO) was shown to significantly increase the incidence of hepatocellular adenoma (but not hepatocellular carcinoma) in male CD-1 mice at dietary levels of 100 and 300 mg/kg/day PBO and in female mice at a dietary level of 300 mg/kg/day. As PBO is not a genotoxic agent, a series of investigative studies were undertaken to elucidate the mode of action (MOA) for PBO-induced mouse liver tumour formation. Male CD-1 mice were fed diets to provide intakes of 0 (control), 30, 100 and 300 mg/kg/day PBO and for purposes of comparison 500 ppm sodium phenobarbital (NaPB), a known constitutive androstane receptor (CAR) activator, for 7 and 14 days. Treatment with 100 and 300 mg/kg/day PBO and 500 ppm NaPB increased relative liver weight which was associated with hepatocyte hypertrophy, with hepatocyte replicative DNA synthesis (RDS) being increased after 7 days treatment. The treatment of CD-1 mice with 30-300 mg/kg/day PBO for 14 days resulted in significant dose-dependent increases in hepatic microsomal cytochrome P450 (CYP) content and 7-pentoxyresorufin O-depentylase (PROD) activity and in hepatic Cyp2b10 mRNA levels. In contrast, PBO produced a biphasic effect on markers of activation of the peroxisome proliferator-activated receptor alpha (PPARα), with small increases in microsomal lauric acid 12-hydroxylase activity and hepatic Cyp4a10 mRNA levels being observed in mice given 100 mg/kg/day with PBO, with either no increase or a significant inhibition being observed in mice given 300 mg/kg/day PBO. The hepatic effects of PBO in male CD-1 mice were generally similar to those produced by NaPB and were reversible after the cessation of treatment for 28 days. Studies were also performed in male C57BL/6J (wild type) mice and in hepatic CAR and pregnane X receptor (PXR) knockout mice (CAR KO/PXR KO mice), where in the CAR KO/PXR KO mice PBO had little effect on markers of CAR activation, but produced some increases in markers of PPARα activation. The treatment of male CD-1 mouse hepatocytes for 4 days with 5-50 μM PBO, 10-1000 μM NaPB and 25 ng/mL epidermal growth factor (EGF) resulted in significant increases in hepatocyte RDS. While treatment of hepatocytes from one male and one female human donor with 5-500 μM PBO and 10-1000 μM NaPB for 4 days had no effect on hepatocyte RDS, treatment with EGF resulted in significant increases in RDS in both human hepatocyte preparations. In summary, PBO is predominantly a hepatic CAR activator at carcinogenic dose levels in CD-1 mice, with activation of hepatic CAR resulting in a suppression of the effect of PBO on hepatic PPARα. A robust MOA for PBO-induced mouse liver tumour formation has been established, this MOA being similar to that previously identified for NaPB and some other rodent liver CAR activators. Based on the lack of effect of PBO on RDS in human hepatocytes, it is considered that the MOA for PBO-induced mouse liver tumour formation is qualitatively not plausible for humans.

The genome of the marine rotifer Brachionus koreanus sheds light on the antioxidative defense system in response to 2-ethyl-phenanthrene and piperonyl butoxide

BRACHIONUS: spp. (Rotifera: Monogononta) have been introduced as ecotoxicological model-organisms that are widely distributed in aquatic environments. Among the Brachionus spp., the monogonont rotifer Brachionus koreanus has been widely used for ecology, ecotoxicology, and evolution, thus, providing the whole genome data of B. koreanus is important for further understandings of in-depth molecular mechanisms. In this study, the completed assembly and characterization of the B. koreanus genome resulted in a total length of 85.7 Mb with 14,975 annotated genes. The final number of scaffolds was 567 with an N50 value and a GC content of 1.86 Mb and 24.35 %, respectively. Based on the fully constructed genome database, a total of 24 CYPs, 23 GSTs, two SODs, and a single CAT genes were identified and analyzed antioxidant activities (CAT, SOD, and GST), and transcriptional regulation of the entire CYPs, GSTs, SODs, and CAT in response to 2-ethyl-phenanthrene (2-ethyl-PHE) and piperonyl butoxide (PBO), to demonstrate the usefulness of the whole genome library of B. koreanus in response xenobiotic-induced oxidative stress. The assembled B. koreanus genome will provide a better understanding on the molecular ecotoxicology in the view of molecular mechanisms underlying toxicological responses, particularly on xenobiotic detoxification processes in the rotifer B. koreanus.

