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

Effects of essential oil of Origanum onites and its major component carvacrol on the expression of toxicity pathway genes in HepG2 cells

BACKGROUND

Origanum species have been used in various commercial constructions as a remedy against burns and wounds, agriculture, alcoholic drinks, fragrance, and flavoring substances of food products. The essential oil of Origanum onites L. (EOOO) and its component carvacrol (CV) possesses a wide range of biological activities including anti-cancer activity.

PURPOSE

The purpose of this study was to investigate the growth inhibitory activity of the essential oil and its major component CV and then hepatotoxicity pathway-related genes in HepG2 cells.

METHODS

The effects of the EOOO and CV on cell growth and mRNA expressions of 84 hepatotoxicity pathway-related genes were investigated in HepG2, using trypan blue exclusion/ bromodeoxyuridine (BrdU) incorporation tests and real-time-polymerase chain reaction (RT-PCR) array, respectively.

RESULTS

The EOOO and CV inhibited cell growth with IC50 values of 0.08 µg/mL and 45 µg/mL, respectively, after 24 h. Real-time, reverse-transcription-polymerase chain reaction (RT2-PCR) array analysis revealed that expressions of 32 genes out of 84 were changed at least 2-fold or more in the EOOO-treated cells. Among them, expression levels of 17 genes were elevated, while expression levels of 15 genes were diminished. Furthermore, after exposure of cells to 45 µg/mL of CV, the expression of 8 genes was increased while the other 8 genes were decreased. Both the EOOO and carvacrol affected the expression of 48 genes of HepG2 cells which are involved in the hepatotoxicity pathway, indicating their hepatoprotective and possible anti-hepatocarcinogenic effects.

CONCLUSION

The present study demonstrates that the essential oil of Origanum onites and carvacrol can be used in various applications such as anticancer or herbal drugs, since its non-hepatotoxicity.

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.

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.

Assessment of genotoxic chemicals using chemogenomic profiling based on gene-knockout library in Saccharomyces cerevisiae

Understanding the adverse effects of genotoxic chemicals and identifying them effectively from non-genotoxic chemicals are of great worldwide concerns. Here, Saccharomyces cerevisiae (yeast) genome-wide single-gene knockout screening approach was conducted to assess two genotoxic chemicals (4-nitroquinoline-1-oxide (4-NQO) and formaldehyde (FA)) and environmental pollutant dichloroacetic acid (DCA, genotoxicity is controversial). DNA repair was significant enriched in the gene ontology (GO) biology process (BP) terms and KEGG pathways when exposed to low concentrations of 4-NQO and FA. Higher concentrations of 4-NQO and FA influenced some RNA metabolic and biosynthesis pathways. Moreover, replication and repair associated pathways were top ranked KEGG pathways with high fold-change for low concentrations of 4-NQO and FA. The similar gene profiles perturbed by DCA with three test concentrations identified, the common GO BP terms associated with aromatic amino acid family biosynthetic process and ubiquitin-dependent protein catabolic process via the multivesicular body sorting pathway. DCA has no obvious genotoxicity as there was no enriched DNA damage and repair pathways and fold-change of replication and repair KEGG pathways were very low. Five genes (RAD18, RAD59, MUS81, MMS4, and BEM4) could serve as candidate genes for genotoxic chemicals. Overall, the yeast functional genomic profiling showed great performance for assessing the signatures and potential molecular mechanisms of genotoxic chemicals.

Integration of Epigenetic Mechanisms into Non-Genotoxic Carcinogenicity Hazard Assessment: Focus on DNA Methylation and Histone Modifications

Epigenetics involves a series of mechanisms that entail histone and DNA covalent modifications and non-coding RNAs, and that collectively contribute to programing cell functions and differentiation. Epigenetic anomalies and DNA mutations are co-drivers of cellular dysfunctions, including carcinogenesis. Alterations of the epigenetic system occur in cancers whether the initial carcinogenic events are from genotoxic (GTxC) or non-genotoxic (NGTxC) carcinogens. NGTxC are not inherently DNA reactive, they do not have a unifying mode of action and as yet there are no regulatory test guidelines addressing mechanisms of NGTxC. To fil this gap, the Test Guideline Programme of the Organisation for Economic Cooperation and Development is developing a framework for an integrated approach for the testing and assessment (IATA) of NGTxC and is considering assays that address key events of cancer hallmarks. Here, with the intent of better understanding the applicability of epigenetic assays in chemical carcinogenicity assessment, we focus on DNA methylation and histone modifications and review: (1) epigenetic mechanisms contributing to carcinogenesis, (2) epigenetic mechanisms altered following exposure to arsenic, nickel, or phenobarbital in order to identify common carcinogen-specific mechanisms, (3) characteristics of a series of epigenetic assay types, and (4) epigenetic assay validation needs in the context of chemical hazard assessment. As a key component of numerous NGTxC mechanisms of action, epigenetic assays included in IATA assay combinations can contribute to improved chemical carcinogen identification for the better protection of public health.

