Development, Use, and Validation of (Q)SARs for Predicting Genotoxicity and Carcinogenicity: Experiences from Italian National Institute of Health Activities.

In silico approaches are now increasingly accepted in several areas of toxicology to rapidly assess chemical hazard without the need for animal testing. Among in silico tools, quantitative and qualitative structure-activity approaches ((Q)SARs) are the most typically applied methods to predict hazard in the absence of experimental data. This paper provides an overview of different protocols that can be applied while dealing with (Q)SARs in different scenarios, namely, (Q)SAR development, use, and validation. Examples of protocols adopted in the three scenarios are reported, derived from the authors' experience in working at the Predictive Toxicology unit of the Italian National Institute of Health, focusing on the endpoints of carcinogenicity and genotoxicity.The illustrated activities are in line with the Institute's mission, the main center of research, control, and technical-scientific advice on public health in Italy.

Development of a genotoxicity/carcinogenicity assessment method by DNA adductome analysis.

Safety evaluation is essential for the development of chemical substances. Since in vivo safety evaluation tests, such as carcinogenesis tests, require long-term observation using large numbers of experimental animals, it is necessary to develop alternative methods that can predict genotoxicity/carcinogenicity in the short term, taking into account the 3Rs (replacement, reduction, and refinement). We established a prediction model of the hepatotoxicity of chemicals using a DNA adductome, which is a comprehensive analysis of DNA adducts that may be used as an indicator of DNA damage in the liver. An adductome was generated with LC-high-resolution accurate mass spectrometer (HRAM) on liver of rats exposed to various chemicals for 24 h, based on two independent experimental protocols. The resulting adductome dataset obtained from each independent experiment (experiments 1 and 2) and integrated dataset were analyzed by linear discriminant analysis (LDA) and found to correctly classify the chemicals into the following four categories: non-genotoxic/non-hepatocarcinogens (-/-), genotoxic/non-hepatocarcinogens (+/-), non-genotoxic/hepatocarcinogens (-/+), and genotoxic/hepatocarcinogens (+/+), based on their genotoxicity/carcinogenicity properties. A prototype model for predicting the genotoxicity/carcinogenicity of the chemicals was established using machine learning methods (using random forest algorithm). When the prototype genotoxicity/carcinogenicity prediction model was used to make predictions for experiments 1 and 2 as well as the integrated dataset, the correct response rates were 89 % (genotoxicity), 94 % (carcinogenicity) and 87 % (genotoxicity/carcinogenicity) for experiment 1, 47 % (genotoxicity), 62 % (carcinogenicity) and 42 % (genotoxicity/carcinogenicity) for experiment 2, and 52 % (genotoxicity), 62 % (carcinogenicity), and 48 % (genotoxicity/carcinogenicity) for the integrated dataset. To improve the accuracy of the toxicity prediction model, the toxicity label was reconstructed as follows; Pattern 1: when +/+ and -/- chemicals were used from the toxicity labels +/+, +/-, -/+ and -/-; and Pattern 2: when +/+, +/-, and -/+ other than -/- were replaced with the label "Others". As a result, chemicals with only +/+ and -/- toxicity labels were used and the correct response rates were approximately 100 % for the measured data in experiment 1, 53 %-66 % for the data in experiment 2, and 59-73 % for the integrated data, all of which were 10 %-30 % higher compared with the data before the label change. In contrast, when the toxicity labels were replaced with -/- and "Others", they reached nearly 100 % in the measured data from experiment 1, 65 %-75 % in the data from experiment 2, and 70 %-78 % in the integrated data, all of which were 10 %-50 % higher compared with the data before the label change.

Differential genotoxicity of Polygoni Multiflori in rat and human: insights from Ames test and S9 metabolic activation system.