Plastics in Cyanobacterial Blooms-Genotoxic Effects of Binary Mixtures of Cylindrospermopsin and Bisphenols in HepG2 Cells

Ever-expanding environmental pollution is causing a rise in cyanobacterial blooms and the accumulation of plastics in water bodies. Consequently, exposure to mixtures of cyanotoxins and plastic-related contaminants such as bisphenols (BPs) is of increasing concern. The present study describes genotoxic effects induced by co-exposure to one of the emerging cyanotoxins-cylindrospermopsin (CYN)-(0.5 µg/mL) and BPs (bisphenol A (BPA), S (BPS), and F (BPF); (10 µg/mL)) in HepG2 cells after 24 and 72 h of exposure. The cytotoxicity was evaluated with an MTS assay and genotoxicity was assessed through the measurement of the induction of DNA double strand breaks (DSB) with the γH2AX assay. The deregulation of selected genes (xenobiotic metabolic enzyme genes, DNA damage, and oxidative response genes) was assessed using qPCR. The results showed a moderate reduction of cell viability and induction of DSBs after 72 h of exposure to the CYN/BPs mixtures and CYN alone. None of the BPs alone reduced cell viability or induced DSBs. No significant difference was observed between CYN and CYN/BPs exposed cells, except with CYN/BPA, where the antagonistic activity of BPA against CYN was indicated. The deregulation of some of the tested genes (CYP1A1, CDKN1A, GADD45A, and GCLC) was more pronounced after exposure to the CYN/BPs mixtures compared to single compounds, suggesting additive or synergistic action. The present study confirms the importance of co-exposure studies, as our results show pollutant mixtures to induce effects different from those confirmed for single compounds.

RNA-protein correlation of liver toxicity markers in HepaRG cells

The liver is a main target organ for the toxicity of many different compounds. While in general, in vivo testing is still routinely used for assessing the hepatotoxic potential of test chemicals, the use of in vitro models offers advantages with regard to throughput, consumption of resources, and animal welfare aspects. Using the human hepatoma cell line HepaRG, we performed a comparative evaluation of a panel of hepatotoxicity marker mRNAs and proteins after exposure of the cells to 30 different pesticidal active compounds comprising herbizides, fungicides, insecticides, and others. The panel of hepatotoxicity markers included nuclear receptor target genes, key players of fatty acid and bile acid metabolism-related pathways, as well as recently identified biomarkers of drug-induced liver injury. Moreover, marker genes and proteins were identified, for example, S100P, ANXA10, CYP1A1, and CYP7A1. These markers respond with high sensitivity to stimulation with chemically diverse test compounds already at non-cytotoxic concentrations. The potency of the test compounds, determined as an overall parameter of their ability to deregulate marker expression in vitro, was very similar between the mRNA and protein levels. Thus, this study does not only characterize the response of human liver cells to 30 different pesticides but also demonstrates that hepatotoxicity testing in human HepaRG cells yields well comparable results at the mRNA and protein levels. Furthermore, robust hepatotoxicity marker genes and proteins were identified in HepaRG cells.

Expression profiling of key pathways in rat liver after a one-year feeding trial with transgenic maize MON810

In a recent one-year feeding study, we observed no adverse effects on tissue level in organs of rats fed with the genetically-modified maize MON810. Here, we assessed RNA expression levels of 86 key genes of the apoptosis-, NF-кB-, DNA-damage response (DDR)-, and unfolded-protein response (UPR) pathways by RT-qPCR in the rat liver. Male and female rats were fed either with 33% MON810 (GMO), isogenic- (ISO), or conventional maize (CONV) and RNAs were quantified from eight rats from each of the six feeding groups. Only Birc2 transcript showed a significant (p ≤ 0.05) consistent difference of ≥1.5-fold between the GMO and ISO groups in both sexes. Unsupervised cluster analysis showed a strong separation of male and female rats, but no clustering of the feeding groups. Individual analysis of the pathways did not show any clustering of the male or female feeding groups either, though transcript levels of UPR pathway-associated genes caused some clustering of the male GMO and CONV feeding group samples. These differences were not seen between the GMO and ISO control or within the female cohort. Our data therefore does not support an adverse effect on rat liver RNA expression through the long-term feeding of MON810 compared to isogenic control maize.

