Investigating the Generalizability of the MultiFlow ® DNA Damage Assay and Several Companion Machine Learning Models With a Set of 103 Diverse Test Chemicals

Mitigation of Volatile Chemicals' Effect on Adjacent Microtiter Plate Wells

In vitro new approach methodologies used to assess chemicals for biological effects are typically designed to limit the amount of test article required and to promote efficiencies such as compatibility with liquid handlers, and so forth. This is certainly true in the case of genetic toxicology, where many methods have been and continue to be developed with 96- or 384-well plate processing in mind. However, one recognized concern with microwell plates is that the volatility of test substances and/or their metabolites and/or their degradation products may affect adjacent wells. Here, we describe an approach that combines breathable membranes as well as activated carbon filters to mitigate volatility issues in 96 well plates. These experiments were performed with cyclophosphamide- and trimethylhydroquinone-exposed TK6 cells and utilized the biomarkers micronuclei, p53, γH2AX, phospho-histone H3, and nuclei to counting bead ratios to both demonstrate volatility impact and to assess the effectiveness of the solution described herein.

Visualization strategies to aid interpretation of high-dimensional genotoxicity data

This article describes a range of high-dimensional data visualization strategies that we have explored for their ability to complement machine learning algorithm predictions derived from MultiFlow® assay results. For this exercise, we focused on seven biomarker responses resulting from the exposure of TK6 cells to each of 126 diverse chemicals over a range of concentrations. Obviously, challenges associated with visualizing seven biomarker responses were further complicated whenever there was a desire to represent the entire 126 chemical data set as opposed to results from a single chemical. Scatter plots, spider plots, parallel coordinate plots, hierarchical clustering, principal component analysis, toxicological prioritization index, multidimensional scaling, t-distributed stochastic neighbor embedding, and uniform manifold approximation and projection are each considered in turn. Our report provides a comparative analysis of these techniques. In an era where multiplexed assays and machine learning algorithms are becoming the norm, stakeholders should find some of these visualization strategies useful for efficiently and effectively interpreting their high-dimensional data.

Liver-on-chip model and application in predictive genotoxicity and mutagenicity of drugs

Currently, there is no test system, whether in vitro or in vivo, capable of examining all endpoints required for genotoxicity evaluation used in pre-clinical drug safety assessment. The objective of this study was to develop a model which could assess all the required endpoints and possesses robust human metabolic activity, that could be used in a streamlined, animal-free manner. Liver-on-chip (LOC) models have intrinsic human metabolic activity that mimics the in vivo environment, making it a preferred test system. For our assay, the LOC was assembled using primary human hepatocytes or HepaRG cells, in a MPS-T12 plate, maintained under microfluidic flow conditions using the PhysioMimix® Microphysiological System (MPS), and co-cultured with human lymphoblastoid (TK6) cells in transwells. This system allows for interaction between two compartments and for the analysis of three different genotoxic endpoints, i.e. DNA strand breaks (comet assay) in hepatocytes, chromosome loss or damage (micronucleus assay) and mutation (Duplex Sequencing) in TK6 cells. Both compartments were treated at 0, 24 and 45 h with two direct genotoxicants: methyl methanesulfonate (MMS) and ethyl methanesulfonate (EMS), and two genotoxicants requiring metabolic activation: benzo[a]pyrene (B[a]P) and cyclophosphamide (CP). Assessment of cytochrome activity, RNA expression, albumin, urea and lactate dehydrogenase production, demonstrated functional metabolic capacities. Genotoxicity responses were observed for all endpoints with MMS and EMS. Increases in the micronucleus and mutations (MF) frequencies were also observed with CP, and %Tail DNA with B[a]P, indicating the metabolic competency of the test system. CP did not exhibit an increase in the %Tail DNA, which is in line with in vivo data. However, B[a]P did not exhibit an increase in the % micronucleus and MF, which might require an optimization of the test system. In conclusion, this proof-of-principle experiment suggests that LOC-MPS technology is a promising tool for in vitro hazard identification genotoxicants.

The use of effect biomarkers in chemical mixtures risk assessment - Are they still important?

Human epidemiological studies with biomarkers of effect play an invaluable role in identifying health effects with chemical exposures and in disease prevention. Effect biomarkers that measure genetic damage are potent tools to address the carcinogenic and/or mutagenic potential of chemical exposures, increasing confidence in regulatory risk assessment decision-making processes. The micronucleus (MN) test is recognized as one of the most successful and reliable assays to assess genotoxic events, which are associated with exposures that may cause cancer. To move towards the next generation risk assessment is crucial to establish bridges between standard approaches, new approach methodologies (NAMs) and tools for increase the mechanistically-based biological plausibility in human studies, such as the adverse outcome pathways (AOPs) framework. This paper aims to highlight the still active role of MN as biomarker of effect in the evolution and applicability of new methods and approaches in human risk assessment, with the positive consequence, that the new methods provide a deeper knowledge of the mechanistically-based biology of these endpoints.

Discovery of MK-1468: A Potent, Kinome-Selective, Brain-Penetrant Amidoisoquinoline LRRK2 Inhibitor for the Potential Treatment of Parkinson's Disease

Genetic mutation of the leucine-rich repeat kinase 2 (LRRK2) protein has been associated with Parkinson's disease (PD), a disabling and progressive neurodegenerative disorder that is devoid of efficacious disease-modifying therapies. Herein, we describe the invention of an amidoisoquinoline (IQ)-derived LRRK2 inhibitor lead chemical series. Knowledge-, structure-, and property-based drug design in concert with rigorous application of in silico calculations and presynthesis predictions enabled the prioritization of molecules with favorable CNS "drug-like" physicochemical properties. This resulted in the discovery of compound 8, which was profiled extensively before human ether-a-go-go (hERG) ion channel inhibition halted its progression. Strategic reduction of lipophilicity and basicity resulted in attenuation of hERG ion channel inhibition while maintaining a favorable CNS efflux transporter profile. Further structure- and property-based optimizations resulted in the discovery of preclinical candidate MK-1468. This exquisitely selective LRRK2 inhibitor has a projected human dose of 48 mg BID and a preclinical safety profile that supported advancement toward GLP toxicology studies.

Scientific opinion on the renewal of the authorisation of proFagus Smoke R709 (SF-008) as a smoke flavouring Primary Product

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product proFagus Smoke R709 (SF-008), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003. This opinion refers to the assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. ProFagus Smoke R709 is obtained by pyrolysis of beech and oak wood as main source materials. The panel concluded that the compositional data provided on the Primary Product are adequate. At the maximum proposed use levels, dietary exposure estimates calculated with DietEx ranged from 0.8 to 12.2 mg/kg body weight (bw) per day at the mean and from 2.3 to 51.4 mg/kg bw per day at the 95th percentile. The Panel concluded that three components in the Primary Product raise a potential concern for genotoxicity. In addition, a potential concern for genotoxicity was identified for the unidentified part of the mixture. The Primary Product contains furan-2(5H)-one, for which a concern for genotoxicity was identified in vivo upon oral administration. Considering that the exposure estimates for this component are above the TTC of 0.0025 μg/kg bw per day for DNA-reactive mutagens and/or carcinogens, the panel concluded that the Primary Product raises concern with respect to genotoxicity.

Review of machine learning and deep learning models for toxicity prediction

The ever-increasing number of chemicals has raised public concerns due to their adverse effects on human health and the environment. To protect public health and the environment, it is critical to assess the toxicity of these chemicals. Traditional in vitro and in vivo toxicity assays are complicated, costly, and time-consuming and may face ethical issues. These constraints raise the need for alternative methods for assessing the toxicity of chemicals. Recently, due to the advancement of machine learning algorithms and the increase in computational power, many toxicity prediction models have been developed using various machine learning and deep learning algorithms such as support vector machine, random forest, k-nearest neighbors, ensemble learning, and deep neural network. This review summarizes the machine learning- and deep learning-based toxicity prediction models developed in recent years. Support vector machine and random forest are the most popular machine learning algorithms, and hepatotoxicity, cardiotoxicity, and carcinogenicity are the frequently modeled toxicity endpoints in predictive toxicology. It is known that datasets impact model performance. The quality of datasets used in the development of toxicity prediction models using machine learning and deep learning is vital to the performance of the developed models. The different toxicity assignments for the same chemicals among different datasets of the same type of toxicity have been observed, indicating benchmarking datasets is needed for developing reliable toxicity prediction models using machine learning and deep learning algorithms. This review provides insights into current machine learning models in predictive toxicology, which are expected to promote the development and application of toxicity prediction models in the future.