Carcinogenesis: Failure of resolution of inflammation?

Inflammation in the tumor microenvironment is a hallmark of cancer and is recognized as a key characteristic of carcinogens. However, the failure of resolution of inflammation in cancer is only recently being understood. Products of arachidonic acid and related fatty acid metabolism called eicosanoids, including prostaglandins, leukotrienes, lipoxins, and epoxyeicosanoids, critically regulate inflammation, as well as its resolution. The resolution of inflammation is now appreciated to be an active biochemical process regulated by endogenous specialized pro-resolving lipid autacoid mediators which combat infections and stimulate tissue repair/regeneration. Environmental and chemical human carcinogens, including aflatoxins, asbestos, nitrosamines, alcohol, and tobacco, induce tumor-promoting inflammation and can disrupt the resolution of inflammation contributing to a devastating global cancer burden. While mechanisms of carcinogenesis have focused on genotoxic activity to induce mutations, nongenotoxic mechanisms such as inflammation and oxidative stress promote genotoxicity, proliferation, and mutations. Moreover, carcinogens initiate oxidative stress to synergize with inflammation and DNA damage to fuel a vicious feedback loop of cell death, tissue damage, and carcinogenesis. In contrast, stimulation of resolution of inflammation may prevent carcinogenesis by clearance of cellular debris via macrophage phagocytosis and inhibition of an eicosanoid/cytokine storm of pro-inflammatory mediators. Controlling the host inflammatory response and its resolution in carcinogen-induced cancers will be critical to reducing carcinogen-induced morbidity and mortality. Here we review the recent evidence that stimulation of resolution of inflammation, including pro-resolution lipid mediators and soluble epoxide hydrolase inhibitors, may be a new chemopreventive approach to prevent carcinogen-induced cancer that should be evaluated in humans.

Identification of Time-Invariant Biomarkers for Non-Genotoxic Hepatocarcinogen Assessment

Non-genotoxic hepatocarcinogens (NGHCs) can only be confirmed by 2-year rodent studies. Toxicogenomics (TGx) approaches using gene expression profiles from short-term animal studies could enable early assessment of NGHCs. However, high variance in the modulation of the genes had been noted among exposure styles and datasets. Expanding from our previous strategy in identifying consensus biomarkers in multiple experiments, we aimed to identify time-invariant biomarkers for NGHCs in short-term exposure styles and validate their applicability to long-term exposure styles. In this study, nine time-invariant biomarkers, namely A2m, Akr7a3, Aqp7, Ca3, Cdc2a, Cdkn3, Cyp2c11, Ntf3, and Sds, were identified from four large-scale microarray datasets. Machine learning techniques were subsequently employed to assess the prediction performance of the biomarkers. The biomarker set along with the Random Forest models gave the highest median area under the receiver operating characteristic curve (AUC) of 0.824 and a low interquartile range (IQR) variance of 0.036 based on a leave-one-out cross-validation. The application of the models to the external validation datasets achieved high AUC values of greater than or equal to 0.857. Enrichment analysis of the biomarkers inferred the involvement of chronic inflammatory diseases such as liver cirrhosis, fibrosis, and hepatocellular carcinoma in NGHCs. The time-invariant biomarkers provided a robust alternative for NGHC prediction.