The Ames test is used worldwide to initially screen the mutagenic potential of new chemicals. In the standard Ames test, S. typhimurium strains (TA100, TA98, TA1535, and TA1537) and Escherichia coli (WP2uvrA) are treated with substances with/without cytochrome P450s (CYPs)-induced rat S9 fractions for identifying mutagens and pro-mutagens. However, many substances show completely different toxicity patterns depending on whether the liver S9 fraction belongs to rats or humans. The natural product Polygoni Multiflori Radix (PMR) can also show bacterial reverse mutation, followed by the rat or human liver S9 fraction. While PMR elicits reverse mutations in the TA1537 strain in rat liver S9 but not in human liver S9, this mechanism has not been verified yet. To explain this, the differences in metabolic enzymes compositions commonly observed between rats and humans have been implicated. This study aimed to explore the key factors that cause differences in the genotoxicity of PMR between rat and human liver S9 metabolic enzymes. The results of next-generation sequencing (NGS) analysis showed that both rat and human metabolic enzymes caused similar mutations in TA1537. However, when the metabolic enzymes in each S9 fraction were analyzed using ion mobility tandem mass spectrometry (IM-MS), rat- and human-specific enzymes were identified among the cytochrome (CYP) family, especially aryl hydrocarbon receptor (AHR)-related CYPs. These findings suggest that CYP1A1 isoforms contribute to the mechanism of PMR in the Ames test. Therefore, an in vitro Ames test might be more reliable in predicting genotoxicity for both rodents and humans. This will also help overcome the limitations of laboratory animal-based toxicity evaluations, which provide unreliable results due to interspecies differences between humans and rodents.

Levothyroxine synthesis impurities are neither mutagenic nor genotoxic: Insilico, Ames test and micronucleus test studies.

In vitro and in silico tests were used to assess the possible genotoxicity and mutagenicity of five impurities that may be present in levothyroxine, a drug used for thyroid hormone replacement therapy. Neither ToxTree nor VEGA (Virtual Models for evaluating the properties of chemicals within a global architecture) identified cause for concern for any of the impurities. Ames test results (doses up to 1 mg per plate), with or without metabolic activation, were negative. The micronucleus test with TK6 (human lymphoblastoid) cells, at doses up to 500 µg/mL, with or without metabolic activation, also gave negative results.

Deep active learning with high structural discriminability for molecular mutagenicity prediction.

The assessment of mutagenicity is essential in drug discovery, as it may lead to cancer and germ cells damage. Although in silico methods have been proposed for mutagenicity prediction, their performance is hindered by the scarcity of labeled molecules. However, experimental mutagenicity testing can be time-consuming and costly. One solution to reduce the annotation cost is active learning, where the algorithm actively selects the most valuable molecules from a vast chemical space and presents them to the oracle (e.g., a human expert) for annotation, thereby rapidly improving the model's predictive performance with a smaller annotation cost. In this paper, we propose muTOX-AL, a deep active learning framework, which can actively explore the chemical space and identify the most valuable molecules, resulting in competitive performance with a small number of labeled samples. The experimental results show that, compared to the random sampling strategy, muTOX-AL can reduce the number of training molecules by about 57%. Additionally, muTOX-AL exhibits outstanding molecular structural discriminability, allowing it to pick molecules with high structural similarity but opposite properties.

N-nitrosamine impurity risk assessment in pharmaceuticals: Utilizing In vivo mutation relative potency comparison to establish an acceptable intake for NTTP.

The finding of N-nitrosodiethylamine (NDEA) and N-nitrosodimethylamine (NDMA) in marketed drugs has led to implementation of risk assessment processes intended to limit exposures to the entire class of N-nitrosamines. A critical component of the risk assessment process is establishing exposure limits that are protective of human health. One approach to establishing exposure limits for novel N-nitrosamines is to conduct an in vivo transgenic rodent (TGR) mutation study. Existing regulatory guidance on N-nitrosamines provides decision making criteria based on interpreting in vivo TGR mutation studies as an overall positive or negative. However, point of departure metrics, such as benchmark dose (BMD), can be used to define potency and provide an opportunity to establish relevant exposure limits. This can be achieved through relative potency comparison of novel N-nitrosamines with model N-nitrosamines possessing robust in vivo mutagenicity and carcinogenicity data. The current work adds to the dataset of model N-nitrosamines by providing in vivo TGR mutation data for N-nitrosopiperidine (NPIP). In vivo TGR mutation data was also generated for a novel N-nitrosamine impurity identified in sitagliptin-containing products, 7-nitroso-3-(trifluoromethyl)-5,6,7,8-tetrahydro-[1,2,4]triazolo-[4,3-a]pyrazine (NTTP). Using the relative potency comparison approach, we have demonstrated the safety of NTTP exposures at or above levels of 1500 ng/day.