Scientific opinion on the renewal of the authorisation of proFagus Smoke R714 (SF-001) as a smoke flavouring Primary Product

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product proFagus Smoke R714 (SF-001), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003. This opinion refers to the assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. ProFagus Smoke R714 is obtained by pyrolysis of beech and oak woods as main source materials. Based on the compositional data, the Panel noted that the identified and quantified proportion of the solvent-free fraction amounts to 39 weight (wt)%, thus the applied method does not meet the legal quality criterion that at least 50% of the solvent-free fraction shall be identified and quantified. At the maximum proposed use levels, dietary exposure estimates calculated with DietEx ranged from 0.7 to 10.9 mg/kg body weight (bw) per day at the mean and from 2.2 to 42.5 mg/kg bw per day at the 95th percentile. The Panel concluded that three components in the Primary Product raise a potential concern for genotoxicity. In addition, a potential concern for genotoxicity was identified for the unidentified part of the mixture. The Primary Product contains furan-2(5H)-one, for which a concern for genotoxicity was identified in vivo upon oral administration. Considering that the exposure estimates for this component are above the threshold of toxicological concern (TTC) of 0.0025 μg/kg bw per day for DNA-reactive mutagens and/or carcinogens, the Panel concluded that the Primary Product raises concern with respect to genotoxicity.

Scientific opinion on the renewal of the authorisation of Smoke Concentrate 809045 (SF-003) as a smoke flavouring Primary Product

The EFSA Panel on Food Additives and Flavourings (FAF) was requested to evaluate the safety of the smoke flavouring Primary Product Smoke Concentrate 809045 (SF-003), for which a renewal application was submitted in accordance with Article 12(1) of Regulation (EC) No 2065/2003. This opinion refers to the assessment of data submitted on chemical characterisation, dietary exposure and genotoxicity of the Primary Product. Product Smoke Concentrate 809045 is obtained by pyrolysis of beech wood. The Panel concluded that the compositional data provided on the Primary Product are adequate. At the maximum proposed use levels, dietary exposure estimates calculated with DietEx ranged from 0.1 to 1.5 mg/kg body weight (bw) per day at the mean and from 0.2 to 5.2 mg/kg bw per day at the 95th percentile. The Panel concluded that eleven components in the Primary Product raise a potential concern for genotoxicity. In addition, a potential concern for genotoxicity was identified for the unidentified part of the mixture. The Primary Product contains furan-2(5H)-one and benzene-1,2-diol, for which a concern for genotoxicity was identified in vivo upon oral administration. Considering that the exposure estimates for these two components are above the threshold of toxicological concern (TTC) of 0.0025 μg/kg bw per day for DNA-reactive mutagens and/or carcinogens, the Panel concluded that the Primary Product raises concern with respect to genotoxicity.

Early detection of genotoxic hepatocarcinogens in rats using γH2AX and Ki-67: prediction by machine learning

Direct DNA double-strand breaks result in phosphorylation of H2AX, a variant of the histone H2 protein. Phosphorylated H2AX (γH2AX) may be a potential indicator in the evaluation of genotoxicity and hepatocarcinogenicity. In this study, γH2AX and Ki-67 were detected in the short-term responses (24 h after chemical administration) to classify genotoxic hepatocarcinogens (GHs) from non-GH chemicals. One hundred and thirty-five 6-week-old Crl: CD(SD) (SPF) male rats were treated with 22 chemicals including 11 GH and 11 non-GH, sacrificed 24 h later, and immunostained with γH2AX and Ki-67. Positivity rates of these markers were measured in the 3 liver ZONEs 1-3; portal, lobular, and central venous regions. These values were input into 3 machine learning models-Naïve Bayes, Random Forest, and k-Nearest Neighbor to classify GH and non-GH using a 10-fold cross-validation method. All 11 and 10 out of 11 GH caused significant increase in γH2AX and Ki-67 levels, respectively (P < .05). Of the 3 machine learning models, Random Forest performed the best. GH were identified with 95.0% sensitivity (76/80 GH-treated rats), 90.9% specificity (50/55 non-GH-treated rats), and 90.0% overall correct response rate using γH2AX staining, and 96.2% sensitivity (77/80), 81.8% specificity (45/55), and 90.4% overall correct response rate using Ki-67 labeling. Random Forest model using γH2AX and Ki-67 could independently predict GH in the early stage with high accuracy.

Toxicological and pharmacokinetic properties of sucralose-6-acetate and its parent sucralose: in vitro screening assays

The purpose of this study was to determine the toxicological and pharmacokinetic properties of sucralose-6-acetate, a structural analog of the artificial sweetener sucralose. Sucralose-6-acetate is an intermediate and impurity in the manufacture of sucralose, and recent commercial sucralose samples were found to contain up to 0.67% sucralose-6-acetate. Studies in a rodent model found that sucralose-6-acetate is also present in fecal samples with levels up to 10% relative to sucralose which suggest that sucralose is also acetylated in the intestines. A MultiFlow® assay, a high-throughput genotoxicity screening tool, and a micronucleus (MN) test that detects cytogenetic damage both indicated that sucralose-6-acetate is genotoxic. The mechanism of action was classified as clastogenic (produces DNA strand breaks) using the MultiFlow® assay. The amount of sucralose-6-acetate in a single daily sucralose-sweetened drink might far exceed the threshold of toxicological concern for genotoxicity (TTCgenotox) of 0.15 µg/person/day. The RepliGut® System was employed to expose human intestinal epithelium to sucralose-6-acetate and sucralose, and an RNA-seq analysis was performed to determine gene expression induced by these exposures. Sucralose-6-acetate significantly increased the expression of genes associated with inflammation, oxidative stress, and cancer with greatest expression for the metallothionein 1 G gene (MT1G). Measurements of transepithelial electrical resistance (TEER) and permeability in human transverse colon epithelium indicated that sucralose-6-acetate and sucralose both impaired intestinal barrier integrity. Sucralose-6-acetate also inhibited two members of the cytochrome P450 family (CYP1A2 and CYP2C19). Overall, the toxicological and pharmacokinetic findings for sucralose-6-acetate raise significant health concerns regarding the safety and regulatory status of sucralose itself.

Quantitative in vitro to in vivo extrapolation of genotoxicity data provides protective estimates of in vivo dose

Genotoxicity assessment is a critical component in the development and evaluation of chemicals. Traditional genotoxicity assays (i.e., mutagenicity, clastogenicity, and aneugenicity) have been limited to dichotomous hazard classification, while other toxicity endpoints are assessed through quantitative determination of points-of-departures (PODs) for setting exposure limits. The more recent higher-throughput in vitro genotoxicity assays, many of which also provide mechanistic information, offer a powerful approach for determining defined PODs for potency ranking and risk assessment. In order to obtain relevant human dose context from the in vitro assays, in vitro to in vivo extrapolation (IVIVE) models are required to determine what dose would elicit a concentration in the body demonstrated to be genotoxic using in vitro assays. Previous work has demonstrated that application of IVIVE models to in vitro bioactivity data can provide PODs that are protective of human health, but there has been no evaluation of how these models perform with in vitro genotoxicity data. Thus, the Genetic Toxicology Technical Committee, under the Health and Environmental Sciences Institute, conducted a case study on 31 reference chemicals to evaluate the performance of IVIVE application to genotoxicity data. The results demonstrate that for most chemicals considered here (20/31), the PODs derived from in vitro data and IVIVE are health protective relative to in vivo PODs from animal studies. PODs were also protective by assay target: mutations (8/13 chemicals), micronuclei (9/12), and aneugenicity markers (4/4). It is envisioned that this novel testing strategy could enhance prioritization, rapid screening, and risk assessment of genotoxic chemicals.