The promise of toxicogenomics for genetic toxicology: past, present and future

Toxicogenomics, the application of genomics to toxicology, was described as 'a new era' for toxicology. Standard toxicity tests typically involve a number of short-term bioassays that are costly, time consuming, require large numbers of animals and generally focus on a single end point. Toxicogenomics was heralded as a way to improve the efficiency of toxicity testing by assessing gene regulation across the genome, allowing rapid classification of compounds based on characteristic expression profiles. Gene expression microarrays could measure and characterise genome-wide gene expression changes in a single study and while transcriptomic profiles that can discriminate between genotoxic and non-genotoxic carcinogens have been identified, challenges with the approach limited its application. As such, toxicogenomics did not transform the field of genetic toxicology in the way it was predicted. More recently, next generation sequencing (NGS) technologies have revolutionised genomics owing to the fact that hundreds of billions of base pairs can be sequenced simultaneously cheaper and quicker than traditional Sanger methods. In relation to genetic toxicology, and thousands of cancer genomes have been sequenced with single-base substitution mutational signatures identified, and mutation signatures have been identified following treatment of cells with known or suspected environmental carcinogens. RNAseq has been applied to detect transcriptional changes following treatment with genotoxins; modified RNAseq protocols have been developed to identify adducts in the genome and Duplex sequencing is an example of a technique that has recently been developed to accurately detect mutation. Machine learning, including MutationSeq and SomaticSeq, has also been applied to somatic mutation detection and improvements in automation and/or the application of machine learning algorithms may allow high-throughput mutation sequencing in the future. This review will discuss the initial promise of transcriptomics for genetic toxicology, and how the development of NGS technologies and new machine learning algorithms may finally realise that promise.

The Carcinogenome Project: In Vitro Gene Expression Profiling of Chemical Perturbations to Predict Long-Term Carcinogenicity

BACKGROUND

Most chemicals in commerce have not been evaluated for their carcinogenic potential. The de facto gold-standard approach to carcinogen testing adopts the 2-y rodent bioassay, a time-consuming and costly procedure. High-throughput in vitro assays are a promising alternative for addressing the limitations in carcinogen screening.

OBJECTIVES

We developed a screening process for predicting chemical carcinogenicity and genotoxicity and characterizing modes of actions (MoAs) using in vitro gene expression assays.

METHODS

We generated a large toxicogenomics resource comprising [Formula: see text] expression profiles corresponding to 330 chemicals profiled in HepG2 (human hepatocellular carcinoma cell line) at multiple doses and replicates. Predictive models of carcinogenicity and genotoxicity were built using a random forest classifier. Differential pathway enrichment analysis was performed to identify pathways associated with carcinogen exposure. Signatures of carcinogenicity and genotoxicity were compared with external sources, including Drugmatrix and the Connectivity Map.

RESULTS

Among profiles with sufficient bioactivity, our classifiers achieved 72.2% Area Under the ROC Curve (AUC) for predicting carcinogenicity and 82.3% AUC for predicting genotoxicity. Chemical bioactivity, as measured by the strength and reproducibility of the transcriptional response, was not significantly associated with long-term carcinogenicity in doses up to [Formula: see text]. However, sufficient bioactivity was necessary for a chemical to be used for prediction of carcinogenicity. Pathway enrichment analysis revealed pathways consistent with known pathways that drive cancer, including DNA damage and repair. The data is available at https://clue.io/CRCGN_ABC , and a portal for query and visualization of the results is accessible at https://carcinogenome.org .

DISCUSSION

We demonstrated an in vitro screening approach using gene expression profiling to predict carcinogenicity and infer MoAs of chemical perturbations. https://doi.org/10.1289/EHP3986.

Mechanisms of DNA-reactive and epigenetic chemical carcinogens: applications to carcinogenicity testing and risk assessment

Chemicals with carcinogenic activity in either animals or humans produce increases in neoplasia through diverse mechanisms. One mechanism is reaction with nuclear DNA. Other mechanisms consist of epigenetic effects involving either modifications of regulatory macromolecules or perturbation of cellular regulatory processes. The basis for distinguishing between carcinogens that have either DNA reactivity or an epigenetic activity as their primary mechanism of action is detailed in this review. In addition, important applications of information on these mechanisms of action to carcinogenicity testing and human risk assessment are discussed.

Screening Strategies and Methods for Better Off-Target Liability Prediction and Identification of Small-Molecule Pharmaceuticals

Pharmaceutical discovery and development is a long and expensive process that, unfortunately, still results in a low success rate, with drug safety continuing to be a major impedance. Improved safety screening strategies and methods are needed to more effectively fill this critical gap. Recent advances in informatics are now making it possible to manage bigger data sets and integrate multiple sources of screening data in a manner that can potentially improve the selection of higher-quality drug candidates. Integrated screening paradigms have become the norm in Pharma, both in discovery screening and in the identification of off-target toxicity mechanisms during later-stage development. Furthermore, advances in computational methods are making in silico screens more relevant and suggest that they may represent a feasible option for augmenting the current screening paradigm. This paper outlines several fundamental methods of the current drug screening processes across Pharma and emerging techniques/technologies that promise to improve molecule selection. In addition, the authors discuss integrated screening strategies and provide examples of advanced screening paradigms.