Sensitive Detection of Genotoxic Substances in Complex Food Matrices by Multiparametric High-Content Analysis.

Genotoxic substances widely exist in the environment and the food supply, posing serious health risks due to their potential to induce DNA damage and cancer. Traditional genotoxicity assays, while valuable, are limited by insufficient sensitivity, specificity, and efficiency, particularly when applied to complex food matrices. This study introduces a multiparametric high-content analysis (HCA) for the detection of genotoxic substances in complex food matrices. The developed assay measures three genotoxic biomarkers, including γ-H2AX, p-H3, and RAD51, which enhances the sensitivity and accuracy of genotoxicity screening. Moreover, the assay effectively distinguishes genotoxic compounds with different modes of action, which not only offers a more comprehensive assessment of DNA damage and the cellular response to genotoxic stress but also provides new insights into the exploration of genotoxicity mechanisms. Notably, the five tested food matrices, including coffee, tea, pak choi, spinach, and tomato, were found not to interfere with the detection of these biomarkers under proper dilution ratios, validating the robustness and reliability of the assay for the screening of genotoxic compounds in the food industry. The integration of multiple biomarkers with HCA provides an efficient method for detecting and assessing genotoxic substances in the food supply, with potential applications in toxicology research and food safety.

Applications of intelligent technology in the evaluation of mutagenicity.

Bioassays are widely used in assessment of mutagenicity. Alternative methods have also been developed, including "intelligent evaluation", which depends on the quality of data, strategies, and techniques. CISOC-PSMT is an Ames test prediction system. The strategies and techniques for intelligent evaluation and four applications of CISOC-PSMT are presented; roles in pesticide management, environmental protection, drug discovery, and safety management of chemicals are introduced.

Evaluating Chromosome Instability and Genotoxicity Through Single Cell Quantitative Imaging Microscopy.

Across eukaryotes, genome stability is essential for normal cell function, physiology, and species survival. Aberrant expression of key genes or exposure to genotoxic agents can have detrimental effects on genome stability and contribute to the development of various diseases, including cancer. Chromosome instability (CIN), or ongoing changes in chromosome complements, is a frequent form of genome instability observed in cancer and is a driver of genetic and cell-to-cell heterogeneity that can be rapidly detected and quantitatively assessed using surrogate markers of CIN. For example, single cell quantitative imaging microscopy (QuantIM) can be used to simultaneously identify changes in nuclear areas and micronucleus formation. While changes in nuclear areas are often associated with large-scale changes in chromosome complements (i.e., ploidy), micronuclei are small extra-nuclear bodies found outside the primary nucleus that have previously been employed as a measure of genotoxicity of test compounds. Here, we present a facile QuantIM approach that allows for the rapid assessment and quantification of CIN associated phenotypes and genotoxicity. First, we provide protocols to optimize and execute CIN and genotoxicity assays. Secondly, we present the critical imaging settings, optimization steps, downstream statistical analyses, and data visualization strategies employed to obtain high quality and robust data. These approaches can be easily applied to assess the prevalence of CIN associated phenotypes and genotoxic stress for a myriad of experimental and clinical contexts ranging from direct tests to large-scale screens of various genetic contexts (i.e., aberrant gene expression) or chemical compounds. In summary, this QuantIM approach facilitates the identification of novel CIN genes and/or genotoxic agents that will provide greater insight into the aberrant genes and pathways underlying CIN and genotoxicity.

Lanthanum nitrate demonstrated no genotoxicity in the conducted tests.