Search for the optimal genotoxicity assay for routine testing of chemicals: Sensitivity and specificity of conventional and new test systems

Many conventional in vitro tests that are currently widely used for routine screening of chemicals have a sensitivity/specificity in the range between 60 % and 80 % for the detection of carcinogens. Most procedures were developed 30-40 years ago. In the last decades several assays became available which are based on the use of metabolically competent cell lines, improvement of the cultivation conditions and development of new endpoints. Validation studies indicate that some of these models may be more reliable for the detection of genotoxicants (i.e. many of them have sensitivity and specificity values between 80 % and 95 %). Therefore, they could replace conventional tests in the future. The bone marrow micronucleus (MN) assay with rodents is at present the most widely used in vivo test. The majority of studies indicate that it detects only 5-6 out of 10 carcinogens while experiments with transgenic rodents and comet assays seem to have a higher predictive value and detect genotoxic carcinogens that are negative in MN experiments. Alternatives to rodent experiments could be MN experiments with hen eggs or their replacement by combinations of new in vitro tests. Examples for promising candidates are ToxTracker, TGx-DDI, multiplex flow cytometry, γH2AX experiments, measurement of p53 activation and MN experiments with metabolically competent human derived liver cells. However, the realization of multicentric collaborative validation studies is mandatory to identify the most reliable tests.

Genotoxicity evaluation of nitrosamine impurities using human TK6 cells transduced with cytochrome P450s

Many nitrosamines are recognized as mutagens and potent rodent carcinogens. Over the past few years, nitrosamine impurities have been detected in various drugs leading to drug recalls. Although nitrosamines are included in a 'cohort of concern' because of their potential human health risks, most of this concern is based on rodent cancer and bacterial mutagenicity data, and there are little data on their genotoxicity in human-based systems. In this study, we employed human lymphoblastoid TK6 cells transduced with human cytochrome P450 (CYP) 2A6 to evaluate the genotoxicity of six nitrosamines that have been identified as impurities in drug products: N-nitrosodiethylamine (NDEA), N-nitrosoethylisopropylamine (NEIPA), N-nitroso-N-methyl-4-aminobutanoic acid (NMBA), N-nitrosomethylphenylamine (NMPA), N-nitrosodiisopropylamine (NDIPA), and N-nitrosodibutylamine (NDBA). Using flow cytometry-based assays, we found that 24-h treatment with NDEA, NEIPA, NMBA, and NMPA caused concentration-dependent increases in the phosphorylation of histone H2A.X (γH2A.X) in CYP2A6-expressing TK6 cells. Metabolism of these four nitrosamines by CYP2A6 also caused significant increases in micronucleus frequency as well as G2/M phase cell-cycle arrest. In addition, nuclear P53 activation was found in CYP2A6-expressing TK6 cells exposed to NDEA, NEIPA, and NMPA. Overall, the genotoxic potency of the six nitrosamine impurities in our test system was NMPA > NDEA ≈ NEIPA > NMBA > NDBA ≈ NDIPA. This study provides new information on the genotoxic potential of nitrosamines in human cells, complementing test results generated from traditional assays and partially addressing the issue of the relevance of nitrosamine genotoxicity for humans. The metabolically competent human cell system reported here may be a useful model for risk assessment of nitrosamine impurities found in drugs.

Comprehensive interpretation of in vitro micronucleus test results for 292 chemicals: from hazard identification to risk assessment application

Risk assessments are increasingly reliant on information from in vitro assays. The in vitro micronucleus test (MNvit) is a genotoxicity test that detects chromosomal abnormalities, including chromosome breakage (clastogenicity) and/or whole chromosome loss (aneugenicity). In this study, MNvit datasets for 292 chemicals, generated by the US EPA's ToxCast program, were evaluated using a decision tree-based pipeline for hazard identification. Chemicals were tested with 19 concentrations (n = 1) up to 200 µM, in the presence and absence of Aroclor 1254-induced rat liver S9. To identify clastogenic chemicals, %MN values at each concentration were compared to a distribution of batch-specific solvent controls; this was followed by cytotoxicity assessment and benchmark concentration (BMC) analyses. The approach classified 157 substances as positives, 25 as negatives, and 110 as inconclusive. Using the approach described in Bryce et al. (Environ Mol Mutagen 52:280-286, 2011), we identified 15 (5%) aneugens. IVIVE (in vitro to in vivo extrapolation) was employed to convert BMCs into administered equivalent doses (AEDs). Where possible, AEDs were compared to points of departure (PODs) for traditional genotoxicity endpoints; AEDs were generally lower than PODs based on in vivo endpoints. To facilitate interpretation of in vitro MN assay concentration-response data for risk assessment, exposure estimates were utilized to calculate bioactivity exposure ratio (BER) values. BERs for 50 clastogens and two aneugens had AEDs that approached exposure estimates (i.e., BER < 100); these chemicals might be considered priorities for additional testing. This work provides a framework for the use of high-throughput in vitro genotoxicity testing for priority setting and chemical risk assessment.

A new imaging platform (iScreen) allows for the concurrent assessment of micronucleus induction and genotoxic mode of action in human A375 cells

Genotoxicity testing guidelines require the assessment of the clastogenic and aneugenic potential of compounds. While in vitro micronucleus assays detect both types of endpoints, it requires labor-intensive microscopic scoring and does not discriminate between the two modes of actions. Here, we present a novel high-content imaging platform in A375 human cells that addresses the need for rapid scoring while providing additional mechanistic information. We evaluated the new platform with 12 compounds, three compounds from each mechanistic class (clastogen, aneugen tubulin binder, aneugen aurora inhibitor, and nongenotoxicant) following 4- and 24-h compound treatments. The approach we developed is first discriminating between genotoxicant and nongenotoxicant using an image analysis algorithm to quantify micronucleus induction below a 60% cytotoxicity cutoff. Then it uses centromere protein A (CENPA) staining for the genotoxic compounds to discriminate between aneugens and clastogens. Lastly, we use phosphorylated histone H2AX Ser139 (γH2AX) staining to confirm clastogenicity and changes in phosphorylated histone 3 Ser10 (pH 3) and increases in polyploidy in mitotic cells to discriminate between aneugens that bind tubulin from those that affect aurora kinases. All compounds were correctly classified, and we showed by using benchmark dose-response analysis that the imaging platform in A375 cells is at least as sensitive as the MicroFlow® assay in TK6 cells for genotoxicant but appears to be more specific for the nongenotoxicants. A detailed comparison of the cell lines and a more comprehensive validation with a much larger compound set, predictive and dose-response modeling will be presented in the future.

In vitro human cell-based aneugen molecular mechanism assay

This laboratory previously described an in vitro human cell-based assay and data analysis scheme that discriminates common molecular targets responsible for chemical-induced in vitro aneugenicity: tubulin destabilization, tubulin stabilization, and inhibition of Aurora kinases (Bernacki et al., Toxicol. Sci. 170 [2019] 382-393). The current report describes updated procedures that simplify benchtop processing and data analysis methods. For these experiments, human lymphoblastoid TK6 cells were exposed to each of 25 aneugens over a range of concentrations in the presence of fluorescent paclitaxel (488 Taxol). After a 4 h treatment period, cells were lysed and nuclei were stained with a nucleic acid dye and labeled with fluorescent antibodies against phospho-histone H3 (p-H3). Flow cytometric analyses revealed several unique signatures: tubulin stabilizers caused increased frequencies of p-H3-positive events with concentration-dependent increases in 488 Taxol-associated fluorescence; tubulin destabilizers caused increased frequencies of p-H3-positive events with concomitant decreases in 488 Taxol-associated fluorescence; and Aurora kinase B inhibitors caused reduced frequencies of p-H3-positive events and lower median fluorescent intensities of p-H3-positive events. These results demonstrate a simple rubric based on 488 Taxol- and p-H3-associated metrics can reliably discriminate between several commonly encountered aneugenic molecular mechanisms.