Genotoxic activity of bisphenol A and its analogues bisphenol S, bisphenol F and bisphenol AF and their mixtures in human hepatocellular carcinoma (HepG2) cells

The use of bisphenol A (BPA) in manufacturing of plastics is being gradually replaced by presumably safer analogues such as bisphenol S (BPS), bisphenol F (BPF) and bisphenol AF (BPAF). Despite their widespread occurrence in the environment, there is a knowledge gap in their toxicological profiles. We investigated cytotoxic/genotoxic effects as well as changes in the expression of selected genes involved in the xenobiotic metabolism, response to oxidative stress and DNA damage upon exposure to BPs and their mixtures in human hepatocellular carcinoma HepG2 cells. BPS and BPF slightly decreased the viability of HepG2 cells, while BPAF was the most cytotoxic compound tested. BPA, BPF and BPAF induced the formation of DNA double strand breaks determined with γH2AX assay, while BPS was inactive (5-20 μg/mL). All four BPs up-regulated the expression of CYP1A1 and UGT1A1, while BPS up-regulated and BPAF down-regulated also the expression of GST1A. Only BPA up-regulated oxidative stress responsive gene GCLC, while BPAF up-regulated the expression of CDKN1A and GADD45a. At concentrations relevant for human exposure (ng/mL range) BPA and its analogues as individual compounds and in mixtures did not exert genotoxic activity, whereas BPA and BPAF as well as the mixtures up-regulated the expressions of CYP1A1 and UGT1A1.

The effect of insecticide synergist treatment on genome-wide gene expression in a polyphagous pest

Synergists can counteract metabolic insecticide resistance by inhibiting detoxification enzymes or transporters. They are used in commercial formulations of insecticides, but are also frequently used in the elucidation of resistance mechanisms. However, the effect of synergists on genome-wide transcription in arthropods is poorly understood. In this study we used Illumina RNA-sequencing to investigate genome-wide transcriptional responses in an acaricide resistant strain of the spider mite Tetranychus urticae upon exposure to synergists such as S,S,S-tributyl phosphorotrithioate (DEF), diethyl maleate (DEM), piperonyl butoxide (PBO) and cyclosporin A (CsA). Exposure to PBO and DEF resulted in a broad transcriptional response and about one third of the differentially expressed genes (DEGs), including cytochrome P450 monooxygenases and UDP-glycosyltransferases, was shared between both treatments, suggesting common transcriptional regulation. Moreover, both DEF and PBO induced genes that are strongly implicated in acaricide resistance in the respective strain. In contrast, CsA treatment mainly resulted in downregulation of Major Facilitator Superfamily (MFS) genes, while DEGs of the DEM treatment were not significantly enriched for any GO-terms.

Identification of essential transcription factors for adequate DNA damage response after benzo(a)pyrene and aflatoxin B1 exposure by combining transcriptomics with functional genomics

