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

A novel support vector machine-based 1-day, single-dose prediction model of genotoxic hepatocarcinogenicity in rats

The development of a rapid and accurate model for determining the genotoxicity and carcinogenicity of chemicals is crucial for effective cancer risk assessment. This study aims to develop a 1-day, single-dose model for identifying genotoxic hepatocarcinogens (GHCs) in rats. Microarray gene expression data from the livers of rats administered a single dose of 58 compounds, including 5 GHCs, was obtained from the Open TG-GATEs database and used for the identification of marker genes and the construction of a predictive classifier to identify GHCs in rats. We identified 10 gene markers commonly responsive to all 5 GHCs and used them to construct a support vector machine-based predictive classifier. In the silico validation using the expression data of the Open TG-GATEs database indicates that this classifier distinguishes GHCs from other compounds with high accuracy. To further assess the model's effectiveness and reliability, we conducted multi-institutional 1-day single oral administration studies on rats. These studies examined 64 compounds, including 23 GHCs, with gene expression data of the marker genes obtained via quantitative PCR 24 h after a single oral administration. Our results demonstrate that qPCR analysis is an effective alternative to microarray analysis. The GHC predictive model showed high accuracy and reliability, achieving a sensitivity of 91% (21/23) and a specificity of 93% (38/41) across multiple validation studies in three institutions. In conclusion, the present 1-day single oral administration model proves to be a reliable and highly sensitive tool for identifying GHCs and is anticipated to be a valuable tool in identifying and screening potential GHCs.

Burn Pit Smoke Condensate-Mediated Toxicity in Human Airway Epithelial Cells

Burn pits are a method of open-air waste management that was common during military operations in Iraq, Afghanistan, and other regions in Southwest Asia. Veterans returning from deployment have reported respiratory symptoms, potentially from exposure to burn pit smoke, yet comprehensive assessment of such exposure on pulmonary health is lacking. We have previously shown that exposure to condensates from burn pit smoke emissions causes inflammation and cytotoxicity in mice. In this study, we explored the effects of burn pit smoke condensates on human airway epithelial cells (HAECs) to understand their impact on cellular targets in the human lung. HAECs were cultured at the air-liquid interface (ALI) and exposed to burn pit waste smoke condensates (plywood, cardboard, plastic, mixed, and mixed with diesel) generated under smoldering and flaming conditions. Cytotoxicity was evaluated by measuring transepithelial electrical resistance (TEER) and lactate dehydrogenase (LDH) release; toxicity scores (TSs) were quantified for each exposure. Pro-inflammatory cytokine release and modulation of gene expression were examined for cardboard and plastic condensate exposures. Burn pit smoke condensates generated under flaming conditions affected cell viability, with flaming mixed waste and plywood exhibiting the highest toxicity scores. Cardboard and plastic smoke condensates modulated cytokine secretion, with GM-CSF and IL-1β altered in more than one exposure group. Gene expression of detoxifying enzymes (ALDH1A3, ALDH3A1, CYP1A1, CYP1B1, NQO1, etc.), mucins (MUC5AC, MUC5B), and cytokines was affected by several smoke condensates. Particularly, expression of IL6 was elevated following exposure to all burn pit smoke condensates, and polycyclic aromatic hydrocarbon acenaphthene was positively associated with the IL-6 level in the basolateral media of HAECs. These observations demonstrate that exposure to smoke condensates of materials present in burn pits adversely affects HAECs and that aberrant cytokine secretion and altered gene expression profiles following burn pit material smoke exposure could contribute to the development of airway disease.

Navigating the bridge between wet and dry lab toxicology research to address current challenges with high-dimensional data