Implementing in vitro bioactivity data to modernize priority setting of chemical inventories

Internationally, there are thousands of existing and newly introduced chemicals in commerce, highlighting the ongoing importance of innovative approaches to identify emerging chemicals of concern. For many chemicals, there is a paucity of hazard and exposure data. Thus, there is a crucial need for efficient and robust approaches to address data gaps and support risk-based prioritization. Several studies have demonstrated the utility of in vitro bioactivity data from the ToxCast program in deriving points of departure (PODs). ToxCast contains data for nearly 1,400 endpoints per chemical, and the bioactivity concentrations, indicative of potential adverse outcomes, can be converted to human-equivalent PODs using high-throughput toxicokinetics (HTTK) modeling. However, data gaps need to be addressed for broader application: the limited chemical space of HTTK and quantitative high-throughput screening data. Here we explore the applicability of in silico models to address these data needs. Specifically, we used ADMET predictor for HTTK predictions and a generalized read-across approach to predict ToxCast bioactivity potency. We applied these models to profile 5,801 chemicals on Canada’s Domestic Substances List (DSL). To evaluate the approach’s performance, bioactivity PODs were compared with in vivo results from the EPA Toxicity Values database for 1,042 DSL chemicals. Comparisons demonstrated that the bioac­tivity PODs, based on ToxCast data or read-across, were conservative for 95% of the chemicals. Comparing bioactivity PODs to human exposure estimates supports the identification of chemicals of potential interest for further work. The bioac­tivity workflow shows promise as a powerful screening tool to support effective triaging of chemical inventories.

Biomarkers of DNA damage response improve in vitro micronucleus assays by revealing genotoxic mode of action and reducing the occurrence of irrelevant positive results

We have previously described two flow cytometry-based in vitro genotoxicity tests: micronucleus (MN) scoring (MicroFlow®) and a multiplexed DNA damage response biomarker assay (MultiFlow®). Here, we describe a strategy for combining the assays in order to efficiently supplement MN analyses with a panel of biomarkers that comment on cytotoxicity (i.e. relative nuclei count, relative increased nuclei count, cleaved PARP-positive chromatin and ethidium monoazide-positive chromatin) and genotoxic mode of action (MoA; i.e. γH2AX, phospho-histone H3, p53 activation and polyploidy). For these experiments, human TK6 cells were exposed to each of 32 well-studied reference chemicals in 96-well plates for 24 continuous hours. The test chemicals were evaluated over a range of concentrations in the presence and absence of a rat liver S9-based metabolic activation system. MultiFlow assay data were acquired at 4 and 24 h, and micronuclei were scored at 24 h. Testing 32 chemicals in two metabolic activation arms translated into 64 a priori calls: 42 genotoxicants and 22 non-genotoxicants. The MN assay showed high sensitivity and moderate specificity (90% and 68%, respectively). When a genotoxic call required significant MN and MultiFlow responses, specificity increased to 95% without adversely affecting sensitivity. The dose-response data were analysed with PROAST Benchmark Dose (BMD) software in order to calculate potency metrics for each endpoint, and ToxPi software was used to synthesise the resulting lower and upper bound 90% confidence intervals into visual profiles. The BMD/ToxPi combination was found to represent a powerful strategy for synthesising multiple BMD confidence intervals, as the software output provided MoA information as well as insights into genotoxic potency.

In Silico Approaches In Carcinogenicity Hazard Assessment: Current Status and Future Needs

Historically, identifying carcinogens has relied primarily on tumor studies in rodents, which require enormous resources in both money and time. In silico models have been developed for predicting rodent carcinogens but have not yet found general regulatory acceptance, in part due to the lack of a generally accepted protocol for performing such an assessment as well as limitations in predictive performance and scope. There remains a need for additional, improved in silico carcinogenicity models, especially ones that are more human-relevant, for use in research and regulatory decision-making. As part of an international effort to develop in silico toxicological protocols, a consortium of toxicologists, computational scientists, and regulatory scientists across several industries and governmental agencies evaluated the extent to which in silico models exist for each of the recently defined 10 key characteristics (KCs) of carcinogens. This position paper summarizes the current status of in silico tools for the assessment of each KC and identifies the data gaps that need to be addressed before a comprehensive in silico carcinogenicity protocol can be developed for regulatory use.

Recent advances in γH2AX biomarker-based genotoxicity assays: A marker of DNA damage and repair

The phosphorylation of histone variant H2AX and formation of γH2AX is a primary response to the DNA double-strand breaks (DSBs). Detection of γH2AX is a robust and sensitive tool for diagnosis of DNA damage and repair in pre-clinical drug discovery investigations. In addition, the replication stress also leads to the formation of γH2AX and cell death and so γH2AX can serve as a surrogate marker of drug-induced cytotoxicity. Recent advances in genomic research offer an opportunity to detect γH2AX as a specific biomarker for quantitative analysis of DNA damages and repair using high content screening technology and quantitative imaging analysis. The proposed approaches identify a wide range of genetic disorders and are applied in combination with other assays in drug discovery and also for the evaluation of the efficacy of various developmental drugs. In the current review, we provide recent insights into the potential of γH2AX biomarker as a powerful tool in genotoxicity analyses for the monitoring and managing of cancer diseases.

The in vitro ToxTracker and Aneugen Clastogen Evaluation extension assay as a tool in the assessment of relative genotoxic potential of e-liquids and their aerosols

In vitro (geno)toxicity assessment of electronic vapour products (EVPs), relative to conventional cigarette, currently uses assays, including the micronucleus and Ames tests. Whilst informative on induction of a finite endpoint and relative risk posed by test articles, such assays could benefit from mechanistic supplementation. The ToxTracker and Aneugen Clastogen Evaluation analysis can indicate the activation of reporters associated with (geno)toxicity, including DNA damage, oxidative stress, the p53-related stress response and protein damage. Here, we tested for the different effects of a selection of neat e-liquids, EVP aerosols and Kentucky reference 1R6F cigarette smoke samples in the ToxTracker assay. The assay was initially validated to assess whether a mixture of e-liquid base components, propylene glycol (PG) and vegetable glycerine (VG) had interfering effects within the system. This was achieved by spiking three positive controls into the system with neat PG/VG or phosphate-buffered saline bubbled (bPBS) PG/VG aerosol (nicotine and flavour free). PG/VG did not greatly affect responses induced by the compounds. Next, when compared to cigarette smoke samples, neat e-liquids and bPBS aerosols (tobacco flavour; 1.6% freebase nicotine, 1.6% nicotine salt or 0% nicotine) exhibited reduced and less complex responses. Tested up to a 10% concentration, EVP aerosol bPBS did not induce any ToxTracker reporters. Neat e-liquids, tested up to 1%, induced oxidative stress reporters, thought to be due to their effects on osmolarity in vitro. E-liquid nicotine content did not affect responses induced. Additionally, spiking nicotine alone only induced an oxidative stress response at a supraphysiological level. In conclusion, the ToxTracker assay is a quick, informative screen for genotoxic potential and mechanisms of a variety of (compositionally complex) samples, derived from cigarettes and EVPs. This assay has the potential for future application in the assessment battery for next-generation (smoking alternative) products, including EVPs.

A deep neural network-based approach for prediction of mutagenicity of compounds

We are exposed to various chemical compounds present in the environment, cosmetics, and drugs almost every day. Mutagenicity is a valuable property that plays a significant role in establishing a chemical compound's safety. Exposure and handling of mutagenic chemicals in the environment pose a high health risk; therefore, identification and screening of these chemicals are essential. Considering the time constraints and the pressure to avoid laboratory animals' use, the shift to alternative methodologies that can establish a rapid and cost-effective detection without undue over-conservation seems critical. In this regard, computational detection and identification of the mutagens in environmental samples like drugs, pesticides, dyes, reagents, wastewater, cosmetics, and other substances is vital. From the last two decades, there have been numerous efforts to develop the prediction models for mutagenicity, and by far, machine learning methods have demonstrated some noteworthy performance and reliability. However, the accuracy of such prediction models has always been one of the major concerns for the researchers working in this area. The mutagenicity prediction models were developed using deep neural network (DNN), support vector machine, k-nearest neighbor, and random forest. The developed classifiers were based on 3039 compounds and validated on 1014 compounds; each of them encoded with 1597 molecular feature vectors. DNN-based prediction model yielded highest prediction accuracy of 92.95% and 83.81% with the training and test data, respectively. The area under the receiver's operating curve and precision-recall curve values were found to be 0.894 and 0.838, respectively. The DNN-based classifier not only fits the data with better performance as compared to traditional machine learning algorithms, viz., support vector machine, k-nearest neighbor, and random forest (with and without feature reduction) but also yields better performance metrics. In current work, we propose a DNN-based model to predict mutagenicity of compounds.