DNA damage mediates widespread changes in transcription through activation or repression of transcription factors (TFs). However, the consequences of regulating specific TFs for the outcome of the DNA repair process remain incompletely understood. Here, we combined transcriptomics and TF binding prediction with functional genomics to identify TFs essential for adequate DNA repair in HepG2 liver cells after a non-cytotoxic dose of carcinogens benzo(a)pyrene (BaP) (2μM) and aflatoxin B1 (AFB1) (5μM). BaP and AFB1 induced a largely common transcriptional response, mediated by similar TFs. A lentiviral shRNA screen knocking down the top31 identified TFs, was performed to determine their effect on DNA repair by assessing phosphorylation of H2AX (γ-H2AX). In addition to the top candidate p53, we identified several other interesting TFs that modulated γ-H2AX after BaP and AFB1 treatment. Validation studies confirmed the role of p53 in reducing γ-H2AX formation and DNA breaks measured by COMET assay after BaP and AFB1 exposure. Expression of the cell cycle inhibitor p21 was profoundly impaired upon p53 knock-down. In addition, the expression of 2 genes involved in nucleotide exchange repair, DDB2 and XPC was significantly reduced in p53 knock-down cells. Although p63 knock-down affected DNA damage upon BaP treatment this was not associated with altered expression of DDB2 or XPC. Finally, knock-down of ARNT reduced γ-H2AX in response to BaP, which was associated with reduced CYP1A1 expression. Importantly, our results suggest a new role for ARNT and its dimerization partner AHR in the occurrence of H2AX phosphorylation after AFB1 treatment. These data show that modulation of TF activity impacts on the repair of BaP- and AFB1-induced DNA damage. Our study also demonstrates the potential of combining functional genomics with genome-wide expression analysis to identify yet unknown causal relationships, thereby aiding in the interpretation of complex biological systems.

Stem cell proliferation patterns as an alternative for in vivo prediction and discrimination of carcinogenic compounds

One of the major challenges in the development of alternative carcinogenicity assays is the prediction of non-genotoxic carcinogens. The variety of non-genotoxic cancer pathways complicates the search for reliable parameters expressing their carcinogenicity. As non-genotoxic and genotoxic carcinogens have different cancer risks, the objective of this study was to develop a concept for an in vivo test, based on flatworm stem cell dynamics, to detect and classify carcinogenic compounds. Our methodology entails an exposure to carcinogenic compounds during the animal's regeneration process, which revealed differences in proliferative responses between non-genotoxic and genotoxic carcinogens during the initial stages of the regeneration process. A proof of concept was obtained after an extensive study of proliferation dynamics of a genotoxic and a non-genotoxic compound. A pilot validation with a limited set of compounds showed that the proposed concept not only enabled a simple prediction of genotoxic and non-genotoxic carcinogens, but also had the power to discriminate between both. We further optimized this discrimination by combining stem cell proliferation responses with a phenotypic screening and by using specific knockdowns. In the future, more compounds will be tested to further validate and prove this concept.

Time-matched analysis of DNA adduct formation and early gene expression as predictive tool for renal carcinogenesis in methylazoxymethanol acetate treated Eker rats

Genotoxic carcinogens pose great hazard to human health. Uncertainty of current risk assessment strategies and long latency periods between first carcinogen exposure and diagnosis of tumors have raised interest in predictive biomarkers. Initial DNA adduct formation is a necessary step for genotoxin induced carcinogenesis. However, as DNA adducts not always translate into tumorigenesis, their predictive value is limited. Here we hypothesize that the combined analysis of pro-mutagenic DNA adducts along with time-matched gene expression changes could serve as a superior prediction tool for genotoxic carcinogenesis. Eker rats, heterozygous for the tuberous sclerosis (Tsc2) tumor suppressor gene and thus highly susceptible towards genotoxic renal carcinogens, were continuously treated with the DNA alkylating carcinogen methylazoxymethanol acetate (MAMAc). Two weeks of MAMAc treatment resulted in a time-dependent increase of O⁶-methylguanine and N7-methylguanine adducts in the kidney cortex, which was however not reflected by significant expression changes of cyto-protective genes involved in DNA repair, cell cycle arrest or apoptosis. Instead, we found a transcriptional regulation of genes involved in the tumor-related MAPK, FoxO and TGF-beta pathways. Continuous MAMAc treatment for up to 6 months resulted in a mild but significant increase of cancerous lesions. In summary, the combined analysis of DNA adducts and early gene expression changes could serve as a suitable predictive tool for genotoxicant-induced carcinogenesis.