Xenobiotic CAR Activators Induce Dlk1-Dio3 Locus Noncoding RNA Expression in Mouse Liver

Derisking xenobiotic-induced nongenotoxic carcinogenesis (NGC) represents a significant challenge during the safety assessment of chemicals and therapeutic drugs. The identification of robust mechanism-based NGC biomarkers has the potential to enhance cancer hazard identification. We previously demonstrated Constitutive Androstane Receptor (CAR) and WNT signaling-dependent up-regulation of the pluripotency associated Dlk1-Dio3 imprinted gene cluster noncoding RNAs (ncRNAs) in the liver of mice treated with tumor-promoting doses of phenobarbital (PB). Here, we have compared phenotypic, transcriptional ,and proteomic data from wild-type, CAR/PXR double knock-out and CAR/PXR double humanized mice treated with either PB or chlordane, and show that hepatic Dlk1-Dio3 locus long ncRNAs are upregulated in a CAR/PXR-dependent manner by two structurally distinct CAR activators. We further explored the specificity of Dlk1-Dio3 locus ncRNAs as hepatic NGC biomarkers in mice treated with additional compounds working through distinct NGC modes of action. We propose that up-regulation of Dlk1-Dio3 cluster ncRNAs can serve as an early biomarker for CAR activator-induced nongenotoxic hepatocarcinogenesis and thus may contribute to mechanism-based assessments of carcinogenicity risk for chemicals and novel therapeutics.

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.

Genome-wide gene expression analysis of mouse embryonic stem cells exposed to p-dichlorobenzene

Because of the limitations of whole animal testing approaches for toxicological assessment, new cell-based assay systems have been widely studied. In this study, we focused on two biological products for toxicological assessment: mouse embryonic stem cells (mESCs) and long noncoding RNAs (lncRNAs). mESCs possess the abilities of self-renewal and differentiation into multiple cell types. LlncRNAs are an important class of pervasive non-protein-coding transcripts involved in the molecular mechanisms associated with responses to chemicals. We exposed mESCs to p-dichlorobenzene (p-DCB) for 1 or 28 days (daily dose), extracted total RNA, and performed deep sequencing analyses. The genome-wide gene expression analysis indicated that mechanisms modulating proteins occurred following acute and chronic exposures, and mechanisms modulating genomic DNA occurred following chronic exposure. Moreover, our results indicate that three novel lncRNAs (Snora41, Gm19947, and Scarna3a) in mESCs respond to p-DCB exposure. We propose that these lncRNAs have the potential to be surrogate indicators of p-DCB responses in mESCs.

Evidence that the capacity of nongenotoxic carcinogens to induce oxidative stress is subject to marked variability

Many drugs and environmental chemicals which are not directly mutagenic have the capacity to increase the incidence of tumors in the liver and other tissues. For this reason, such compounds are known as nongenotoxic carcinogens. The mechanisms underlying their effects remain unclear; however, their capacity to induce oxidative stress is considered to be a critical step in the carcinogenic process, although the evidence that this is actually the case remains equivocal and sparse. We have exploited a novel heme oxygenase-1 reporter mouse to evaluate the capacity of nongenotoxic carcinogens with different mechanisms of action to induce oxidative stress in the liver in vivo. When these compounds were administered at doses reported to cause liver tumors, marked differences in activation of the reporter were observed. 1,4-Dichlorobenzene and nafenopin were strong inducers of oxidative stress, whereas phenobarbital, piperonyl butoxide, cyproterone acetate, and WY14,643 were, at best, only very weak inducers. In the case of phenobarbital and thioacetamide, the number of LacZ-positive hepatocytes increased with time, and for the latter also with dose. The data obtained demonstrate that although some nongenotoxic carcinogens can induce oxidative stress, it is not a dominant feature of the response to these compounds. Therefore in contrast to the current models, these data suggest that oxidative stress is not a key determinant in the mechanism of nongenotoxic carcinogenesis but may contribute to the effects in a compound-specific manner.