The use of benchmark dose uncertainty measurements for robust comparative potency analyses

The Benchmark Dose (BMD) method is the favored approach for quantitative dose-response analysis where uncertainty measurements are delineated between the upper (BMDU) and lower (BMDL) confidence bounds, or confidence intervals (CIs). Little has been published on the accurate interpretation of uncertainty measurements for potency comparative analyses between different test conditions. We highlight this by revisiting a previously published comparative in vitro genotoxicity dataset for human lymphoblastoid TK6 cells that were exposed to each of 10 clastogens in the presence and absence (+/-) of low concentration (0.25%) S9, and scored for p53, γH2AX and Relative Nuclei Count (RNC) responses at two timepoints (Tian et al., 2020). The researchers utilized BMD point estimates in potency comparative analysis between S9 treatment conditions. Here we highlight a shortcoming that the use of BMD point estimates can mischaracterize potency differences between systems. We reanalyzed the dose responses by BMD modeling using PROAST v69.1. We used the resulting BMDL and BMDU metrics to calculate "S9 potency ratio confidence intervals" that compare the relative potency of compounds +/- S9 as more statistically robust metrics for comparative potency measurements compared to BMD point estimate ratios. We performed unsupervised hierarchical clustering that identified four S9-dependent groupings: high and low-level potentiation, no effect, and diminution. This work demonstrates the importance of using BMD uncertainty measurements in potency comparative analyses between test conditions. Irrespective of the source of the data, we propose a stepwise approach when performing BMD modeling in comparative potency analyses between test conditions.

Experiments in the EpiDerm 3D Skin In Vitro Model and Minipigs In Vivo Indicate Comparatively Lower In Vivo Skin Sensitivity of Topically Applied Aneugenic Compounds

Risk management of in vitro aneugens for topically applied compounds is not clearly defined because there is no validated methodology to accurately measure compound concentration in proliferating stratum basale keratinocytes of the skin. Here, we experimentally tested several known aneugens in the EpiDerm reconstructed human skin in vitro micronucleus assay and compared the results to flow cytometric mechanistic biomarkers (phospho-H3; MPM2, DNA content). We then evaluated similar biomarkers (Ki-67, nuclear area) using immunohistochemistry in skin sections of minipigs following topical exposure the potent aneugens, colchicine, and hesperadin. Data from the EpiDerm model showed positive micronucleus responses for all aneugens tested following topical or direct media dosing with similar sensitivity when adjusted for applied dose. Quantitative benchmark dose-response analysis exhibited increases in the mitotic index biomarkers phospho-H3 and MPM2 for tubulin binders and polyploidy for aurora kinase inhibitors are at least as sensitive as the micronucleus endpoint. By comparison, the aneugens tested did not induce histopathological changes, increases in Ki-67 immunolabeling or nuclear area in skin sections from the in vivo minipig study at doses in significant excess of those eliciting a response in vitro. Results indicate the EpiDerm in vitro micronucleus assay is suitable for the hazard identification of aneugens. The lack of response in the minipig studies indicates that the barrier function of the minipig skin, which is comparable to human skin, protects from the effects of aneugens in vivo. These results provide a basis for conducting additional studies in the future to further refine this understanding.

Absence of hydroxyurea-induced mutational effects supports higher utilisation for the treatment of sickle cell anaemia

Hydroxyurea (hydroxycarbamide) is approved for treating both children and adults with sickle cell anaemia (SCA). Fetal haemoglobin (HbF) induction is the primary treatment response, along with improved anaemia, reduced haemolysis, myelosuppression and decreased endothelial inflammation. Hydroxyurea has proven clinical efficacy for SCA - treatment significantly reduces disease manifestations and prolongs survival. Despite these recognised benefits, long-standing concerns regarding the risks of mutagenic and potentially carcinogenic drug exposure have hampered efforts for broad hydroxyurea use in SCA, although these are based largely on outdated experimental models and treatment experiences with myeloproliferative neoplasms. Consequently, many patients with SCA are not receiving this highly effective disease-modifying therapy. In this review, we describe the concept of genotoxicity and its laboratory measurements, summarise hydroxyurea-associated data from both preclinical and clinical studies, and discuss carcinogenic potential. The genotoxicity results clearly demonstrate that hydroxyurea does not directly bind DNA and is not mutagenic. Rather, its genotoxic effects are limited to indirect clastogenicity occurring in select cell types, and only when high dose and time thresholds are exceeded. This absence of mutagenic activity is consistent with the observed lack of any compelling carcinogenic potential. Since hydroxyurea therapy for SCA carries minimal carcinogenic risks, the current drug labelling should be modified accordingly, and prescribing practices should be broadened to allow better access and increased utilisation of this highly effective drug.

Performance of HepaRG and HepG2 cells in the high-throughput micronucleus assay for in vitro genotoxicity assessment

The micronucleus (MN) assay is a core test used to evaluate genotoxic potential of xenobiotics. The traditional in vitro MN assay is usually conducted in cells lacking metabolic competency or by supplementing cultures with an exogenous rat S9 metabolic system, which creates a significant assay limitation for detecting genotoxic metabolites. Our previous study demonstrated that compared to HepG2, HepaRG cells exhibited a significantly higher level of CYP450 enzyme activities and detected a greater portion of genotoxic carcinogens requiring metabolic activation using the Comet assay. The aim of this study was to assess the performance of HepaRG cells in the flow cytometry-based MN assay by testing 28 compounds with known genotoxic or carcinogenic modes of action (MoA). HepaRG cells exhibited higher sensitivity (83%) than HepG2 cells (67%) in detecting 12 indirect-acting genotoxicants or carcinogens. The HepaRG MN assay was 100% specific and 93% accurate in detecting genotoxic potential of the 28 compounds. Quantitative comparison of the MN concentration-response data using benchmark dose analysis showed that most of the tested compounds induced higher % MN in HepaRG than HepG2 cells. In addition, HepaRG cells were compatible with the Multiflow DNA damage assay, which predicts the genotoxic MoA of compounds tested. These results suggest that high-throughput flow cytometry-based MN assay may be adapted using HepaRG cells for genotoxicity assessment, and that HepaRG cells appear to be more sensitive than HepG2 cells in detecting genotoxicants or carcinogens that require metabolic activation.

In vitro and in silico genetic toxicity screening of flavor compounds and other ingredients in tobacco products with emphasis on ENDS

Electronic nicotine delivery systems (ENDS) are regulated tobacco products and often contain flavor compounds. Given the concern of increased use and the appeal of ENDS by young people, evaluating the potential of flavors to induce DNA damage is important for health hazard identification. In this study, alternative methods were used as prioritization tools to study the genotoxic mode of action (MoA) of 150 flavor compounds. In particular, clastogen-sensitive (γH2AX and p53) and aneugen-sensitive (p-H3 and polyploidy) biomarkers of DNA damage in human TK6 cells were aggregated through a supervised three-pronged ensemble machine learning prediction model to prioritize chemicals based on genotoxicity. In addition, in silico quantitative structure-activity relationship (QSAR) models were used to predict genotoxicity and carcinogenic potential. The in vitro assay identified 25 flavors as positive for genotoxicity: 15 clastogenic, eight aneugenic and two with a mixed MoA (clastogenic and aneugenic). Twenty-three of these 25 flavors predicted to induce DNA damage in vitro are documented in public literature to be in e-liquid or in the aerosols produced by ENDS products with youth-appealing flavors and names. QSAR models predicted 46 (31%) of 150 compounds having at least one positive call for mutagenicity, clastogenicity or rodent carcinogenicity, 49 (33%) compounds were predicted negative for all three endpoints, and remaining compounds had no prediction call. The parallel use of these predictive technologies to elucidate MoAs for potential genetic damage, hold utility as a screening strategy. This study is the first high-content and high-throughput genotoxicity screening study with an emphasis on flavors in ENDS products.