Toxicology research has rapidly evolved, leveraging increasingly advanced technologies in high-throughput approaches to yield important information on toxicological mechanisms and health outcomes. Data produced through toxicology studies are consequently becoming larger, often producing high-dimensional data. These types of data hold promise for imparting new knowledge, yet inherently have complexities causing them to be a rate-limiting element for researchers, particularly those that are housed in "wet lab" settings (i.e., researchers that use liquids to analyze various chemicals and biomarkers as opposed to more computationally focused, "dry lab" researchers). These types of challenges represent topics of ongoing conversation amongst our team and researchers in the field. The aim of this perspective is to i) summarize hurdles in analyzing high-dimensional data in toxicology that require improved training and translation for wet lab researchers, ii) highlight example methods that have aided in translating data analysis techniques to wet lab researchers; and iii) describe challenges that remain to be effectively addressed, to date, in toxicology research. Specific aspects include methodologies that could be introduced to wet lab researchers, including data pre-processing, machine learning, and data reduction. Current challenges discussed include model interpretability, study biases, and data analysis training. Example efforts implemented to translate these data analysis techniques are also mentioned, including online data analysis resources and hands-on workshops. Questions are also posed to continue conversation in the toxicology community. Contents of this perspective represent timely issues broadly occurring in the fields of bioinformatics and toxicology that require ongoing dialogue between wet and dry lab researchers.

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.

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.

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.

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.

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.

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.

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.

Risks for public health related to the presence of furan and methylfurans in food

The European Commission asked EFSA for a scientific evaluation on the risk to human health of the presence of furan and methylfurans (2-methylfuran, 3-methylfuran and 2,5-dimethylfuran) in food. They are formed in foods during thermal processing and can co-occur. Furans are produced from several precursors such as ascorbic acid, amino acids, carbohydrates, unsaturated fatty acids and carotenoids, and are found in a variety of foods including coffee and canned and jarred foods. Regarding furan occurrence, 17,056 analytical results were used in the evaluation. No occurrence data were received on methylfurans. The highest exposures to furan were estimated for infants, mainly from ready-to-eat meals. Grains and grain-based products contribute most for toddlers, other children and adolescents. In adults, elderly and very elderly, coffee is the main contributor to dietary exposure. Furan is absorbed from the gastrointestinal tract and is found in highest amounts in the liver. It has a short half-life and is metabolised by cytochrome P450 2E1 (CYP2E1) to the reactive metabolite, cis-but-2-ene-1,4-dialdehyde (BDA). BDA can bind covalently to amino acids, proteins and DNA. Furan is hepatotoxic in rats and mice with cholangiofibrosis in rats and hepatocellular adenomas/carcinomas in mice being the most prominent effects. There is limited evidence of chromosomal damage in vivo and a lack of understanding of the underlying mechanism. Clear evidence for indirect mechanisms involved in carcinogenesis include oxidative stress, gene expression alterations, epigenetic changes, inflammation and increased cell proliferation. The CONTAM Panel used a margin of exposure (MOE) approach for the risk characterisation using as a reference point a benchmark dose lower confidence limit for a benchmark response of 10% of 0.064 mg/kg body weight (bw) per day for the incidence of cholangiofibrosis in the rat. The calculated MOEs indicate a health concern. This conclusion was supported by the calculated MOEs for the neoplastic effects.

The principle of safety evaluation in medicinal drug - how can toxicology contribute to drug discovery and development as a multidisciplinary science?

Pharmaceutical (drug) safety assessment covers a diverse science-field in the drug discovery and development including the post-approval and post-marketing phases in order to evaluate safety and risk management. The principle in toxicological science is to be placed on both of pure and applied sciences that are derived from past/present scientific knowledge and coming new science and technology. In general, adverse drug reactions are presented as "biological responses to foreign substances." This is the basic concept of thinking about the manifestation of adverse drug reactions. Whether or not toxic expressions are extensions of the pharmacological effect, adverse drug reactions as seen from molecular targets are captured in the category of "on-target" or "off-target", and are normally expressed as a biological defense reaction. Accordingly, reactions induced by pharmaceuticals can be broadly said to be defensive reactions. Recent molecular biological conception is in line with the new, remarkable scientific and technological developments in the medical and pharmaceutical areas, and the viewpoints in the field of toxicology have shown that they are approaching toward the same direction as well. This paper refers to the basic concept of pharmaceutical toxicology, the differences for safety assessment in each stage of drug discovery and development, regulatory submission, and the concept of scientific considerations for risk assessment and management from the viewpoint of "how can multidisciplinary toxicology contribute to innovative drug discovery and development?" And also realistic translational research from preclinical to clinical application is required to have a significant risk management in post market by utilizing whole scientific data derived from basic and applied scientific research works. In addition, the significance for employing the systems toxicology based on AOP (Adverse Outcome Pathway) analysis is introduced, and coming challenges on precision medicine are to be addressed for the new aspect of efficacy and safety evaluation.