Use of early phenotypic in vivo markers to assess human relevance of an unusual rodent non-genotoxic carcinogen in vitro

Foci of altered hepatocytes (FAH) are considered putative, pre-neoplastic lesions that can occur spontaneously in aging rodents, but can also be induced by chemicals or drugs. Progression of FAH to hepatocellular neoplasms has been reported repeatedly but increases in foci in rodents do not necessarily lead to tumors in carcinogenicity studies and the relevance for humans often remains unclear. Here we present the case of RG3487, a molecule which induced FAH and, later on, tumors in rats. Because the molecule was negative in genotoxicity assays it was classified as a non-genotoxic carcinogen. In order to assess the potential for liver tumor formation in humans, we analyzed treatment-induced changes in vivo to establish a possible mode of action (MoA). In vivo and in vitro gene expression analysis revealed that nuclear receptor signaling was unlikely to be the relevant MoA and no other known mechanism could be established. We therefore took an approach comparing phenotypic markers, including mRNA changes, proliferation and glycogen accumulation, in vitro using cells of different species to assess the human relevance of this finding. Since the alterations observed in rats were not seen in the liver of mice or dogs in vivo, we could validate the relevance of the cell models chosen by use of hepatocytes from these species in vitro. This ultimately allowed for a cross-species comparison, which suggested that the formation of FAH and liver tumors was rat specific and unlikely to translate to human. Our work showed that phenotypic species comparison in vitro is a useful approach for assessment of the human relevance of pre-clinical findings where no known mechanism can be established.

Gene Expression Profiles in Rat Liver Slices Exposed to Hepatocarcinogenic Enzyme Inducers, Peroxisome Proliferators, and 17α-Ethinylestradiol

Transcription profiling is used as an in vivo method for predicting the mode-of-action class of nongenotoxic carcinogens. To set up a reliable in vitro short-term test system DNA microarray technology was combined with rat liver slices. Seven compounds known to act as tumor promoters were selected, which included the enzyme inducers phenobarbital, α-hexachlorocyclohexane, and cyproterone acetate; the peroxisome proliferators WY-14,643, dehydroepiandrosterone, and ciprofibrate; and the hormone 17 α-ethinylestradiol. Rat liver slices were exposed to various concentrations of the compounds for 24 h. Toxicology-focused TOXaminer™ DNA microarrays containing approximately 1500 genes were used for generating gene expression profiles for each of the test compound. Hierarchical cluster analysis revealed that (i) gene expression profiles generated in rat liver slices in vitro were specific allowing classification of compounds with similar mode of action and (ii) expression profiles of rat liver slices exposed in vitro correlate with those induced after in vivo treatment (reported previously). Enzyme inducers and peroxisome proliferators formed two separate clusters, confirming that they act through different mechanisms. Expression profiles of the hormone 17 α-ethinylestradiol were not similar to any of the other compounds. In conclusion, gene expression profiles induced by compounds that act via similar mechanisms showed common effects on transcription upon treatment in vivo and in rat liver slices in vitro.

Critical role of toxicologic pathology in a short-term screen for carcinogenicity

Carcinogenic potential of chemicals is currently evaluated using a two year bioassay in rodents. Numerous difficulties are known for this assay, most notably, the lack of information regarding detailed dose response and human relevance of any positive findings. A screen for carcinogenic activity has been proposed based on a 90 day screening assay. Chemicals are first evaluated for proliferative activity in various tissues. If negative, lack of carcinogenic activity can be concluded. If positive, additional evaluation for DNA reactivity, immunosuppression, and estrogenic activity are evaluated. If these are negative, additional efforts are made to determine specific modes of action in the animal model, with a detailed evaluation of the potential relevance to humans. Applications of this approach are presented for liver and urinary bladder. Toxicologic pathology is critical for all of these evaluations, including a detailed histopathologic evaluation of the 90 day assay, immunohistochemical analyses for labeling index, and involvement in a detailed mode of action analysis. Additionally, the toxicologic pathologist needs to be involved with molecular evaluations and evaluations of new molecularly developed animal models. The toxicologic pathologist is uniquely qualified to provide the expertise needed for these evaluations.