Aneugen Versus Clastogen Evaluation and Oxidative Stress-Related Mode-of-Action Assessment of Genotoxic Compounds Using the ToxTracker Reporter Assay

Understanding the mode-of-action (MOA) of genotoxic compounds and differentiating between direct DNA interaction and indirect genotoxicity is crucial for their reliable safety assessment. ToxTracker is a stem cell-based reporter assay that detects activation of various cellular responses that are associated with genotoxicity and cancer. ToxTracker consists of 6 different GFP reporter cell lines that can detect the induction of DNA damage, oxidative stress, and protein damage in a single test. The assay can thereby provide insight into the MOA of compounds. Genotoxicity is detected in ToxTracker by activation of 2 independent GFP reporters. Activation of the Bscl2-GFP reporter is associated with induction of DNA adducts and subsequent inhibition of DNA replication and the Rtkn-GFP reporter is activated following the formation of DNA double-strand breaks. Here, we show that the differential activation of these 2 genotoxicity reporters could be used to further differentiate between a DNA reactive and clastogenic or a non-DNA-reactive aneugenic MOA of genotoxic compounds. For further classification of aneugenic and clastogenic compounds, the ToxTracker assay was extended with cell cycle analysis and aneuploidy assessment. The extension was validated using a selection of 16 (genotoxic) compounds with a well-established MOA. Furthermore, indirect genotoxicity related to the production of reactive oxygen species was investigated using the DNA damage and oxidative stress ToxTracker reporters in combination with different reactive oxygen species scavengers. With these new extensions, ToxTracker was able to accurately classify compounds as genotoxic or nongenotoxic and could discriminate between DNA-reactive compounds, aneugens, and indirect genotoxicity caused by oxidative stress.

Image analysis of mechanistic protein biomarkers for the characterization of genotoxicants: Aneugens, clastogens, and reactive oxygen species inducers

The early detection of genotoxicity contributes to cutting-edge drug discovery and development, requiring effective identification of genotoxic hazards posed by drugs while providing mode of action (MoA) information in a high throughput manner. In other words, there is a need to complement standard genotoxicity testing according to the test battery given in ICH S2(R1) with new in vitro tools, thereby contributing to a more in-depth analysis of genotoxic effects. Here, we report on a proof-of-concept MoA approach based on post-translational modifications of proteins (PTMs) indicative of clastogenic and aneugenic effects in TK6 cells using imaging technology (with automated analysis). Cells were exposed in a 96-well plate format with a panel of reference (geno)toxic compounds and subsequently analyzed at 4 and 24 hr to detect dose-dependent changes in PTMs, relevant for mechanistic analysis. All tested compounds that interfere with the spindle apparatus yielded a BubR1 (S640) (3/3) and phospho-histone H3 (S28) (7/9) positive dose-response reflecting aneugenicity, whereas compounds inducing DNA double-strand-breaks were associated with positive FANCD2 (S1404) and 53BP1 (S1778) responses pointing to clastogenicity (2/3). The biomarker p53 (K373) was able to distinguish genotoxicants from non-genotoxicants (2/4), while the induction of reactive oxygen species (ROS), potentially causing DNA damage, was associated with a positive Nrf2 (S40) response (2/2). This work demonstrates that genotoxicants and non-genotoxicants induce different biomarker responses in TK6 cells which can be used for reliable classification into MoA groups (aneugens/clastogens/non-genotoxicants/ROS inducers), supporting a more in-depth safety assessment of drug candidates.

3Rs-friendly approach to exogenous metabolic activation that supports high-throughput genetic toxicology testing

MultiFlow® DNA Damage-p53, γH2AX, Phospho-Histone H3 is a miniaturized, flow cytometry-based assay that provides genotoxic mode of action information by distinguishing clastogens, aneugens, and nongenotoxicants. Work to date has focused on the p53-competent human cell line TK6. While mammalian cell genotoxicity assays typically supply exogenous metabolic activation in the form of concentrated rat liver S9, this is a less-than-ideal approach for several reasons, including 3Rs considerations. Here, we describe our experiences with low concentration S9 and saturating co-factors which were allowed to remain in contact with cells and test chemicals for 24 continuous hours. We exposed TK6 cells in 96-well plates to each of 15 reference chemicals over a range of concentrations, both in the presence and absence of 0.25% v/v phenobarbital/β-naphthoflavone-induced rat liver S9. After 4 and 24 hr of treatment cell aliquots were added to wells of a microtiter plate containing the working detergent/stain/antibody cocktail. After a brief incubation robotic sampling was employed for walk-away flow cytometric data acquisition. PROAST benchmark dose (BMD) modeling was used to characterize the resulting dose-response curves. For each of the 8 reference pro-genotoxicants studied, relative nuclei count, γH2AX, and/or p53 biomarker BMD values were order(s) of magnitude lower for 0.25% S9 conditions compared to 0% S9. Conversely, several of the direct-acting reference chemicals exhibited appreciably lower cytotoxicity and/or genotoxicity BMD values in the presence of S9 (eg, resorcinol). These results prove the efficacy of the low concentration S9 system, and indicate that an efficient and highly scalable multiplexed assay can effectively identify chemicals that require bioactivation to exert their genotoxic effects.

Benchmark Dose Analysis of DNA Damage Biomarker Responses Provides Compound Potency and Adverse Outcome Pathway Information for the Topoisomerase II Inhibitor Class of Compounds

Genetic toxicology data have traditionally been utilized for hazard identification to provide a binary call for a compound's risk. Recent advances in the scientific field, especially with the development of high-throughput methods to quantify DNA damage, have influenced a change of approach in genotoxicity assessment. The in vitro MultiFlow® DNA Damage Assay is one such method which multiplexes γH2AX, p53, phospho-histone H3 biomarkers into a single-flow cytometric analysis (Bryce et al., [2016]: Environ Mol Mutagen 57:546-558). This assay was used to study human TK6 cells exposed to each of eight topoisomerase II poisons for 4 and 24 hr. Using PROAST v65.5, the Benchmark Dose approach was applied to the resulting flow cytometric datasets. With "compound" serving as covariate, all eight compounds were combined into a single analysis, per time point and endpoint. The resulting 90% confidence intervals, plotted in Log scale, were considered as the potency rank for the eight compounds. The in vitro MultiFlow data showed a maximum confidence interval span of 1Log, which indicates data of good quality. Patterns observed in the compound potency rank were scrutinized by using the expert rule-based software program Derek Nexus, developed by Lhasa Limited. Compound sub-classification and structural alerts were considered contributory to the potencies observed for the topoisomerase II poisons studied herein. The Topo II poison Adverse Outcome Pathway was evaluated with MultiFlow endpoints serving as Key Events. The step-wise approach described herein can be considered as a foundation for risk assessment of compounds within a specific mode of action of interest. Environ. Mol. Mutagen. 2020. © 2020 Wiley Periodicals, Inc.

Considerations for the Use of Mutation as a Regulatory Endpoint in Risk Assessment

Assessment of a chemical's potential to cause permanent changes in the genetic code has been a common practice in the industry and regulatory settings for decades. Furthermore, the genetic toxicity battery of tests has typically been employed during the earliest stages of the research and development programs of new product development. A positive outcome from such battery has a major impact on the chemical's utility, industrial hygiene, product stewardship practices, and product life cycle analysis, among many other decisions that need to be taken by the industry, even before the registration of a chemical is undertaken. Under the prevailing regulatory paradigm, the dichotomous (yes/no) evaluation of the chemical's genotoxic potential leads to a conservative, linear no-threshold (LNT) risk assessment, unless compelling and undeniable data to the contrary can be provided to satisfy regulators, typically in a number of different global jurisdictions. With the current advent of predictive methods, new testing paradigms, mode-of-action/adverse outcome pathways, and quantitative risk assessment approaches, various stakeholders are starting to employ these state-of-the-science methodologies to further the conversation on decision making and advance the regulatory paradigm beyond the dominant LNT status quo. This commentary describes these novel methodologies, relevant biological responses, and how these can affect internal and regulatory risk assessment approaches. Environ. Mol. Mutagen. 61:84-93, 2020. © 2019 Wiley Periodicals, Inc.