Given the widespread applications in industrial and agricultural production, the health effects of rare earth elements (REEs) have garnered public attention, and the genotoxicity of REEs remains unclear. In this study, we evaluated the genetic effects of lanthanum nitrate, a typical representative of REEs, with guideline-compliant in vivo and in vitro methods. Genotoxicity assays, including the Ames test, comet assay, mice bone marrow erythrocyte micronucleus test, spermatogonial chromosomal aberration test, and sperm malformation assay were conducted to assess mutagenicity, chromosomal damage, DNA damage, and sperm malformation. In the Ames test, no statistically significant increase in bacterial reverse mutation frequencies was found as compared with the negative control. Mice exposed to lanthanum nitrate did not exhibit a statistically significant increase in bone marrow erythrocyte micronucleus frequencies, spermatogonial chromosomal aberration frequencies, or sperm malformation frequencies compared to the negative control (P > 0.05). Additionally, after a 24-h treatment with lanthanum nitrate at concentrations of 1.25, 5, and 20 µg/ml, no cytotoxicity was observed in CHL cells. Furthermore, the comet assay results indicate no significant DNA damage was observed even after exposure to high doses of lanthanum nitrate (20 µg/ml). In conclusion, our findings suggest that lanthanum nitrate does not exhibit genotoxicity.

Genotoxicity assessments of N-nitrosoethylisopropylamine (NEIPA) and N-nitrosodiisopropylamine (NDIPA) in the C57BL/6J mouse.

N-Nitrosamines, known as drug impurities and suspected carcinogens, have drawn significant public concern. In response to drug regulatory needs, the European Medicines Agency (EMA) has previously proposed a carcinogenic potency categorization approach based on the N-nitrosamine α-hydroxylation hypothesis, i.e., that N-nitrosamine mutagenicity increases with the number of α-hydrogen atoms. However, this structure-activity relationship has not been fully tested in vivo. NEIPA (N-nitrosoethylisopropylamine) and NDIPA (N-nitrosodiisopropylamine) are small N-Nitrosamines with similar structures, differing in that the former compound has an additional α-hydrogen atom. In this study, NEIPA and NEIPA doses, 25-100 mg/kg, were administered orally to C57BL/6 J mice for seven consecutive days, and their mutation and DNA damage effects were compared. Compared with NDIPA, the mutagenicity and DNA damage potencies of NEIPA (which contains one more α-hydrogen) were much greater. These differences may be related to their distinct metabolic pathways and target organs. This case study confirms the role of α-hydroxyl modification in the mutagenicity of nitrosamines, with oxidation at the α-hydrogen being a crucial step in the formation of mutagens from N-Nitrosamines, and can inform mutagenicity risk assessment and the formulation of regulatory standards for N-nitrosamine impurities.

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.

In vivo genotoxicity assessment of N-(-9 acridinyl)-b-alanine hydrochloride (S-300) using a validated Pig-a mutagenesis assay.

BACKGROUND: N-(-9 acridinyl)-b-alanine hydrochloride (S-300) is the main byproduct of red blood cell (RBC) amustaline/glutathione(GSH) pathogen reduction, currently undergoing phase III US clinical trials following successful European studies(1-3). Phosphatidylinositol glycan, class A (Pig-a) X-linked gene mutagenesis is a validated mammalian in vivo mutation assay for genotoxicity, assessed as clonal loss of glycosylphosphatidylinositol-linked CD59 cell-surface molecules on reticulocytes (RETs) and RBCs. METHODS: Male Sprague-Dawley rats received continuous infusion of S-300 up to the maximum feasible dose (240 mg/kg/day-limited by solubility and volume) for 28 days. Positive controls received a known mutagen by oral gavage on Days 1-3. Plasma levels of S-300 were assessed by HPLC before, during and after infusion. CD59-negative RBCs and RETs were enumerated in pre-dose and Day 28 samples, using a flow cytometric method. Outcome was evaluated by predetermined criteria using concurrent and historical controls. Toxicity was assessed by laboratory measures and necropsy. RESULTS: S-300 reached maximum, dose-dependent levels (3-15 µmol/L) within 2-8 h that were sustained for 672 h and undetectable 2 h after infusion. Circulating RET levels indicated a lack of hematopoietic toxicity. Necropsy revealed minimal-mild observations related to poor S-300 solubility at high concentrations. Pig-a assessment met the preset acceptability criteria and revealed no increase in mutant RBCs or RETs. CONCLUSIONS: Maximum feasible S-300 exposure of rats by continuous infusion for 28 days was not genotoxic as assessed by an Organization for Economic Cooperation and Development-compliant, mammalian, in vivo Pig-a gene mutation assay that meets the requirements of International Conference on Harmonization (ICH) S2(R1) and FDA guidances on genotoxicity testing.