Influence of selected anti-cancer drugs on the induction of DNA double-strand breaks and changes in gene expression in human hepatoma HepG2 cells

In chemotherapy, various anti-cancer drugs with different mechanisms of action are used and may represent different risk of undesirable delayed side effects in treated patients as well as in occupationally exposed populations. The aim of the present study was to evaluate genotoxic potential of four widely used anti-cancer drugs with different mechanisms of action: 5-fluorouracil (5-FU), cisplatin (CDDP) and etoposide (ET) that cause cell death by targeting DNA function and imatinib mesylate (IM) that inhibits targeted protein kinases in cancer cells in an experimental model with human hepatoma HepG2 cells. After 24 h of exposure all four anti-cancer drugs at non-cytotoxic concentrations induced significant increase in formation of DNA double strand breaks (DSBs), with IM being the least effective. The analysis of the changes in the expression of genes involved in the response to DNA damage (CDKN1A, GADD45A, MDM2), apoptosis (BAX, BCL2) and oncogenesis (MYC, JUN) showed that 5-FU, CDDP and ET upregulated the genes involved in DNA damage response, while the anti-apoptotic gene BCL2 and oncogene MYC were downregulated. On the contrary, IM did not change the mRNA level of the studied genes, showing different mechanism of action that probably does not involve direct interaction with DNA processing. Genotoxic effects of the tested anti-cancer drugs were observed at their therapeutic concentrations that may consequently lead to increased risk for development of delayed adverse effects in patients. In addition, considering the genotoxic mechanism of action of 5-FU, CDDP and ET an increased risk can also not be excluded in occupationally exposed populations. The results also indicate that exposure to 5-FU, CDDP and ET represent a higher risk for delayed effects such as cancer, reproductive effects and heritable disease than exposure to IM.

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.

Exploiting microRNA and mRNA profiles generated in vitro from carcinogen-exposed primary mouse hepatocytes for predicting in vivo genotoxicity and carcinogenicity

The well-defined battery of in vitro systems applied within chemical cancer risk assessment is often characterised by a high false-positive rate, thus repeatedly failing to correctly predict the in vivo genotoxic and carcinogenic properties of test compounds. Toxicogenomics, i.e. mRNA-profiling, has been proven successful in improving the prediction of genotoxicity in vivo and the understanding of underlying mechanisms. Recently, microRNAs have been discovered as post-transcriptional regulators of mRNAs. It is thus hypothesised that using microRNA response-patterns may further improve current prediction methods. This study aimed at predicting genotoxicity and non-genotoxic carcinogenicity in vivo, by comparing microRNA- and mRNA-based profiles, using a frequently applied in vitro liver model and exposing this to a range of well-chosen prototypical carcinogens. Primary mouse hepatocytes (PMH) were treated for 24 and 48h with 21 chemical compounds [genotoxins (GTX) vs. non-genotoxins (NGTX) and non-genotoxic carcinogens (NGTX-C) versus non-carcinogens (NC)]. MicroRNA and mRNA expression changes were analysed by means of Exiqon and Affymetrix microarray-platforms, respectively. Classification was performed by using Prediction Analysis for Microarrays (PAM). Compounds were randomly assigned to training and validation sets (repeated 10 times). Before prediction analysis, pre-selection of microRNAs and mRNAs was performed by using a leave-one-out t-test. No microRNAs could be identified that accurately predicted genotoxicity or non-genotoxic carcinogenicity in vivo. However, mRNAs could be detected which appeared reliable in predicting genotoxicity in vivo after 24h (7 genes) and 48h (2 genes) of exposure (accuracy: 90% and 93%, sensitivity: 65% and 75%, specificity: 100% and 100%). Tributylinoxide and para-Cresidine were misclassified. Also, mRNAs were identified capable of classifying NGTX-C after 24h (5 genes) as well as after 48h (3 genes) of treatment (accuracy: 78% and 88%, sensitivity: 83% and 83%, specificity: 75% and 93%). Wy-14,643, phenobarbital and ampicillin trihydrate were misclassified. We conclude that genotoxicity and non-genotoxic carcinogenicity probably cannot be accurately predicted based on microRNA profiles. Overall, transcript-based prediction analyses appeared to clearly outperform microRNA-based analyses.