Application of the adverse outcome pathway framework to genotoxic modes of action

In May 2017, the Health and Environmental Sciences Institute's Genetic Toxicology Technical Committee hosted a workshop to discuss whether mode of action (MOA) investigation is enhanced through the application of the adverse outcome pathway (AOP) framework. As AOPs are a relatively new approach in genetic toxicology, this report describes how AOPs could be harnessed to advance MOA analysis of genotoxicity pathways using five example case studies. Each of these genetic toxicology AOPs proposed for further development includes the relevant molecular initiating events, key events, and adverse outcomes (AOs), identification and/or further development of the appropriate assays to link an agent to these events, and discussion regarding the biological plausibility of the proposed AOP. A key difference between these proposed genetic toxicology AOPs versus traditional AOPs is that the AO is a genetic toxicology endpoint of potential significance in risk characterization, in contrast to an adverse state of an organism or a population. The first two detailed case studies describe provisional AOPs for aurora kinase inhibition and tubulin binding, leading to the common AO of aneuploidy. The remaining three case studies highlight provisional AOPs that lead to chromosome breakage or mutation via indirect DNA interaction (inhibition of topoisomerase II, production of cellular reactive oxygen species, and inhibition of DNA synthesis). These case studies serve as starting points for genotoxicity AOPs that could ultimately be published and utilized by the broader toxicology community and illustrate the practical considerations and evidence required to formalize such AOPs so that they may be applied to genetic toxicity evaluation schemes. Environ. Mol. Mutagen. 61:114-134, 2020. © 2019 Wiley Periodicals, Inc.

Evidence for an Aneugenic Mechanism of Action for Micronucleus Induction by Black Cohosh Extract

Black cohosh extract (BCE) is a popular botanical dietary supplement marketed to relieve symptoms of various gynecological ailments. Studies conducted by the National Toxicology Program (NTP) showed that BCE induces micronucleated erythrocytes in female rats and mice. Subsequently, the NTP showed that a variety of BCEs, including the sample that induced micronuclei (MN) in vivo ("NTP BCE") had a similar effect in human TK6 cells. Further testing with the MultiFlow® DNA Damage Assay revealed that TK6 cells exposed to NTP BCE, as well as a BCE reference material (BC XRM), exhibited a signature consistent with aneugenic activity in TK6 cells. Results from experiments reported herein confirmed these in vitro observations with NTP BCE and BC XRM. We extended these studies to include a novel test system, the MultiFlow Aneugen Molecular Mechanism Assay. For these experiments, TK6 cells were exposed to NTP BCE and BC XRM over a range of concentrations in the presence of fluorescent Taxol (488 Taxol). After 4 h, nuclei from lysed cells were stained with a nucleic acid dye and labeled with fluorescent antibodies against phospho-histone H3 (p-H3) and Ki-67. Whereas BCEs did not affect p-H3:Ki-67 ratios (a signature of aneugenic mitotic kinase inhibitors), 488 Taxol-associated fluorescence (a tubulin binder-sensitive endpoint) was affected. More specifically, 488 Taxol-associated fluorescence was reduced over the same concentration range that was previously observed to induce MN. These results provide direct evidence that BCEs destabilize microtubules in vitro, and this is the molecular mechanism responsible for the aneugenicity findings. Environ. Mol. Mutagen. 2019. © 2019 The Authors. Environmental and Molecular Mutagenesis published by Wiley Periodicals, Inc. on behalf of Environmental Mutagen Society.

Baseline effects of non-flavored e-liquids in the in vitro micronucleus assay

Electronic nicotine delivery systems (ENDSs; e.g. e-cigarettes) are being developed as potentially reduced-risk alternatives to the continued use of conventional tobacco products. They typically comprise a device that heats an e-liquid to generate inhalable vapor. E-liquids and ENDS-derived vapor have been the focus of toxicological assessment; in particular, their DNA-damaging potential has been investigated with varying outcomes and conclusions. In vitro genetic toxicology assays have formed a part of these assessments. However, they are susceptible to producing misleading or false positive results, especially under extreme conditions. In the present study, we evaluated a series of six neat (non-vaporized) non-flavored e-liquids (NFEL-A to F) in a flow cytometry version of the in vitro micronucleus assay in order to characterize their baseline effects on Chinese hamster ovary cells under hazard identification conditions. The NFELs induced cytotoxicity universally despite differing in propylene glycol (PG), vegetable glycerin (VG), and nicotine content. In addition, significant genotoxic responses were also detected with the PG-predominant e-liquids NFEL-A, D, and F but not with NFEL-B, C, or E, which contained higher proportions of VG. All six NFELs induced extreme cell culture conditions (i.e. increases in pH and osmolality) at the concentrations assessed. They also exhibited nonbiologically relevant effects on the mechanistic endpoints (i.e. cell cycle and phosphorylated histones H2AX and H3). In conclusion, although the PG component of the NFELs drove micronucleus formation in the assay, data on the complementary mechanistic endpoints suggest that this apparent DNA damage is potentially misleading and of negligible biological relevance as a risk for DNA integrity. In future assessments, any adverse changes (such as signatures of micronuclei induction, G2M arrest, and increases in γH2AX) relative to this reference data set might indicate a possible genotoxic hazard and would prompt further investigations for exploring the extent of risk.

Genetic toxicology in silico protocol

In silico toxicology (IST) approaches to rapidly assess chemical hazard, and usage of such methods is increasing in all applications but especially for regulatory submissions, such as for assessing chemicals under REACH as well as the ICH M7 guideline for drug impurities. There are a number of obstacles to performing an IST assessment, including uncertainty in how such an assessment and associated expert review should be performed or what is fit for purpose, as well as a lack of confidence that the results will be accepted by colleagues, collaborators and regulatory authorities. To address this, a project to develop a series of IST protocols for different hazard endpoints has been initiated and this paper describes the genetic toxicity in silico (GIST) protocol. The protocol outlines a hazard assessment framework including key effects/mechanisms and their relationships to endpoints such as gene mutation and clastogenicity. IST models and data are reviewed that support the assessment of these effects/mechanisms along with defined approaches for combining the information and evaluating the confidence in the assessment. This protocol has been developed through a consortium of toxicologists, computational scientists, and regulatory scientists across several industries to support the implementation and acceptance of in silico approaches.

Aneugen Molecular Mechanism Assay: Proof-of-Concept With 27 Reference Chemicals

A tiered bioassay and data analysis scheme is described for elucidating the most common molecular targets responsible for chemical-induced in vitro aneugenicity: tubulin destabilization, tubulin stabilization, and inhibition of mitotic kinase(s). To evaluate this strategy, TK6 cells were first exposed to each of 27 presumed aneugens over a range of concentrations. After 4 and 24 h of treatment, γH2AX, p53, phospho-histone H3 (p-H3), and polyploidization biomarkers were evaluated using the MultiFlow DNA Damage Assay Kit. The assay identified 27 of 27 chemicals as genotoxic, with 25 exhibiting aneugenic signatures, 1 aneugenic and clastogenic, and 1 clastogenic. Subsequently, a newly described follow-up assay was employed to investigate the aneugenic agents' molecular targets. For these experiments, TK6 cells were exposed to each of 26 chemicals in the presence of 488 Taxol. After 4 h, cells were lysed and the liberated nuclei and mitotic chromosomes were stained with a nucleic acid dye and labeled with fluorescent antibodies against p-H3 and Ki-67. Flow cytometric analyses revealed that alterations to 488 Taxol-associated fluorescence were only observed with tubulin binders-increases in the case of tubulin stabilizers, decreases with destabilizers. Mitotic kinase inhibitors with known Aurora kinase B inhibiting activity were the only aneugens that dramatically decreased the ratio of p-H3-positive to Ki-67-positive nuclei. Unsupervised hierarchical clustering based on 488 Taxol fluorescence and p-H3: Ki-67 ratios clearly distinguished compounds with these disparate molecular mechanisms. Furthermore, a classification algorithm based on an artificial neural network was found to effectively predict molecular target, as leave-one-out cross-validation resulted in 25/26 agreement with a priori expectations. These results are encouraging, as they suggest that an adequate number of training set chemicals, in conjunction with a machine learning algorithm based on 488 Taxol, p-H3, and Ki-67 responses, can reliably elucidate the most commonly encountered aneugenic molecular targets.