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.

Non-clinical safety assessment of novel drug modalities: Genome safety perspectives on viral-, nuclease- and nucleotide-based gene therapies.

Gene therapies have emerged as promising treatments for various conditions including inherited diseases as well as cancer. Ensuring their safe clinical application requires the development of appropriate safety testing strategies. Several guidelines have been provided by health authorities to address these concerns. These guidelines state that non-clinical testing should be carried out on a case-by-case basis depending on the modality. This review focuses on the genome safety assessment of frequently used gene therapy modalities, namely Adeno Associated Viruses (AAVs), Lentiviruses, designer nucleases and mRNAs. Important safety considerations for these modalities, amongst others, are vector integrations into the patient genome (insertional mutagenesis) and off-target editing. Taking into account the constraints of in vivo studies, health authorities endorse the development of novel approach methodologies (NAMs), which are innovative in vitro strategies for genotoxicity testing. This review provides an overview of NAMs applied to viral and CRISPR/Cas9 safety, including next generation sequencing-based methods for integration site analysis and off-target editing. Additionally, NAMs to evaluate the oncogenicity risk arising from unwanted genomic modifications are discussed. Thus, a range of promising techniques are available to support the safe development of gene therapies. Thorough validation, comparisons and correlations with clinical outcomes are essential to identify the most reliable safety testing strategies. By providing a comprehensive overview of these NAMs, this review aims to contribute to a better understanding of the genome safety perspectives of gene therapies.

Evaluating the mutagenicity of N-nitrosodimethylamine in 2D and 3D HepaRG cell cultures using error-corrected next generation sequencing.

Human liver-derived metabolically competent HepaRG cells have been successfully employed in both two-dimensional (2D) and 3D spheroid formats for performing the comet assay and micronucleus (MN) assay. In the present study, we have investigated expanding the genotoxicity endpoints evaluated in HepaRG cells by detecting mutagenesis using two error-corrected next generation sequencing (ecNGS) technologies, Duplex Sequencing (DS) and High-Fidelity (HiFi) Sequencing. Both HepaRG 2D cells and 3D spheroids were exposed for 72 h to N-nitrosodimethylamine (NDMA), followed by an additional incubation for the fixation of induced mutations. NDMA-induced DNA damage, chromosomal damage, and mutagenesis were determined using the comet assay, MN assay, and ecNGS, respectively. The 72-h treatment with NDMA resulted in concentration-dependent increases in cytotoxicity, DNA damage, MN formation, and mutation frequency in both 2D and 3D cultures, with greater responses observed in the 3D spheroids compared to 2D cells. The mutational spectrum analysis showed that NDMA induced predominantly A:T → G:C transitions, along with a lower frequency of G:C → A:T transitions, and exhibited a different trinucleotide signature relative to the negative control. These results demonstrate that the HepaRG 2D cells and 3D spheroid models can be used for mutagenesis assessment using both DS and HiFi Sequencing, with the caveat that severe cytotoxic concentrations should be avoided when conducting DS. With further validation, the HepaRG 2D/3D system may become a powerful human-based metabolically competent platform for genotoxicity testing.

Within-laboratory reproducibility of Ames test results: Are repeat tests necessary?

The Ames test is required by regulatory agencies worldwide for assessing the mutagenic and carcinogenic potential of chemical compounds. This test uses several strains of bacteria to evaluate mutation induction: positive results in the assay are predictive of rodent carcinogenicity. As an initial step to understanding how well the assay may detect mutagens present as constituents of complex mixtures such as botanical extracts, a cross-sector working group examined the within-laboratory reproducibility of the Ames test using the extensive, publicly available National Toxicology Program (NTP) Ames test database comprising more than 3000 distinct test articles, most of which are individual chemicals. This study focused primarily on NTP tests conducted using the standard Organization for Economic Co-operation and Development Test Guideline 471 preincubation test protocol with 10% rat liver S9 for metabolic activation, although 30% rat S9 and 10 and 30% hamster liver S9 were also evaluated. The reproducibility of initial negative responses in all strains with and without 10% S9, was quite high, ranging from 95% to 99% with few exceptions. The within-laboratory reproducibility of initial positive responses for strains TA98 and TA100 with and without 10% rat liver S9 was ≥90%. Similar results were seen with hamster S9. As expected, the reproducibility of initial equivocal responses was lower, <50%. These results will provide context for determining the optimal design of recommended test protocols for use in screening both individual chemicals and complex mixtures, including botanicals.