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.

Toxicology Strategies for Drug Discovery: Present and Future

Attrition due to nonclinical safety represents a major issue for the productivity of pharmaceutical research and development (R&D) organizations, especially during the compound optimization stages of drug discovery and the early stages of clinical development. Focusing on decreasing nonclinical safety-related attrition is not a new concept, and various approaches have been experimented with over the last two decades. Front-loading testing funnels in Discovery with in vitro toxicity assays designed to rapidly identify unfavorable molecules was the approach adopted by most pharmaceutical R&D organizations a few years ago. However, this approach has also a non-negligible opportunity cost. Hence, significant refinements to the "fail early, fail often" paradigm have been proposed recently to reflect the complexity of accurately categorizing compounds with early data points without taking into account other important contextual aspects, in particular efficacious systemic and tissue exposures. This review provides an overview of toxicology approaches and models that can be used in pharmaceutical Discovery at the series/lead identification and lead optimization stages to guide and inform chemistry efforts, as well as a personal view on how to best use them to meet nonclinical safety-related attrition objectives consistent with a sustainable pharmaceutical R&D model. The scope of this review is limited to small molecules, as large molecules are associated with challenges that are quite different. Finally, a perspective on how several emerging technologies may impact toxicity evaluation is also provided.

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.

Bayesian Network Inference Enables Unbiased Phenotypic Anchoring of Transcriptomic Responses to Cigarette Smoke in Humans

Microarray-based transcriptomic analysis has been demonstrated to hold the opportunity to study the effects of human exposure to, e.g., chemical carcinogens at the whole genome level, thus yielding broad-ranging molecular information on possible carcinogenic effects. Since genes do not operate individually but rather through concerted interactions, analyzing and visualizing networks of genes should provide important mechanistic information, especially upon connecting them to functional parameters, such as those derived from measurements of biomarkers for exposure and carcinogenic risk. Conventional methods such as hierarchical clustering and correlation analyses are frequently used to address these complex interactions but are limited as they do not provide directional causal dependence relationships. Therefore, our aim was to apply Bayesian network inference with the purpose of phenotypic anchoring of modified gene expressions. We investigated a use case on transcriptomic responses to cigarette smoking in humans, in association with plasma cotinine levels as biomarkers of exposure and aromatic DNA-adducts in blood cells as biomarkers of carcinogenic risk. Many of the genes that appear in the Bayesian networks surrounding plasma cotinine, and to a lesser extent around aromatic DNA-adducts, hold biologically relevant functions in inducing severe adverse effects of smoking. In conclusion, this study shows that Bayesian network inference enables unbiased phenotypic anchoring of transcriptomics responses. Furthermore, in all inferred Bayesian networks several dependencies are found which point to known but also to new relationships between the expression of specific genes, cigarette smoke exposure, DNA damaging-effects, and smoking-related diseases, in particular associated with apoptosis, DNA repair, and tumor suppression, as well as with autoimmunity.

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.

Development and application of the adverse outcome pathway framework for understanding and predicting chronic toxicity: I. Challenges and research needs in ecotoxicology

To elucidate the effects of chemicals on populations of different species in the environment, efficient testing and modeling approaches are needed that consider multiple stressors and allow reliable extrapolation of responses across species. An adverse outcome pathway (AOP) is a concept that provides a framework for organizing knowledge about the progression of toxicity events across scales of biological organization that lead to adverse outcomes relevant for risk assessment. In this paper, we focus on exploring how the AOP concept can be used to guide research aimed at improving both our understanding of chronic toxicity, including delayed toxicity as well as epigenetic and transgenerational effects of chemicals, and our ability to predict adverse outcomes. A better understanding of the influence of subtle toxicity on individual and population fitness would support a broader integration of sublethal endpoints into risk assessment frameworks. Detailed mechanistic knowledge would facilitate the development of alternative testing methods as well as help prioritize higher tier toxicity testing. We argue that targeted development of AOPs supports both of these aspects by promoting the elucidation of molecular mechanisms and their contribution to relevant toxicity outcomes across biological scales. We further discuss information requirements and challenges in application of AOPs for chemical- and site-specific risk assessment and for extrapolation across species. We provide recommendations for potential extension of the AOP framework to incorporate information on exposure, toxicokinetics and situation-specific ecological contexts, and discuss common interfaces that can be employed to couple AOPs with computational modeling approaches and with evolutionary life history theory. The extended AOP framework can serve as a venue for integration of knowledge derived from various sources, including empirical data as well as molecular, quantitative and evolutionary-based models describing species responses to toxicants. This will allow a more efficient application of AOP knowledge for quantitative chemical- and site-specific risk assessment as well as for extrapolation across species in the future.