Predictions of genotoxic potential, mode of action, molecular targets, and potency via a tiered multiflow® assay data analysis strategy

The in vitro MultiFlow® DNA Damage Assay multiplexes γH2AX, p53, phospho-histone H3, and polyploidization biomarkers into a single flow cytometric analysis. The current report describes a tiered sequential data analysis strategy based on data generated from exposure of human TK6 cells to a previously described 85 chemical training set and a new pharmaceutical-centric test set (n = 40). In each case, exposure was continuous over a range of closely spaced concentrations, and cell aliquots were removed for analysis following 4 and 24 hr of treatment. The first data analysis step focused on chemicals' genotoxic potential, and for this purpose, we evaluated the performance of a machine learning (ML) ensemble, a rubric that considered fold increases in biomarkers against global evaluation factors (GEFs), and a hybrid strategy that considered ML and GEFs. This first tier further used ML output and/or GEFs to classify genotoxic activity as clastogenic and/or aneugenic. Test set results demonstrated the generalizability of the first tier, with particularly good performance from the ML ensemble: 35/40 (88%) concordance with a priori genotoxicity expectations and 21/24 (88%) agreement with expected mode of action (MoA). A second tier applied unsupervised hierarchical clustering to the biomarker response data, and these analyses were found to group certain chemicals, especially aneugens, according to their molecular targets. Finally, a third tier utilized benchmark dose analyses and MultiFlow biomarker responses to rank genotoxic potency. The relevance of these rankings is supported by the strong agreement found between benchmark dose values derived from MultiFlow biomarkers compared to those generated from parallel in vitro micronucleus analyses. Collectively, the results suggest that a tiered MultiFlow data analysis pipeline is capable of rapidly and effectively identifying genotoxic hazards while providing additional information that is useful for modern risk assessments-MoA, molecular targets, and potency. Environ. Mol. Mutagen. 60:513-533, 2019. © 2019 Wiley Periodicals, Inc.

Identifying Compounds with Genotoxicity Potential Using Tox21 High-Throughput Screening Assays

Genotoxicity is a critical component of a comprehensive toxicological profile. The Tox21 Program used five quantitative high-throughput screening (qHTS) assays measuring some aspect of DNA damage/repair to provide information on the genotoxic potential of over 10 000 compounds. Included were assays detecting activation of p53, increases in the DNA repair protein ATAD5, phosphorylation of H2AX, and enhanced cytotoxicity in DT40 cells deficient in DNA-repair proteins REV3 or KU70/RAD54. Each assay measures a distinct component of the DNA damage response signaling network; >70% of active compounds were detected in only one of the five assays. When qHTS results were compared with results from three standard genotoxicity assays (bacterial mutation, in vitro chromosomal aberration, and in vivo micronucleus), a maximum of 40% of known, direct-acting genotoxicants were active in one or more of the qHTS genotoxicity assays, indicating low sensitivity. This suggests that these qHTS assays cannot in their current form be used to replace traditional genotoxicity assays. However, despite the low sensitivity, ranking chemicals by potency of response in the qHTS assays revealed an enrichment for genotoxicants up to 12-fold compared with random selection, when allowing a 1% false positive rate. This finding indicates these qHTS assays can be used to prioritize chemicals for further investigation, allowing resources to focus on compounds most likely to induce genotoxic effects. To refine this prioritization process, models for predicting the genotoxicity potential of chemicals that were active in Tox21 genotoxicity assays were constructed using all Tox21 assay data, yielding a prediction accuracy up to 0.83. Data from qHTS assays related to stress-response pathway signaling (including genotoxicity) were the most informative for model construction. By using the results from qHTS genotoxicity assays, predictions from models based on qHTS data, and predictions from commercial bacterial mutagenicity QSAR models, we prioritized Tox21 chemicals for genotoxicity characterization.

Comparative Genotoxicity of TEMPO and 3 of Its Derivatives in Mouse Lymphoma Cells

TEMPO (2, 2, 6, 6-tetramethylphiperidine-1-oxyl) and its derivatives are stable free radical nitroxides widely used in the field of chemistry, biology, and pharmacology. TEMPO was previously found to be mutagenic and to induce micronuclei in mammalian cells. In this study, we investigated and quantified the genotoxicity of 4 structurally similar nitroxides, TEMPO and 3 of its derivatives (4-hydroxy-TEMPO, 4-oxo-TEMPO, and 4-methoxy-TEMPO), using the mouse lymphoma assay (MLA) and Comet assay in L5178Y Tk+/- cells. The results showed that all tested nitroxides were cytotoxic and mutagenic in the MLA, both in the presence and absence of S9, with metabolic activation significantly enhancing the cytotoxicity and/or mutagenicity. In addition, the 4 nitroxides caused DNA-strand breakage. The mutagenicity and DNA damaging dose-responses of the test articles were compared using the PROAST benchmark dose software package. The potency ranking of the 4 nitroxides for mutagenicity was different from the ranking of the DNA damaging effects. The mode of action analysis by a multi-endpoint DNA damage pathway assay classified all 4 nitroxides as clastogens. In addition, the majority of the induced Tk mutants showed loss of heterozygosity at the Tk and D11Mit42 loci (ie, chromosome damage <31 Mbp). These results suggest that TEMPO and its 3 derivatives are cytotoxic and mutagenic in mouse lymphoma cells through a mechanism that involves strand breakage and large alterations to DNA. The potency rankings indicate that the different TEMPO derivatives vary in their mutagenic and DNA damaging potential.

Targets and mechanisms of chemically induced aneuploidy. Part 1 of the report of the 2017 IWGT workgroup on assessing the risk of aneugens for carcinogenesis and hereditary diseases

An aneuploidy workgroup was established as part of the 7th International Workshops on Genotoxicity Testing. The workgroup conducted a review of the scientific literature on the biological mechanisms of aneuploidy in mammalian cells and methods used to detect chemical aneugens. In addition, the current regulatory framework was discussed, with the objective to arrive at consensus statements on the ramifications of exposure to chemical aneugens for human health risk assessment. As part of these efforts, the workgroup explored the use of adverse outcome pathways (AOPs) to document mechanisms of chemically induced aneuploidy in mammalian somatic cells. The group worked on two molecular initiating events (MIEs), tubulin binding and binding to the catalytic domain of aurora kinase B, which result in several adverse outcomes, including aneuploidy. The workgroup agreed that the AOP framework provides a useful approach to link evidence for MIEs with aneuploidy on a cellular level. The evidence linking chemically induced aneuploidy with carcinogenicity and hereditary disease was also reviewed and is presented in two companion papers. In addition, the group came to the consensus that the current regulatory test batteries, while not ideal, are sufficient for the identification of aneugens and human risk assessment. While it is obvious that there are many different MIEs that could lead to the induction of aneuploidy, the most commonly observed mechanisms involving chemical aneugens are related to tubulin binding and, to a lesser extent, inhibition of mitotic kinases. The comprehensive review presented here should help with the identification and risk management of aneugenic agents.

Genotoxicity and mutagenicity assessment of food contaminant mixtures present in the French diet

Through diet, people are exposed simultaneously to a variety of contaminants (e.g. heavy metals, mycotoxins, pesticides) that could have combined adverse effects on human health. A previous study identified six main mixtures of food contaminants to which French adult consumers are exposed. These complex mixtures are comprised of 11 to 19 chemicals that have numerous toxic properties. In the present study, we investigated the genotoxic effects of these food contaminants, as single molecules and in mixtures that reflect their occurrence in the French diet, using the γH2AX assay in two human cell lines (HepG2, LS-174 T). Results of detailed analysis of the 49 individual contaminants (including 21 tested in this study) demonstrated a positive genotoxic response to 14 contaminants in HepG2 and 12 in LS-174 T cells. Next, our results indicated that two mixtures out of six triggered significant γH2AX induction after 24 hr of treatment, at concentrations for which individual compounds did not induce any DNA damage, suggesting more than additive interactions between chemicals. γH2AX positive mixtures were then tested for mutagenicity with the innovative in vitro PIG-A assay in HepG2 cells coupled with the soft agar colony formation assay. The two γH2AX positive mixtures led to a significant increase in the frequency of PIG-A GPI-deficient cells and in the number of colonies formed in soft agar. In conclusion, our study demonstrates that two mixtures of contaminants present in the French diet induce genotoxicity and mutagenicity, and that the combined effects of single molecules present in these mixtures are likely not additive, highlighting potential problems for hazard assessment of mixtures. Environ. Mol. Mutagen. 59:742-754, 2018. © 2018 Wiley Periodicals, Inc.