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.

Cross-platform toxicogenomics for the prediction of non-genotoxic hepatocarcinogenesis in rat

In the area of omics profiling in toxicology, i.e. toxicogenomics, characteristic molecular profiles have previously been incorporated into prediction models for early assessment of a carcinogenic potential and mechanism-based classification of compounds. Traditionally, the biomarker signatures used for model construction were derived from individual high-throughput techniques, such as microarrays designed for monitoring global mRNA expression. In this study, we built predictive models by integrating omics data across complementary microarray platforms and introduced new concepts for modeling of pathway alterations and molecular interactions between multiple biological layers. We trained and evaluated diverse machine learning-based models, differing in the incorporated features and learning algorithms on a cross-omics dataset encompassing mRNA, miRNA, and protein expression profiles obtained from rat liver samples treated with a heterogeneous set of substances. Most of these compounds could be unambiguously classified as genotoxic carcinogens, non-genotoxic carcinogens, or non-hepatocarcinogens based on evidence from published studies. Since mixed characteristics were reported for the compounds Cyproterone acetate, Thioacetamide, and Wy-14643, we reclassified these compounds as either genotoxic or non-genotoxic carcinogens based on their molecular profiles. Evaluating our toxicogenomics models in a repeated external cross-validation procedure, we demonstrated that the prediction accuracy of our models could be increased by joining the biomarker signatures across multiple biological layers and by adding complex features derived from cross-platform integration of the omics data. Furthermore, we found that adding these features resulted in a better separation of the compound classes and a more confident reclassification of the three undefined compounds as non-genotoxic carcinogens.

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.

A metabolomics investigation of non-genotoxic carcinogenicity in the rat

Non-genotoxic carcinogens (NGCs) promote tumor growth by altering gene expression, which ultimately leads to cancer without directly causing a change in DNA sequence. As a result NGCs are not detected in mutagenesis assays. While there are proposed biomarkers of carcinogenic potential, the definitive identification of non-genotoxic carcinogens still rests with the rat and mouse long-term bioassay. Such assays are expensive and time-consuming and require a large number of animals, and their relevance to human health risk assessments is debatable. Metabolomics and lipidomics in combination with pathology and clinical chemistry were used to profile perturbations produced by 10 compounds that represented a range of rat non-genotoxic hepatocarcinogens (NGC), non-genotoxic non-hepatocarcinogens (non-NGC), and a genotoxic hepatocarcinogen. Each compound was administered at its maximum tolerated dose level for 7, 28, and 91 days to male Fisher 344 rats. Changes in liver metabolite concentration differentiated the treated groups across different time points. The most significant differences were driven by pharmacological mode of action, specifically by the peroxisome proliferator activated receptor alpha (PPAR-α) agonists. Despite these dominant effects, good predictions could be made when differentiating NGCs from non-NGCs. Predictive ability measured by leave one out cross validation was 87% and 77% after 28 days of dosing for NGCs and non-NGCs, respectively. Among the discriminatory metabolites we identified free fatty acids, phospholipids, and triacylglycerols, as well as precursors of eicosanoid and the products of reactive oxygen species linked to processes of inflammation, proliferation, and oxidative stress. Thus, metabolic profiling is able to identify changes due to the pharmacological mode of action of xenobiotics and contribute to early screening for non-genotoxic potential.