Gastrointestinal tract exposure to particles and DNA damage in animals: A review of studies before, during and after the peak of nanotoxicology.

Humans ingest particles and fibers on daily basis. Non-digestible carbohydrates are beneficial to health and food additives are considered safe. However, titanium dioxide (E171) has been banned in the European Union because the European Food Safety Authority no longer considers it non-genotoxic. Ingestion of microplastics and nanoplastics are novel exposures; their potential hazardous effects to humans have been under the radar for many years. In this review, we have assessed the association between oral exposure to man-made particles/fibers and genotoxicity in gastrointestinal tract cells and secondary tissues. We identified a total of 137 studies on oral exposure to particles and fibers. This was reduced to 49 papers with sufficient quality and relevance, including exposures to asbestos, diesel exhaust particles, titanium dioxide, silver nanoparticles, zinc oxide, synthetic amorphous silica and certain other nanomaterials. Nineteen studies show positive results, 25 studies show null results, and 5 papers show equivocal results on genotoxicity. Recent studies seem to show null effects, whereas there is a higher proportion of positive genotoxicity results in early studies. Genotoxic effects seem to cluster in studies on diesel exhaust particles and titanium dioxide, whereas studies on silver nanoparticles, zinc oxide and synthetic amorphous silica seem to show mainly null effects. The most widely used genotoxic tests are the alkaline comet assay and micronucleus assay. There are relatively few results on genotoxicity using reliable measurements of oxidatively damaged DNA, DNA double strand breaks (γH2AX assay) and mutations. In general, evidence suggest that oral exposure to particles and fibers is associated with genotoxicity in animals.

Strategy proposal using QSAR models to approach mutagenicity assessment of non intentionally added substances in recycled plastic resins.

CONTEXT: Transition to the use of recycled plastics raises an issue concerning safety assessment of Non Intentionally Added Substances (NIAS). To assess the mutagenic potential of the recycled polyethylene impurities and to evaluate the need to perform in vitro assays on recycled resins, this study lies in identifying existing NIAS associated with recycled Low/High Density Polyethylene and assessing the mutagenicity data-gaps by employing in silico tools. METHODS: Quantitative Structure-Activity Relationship (QSAR) models predicting Ames mutagenicity were selected from literature, then NIAS were run to 1/evaluate performances of each model, 2/apply a QSAR strategy on the NIAS molecular space and address data-gaps. RESULTS: Among the 165 NIAS identified, experimental Ames results were not found for 50 substances while the substances with experimental data were predominantly negatives. No individual model was able to predict all NIAS due to applicability domain limitations. Taking into account 1/calculated performances, 2/availability of applicability domain, 3/description of the Training Set, an Integrated Strategy was founded including Sarpy, Consensus and Protox to extend the applicability domain. CONCLUSION & PERSPECTIVES: Existing data and predictions generated by this strategy suggest a low mutagenic potential of NIAS. Further investigation is needed to explore other genotoxicity mechanisms.

Effect of cell treatment procedures on in vitro genotoxicity assessment.

So far, the majority of in vitro toxicological experiments are conducted after an acute 24 h treatment that does not represent a realistic human chemical exposure. Recently, new in vitro approaches have been proposed to study the chemical toxicological effect over several days in order to be more predictive of a representative exposure scenario. In this study, we investigated the genotoxic potential of chemicals (direct or bioactived clastogen, aneugen and apoptotic inducer) with the γH2AX and pH3 biomarkers, in the human liver-derived HepaRP cell line. We used different treatment durations, with or without a three-day recovery stage (release period), before genotoxicity measurement. Data were analysed with the Benchmark Dose approach. We observed that the detection of clastogenic compounds (notably for DNA damaging agents) was more sensitive after three days of repeated treatment compared to one or three treatments over 24 h. In contrast, aneugenic chemicals were detected as genotoxic in a similar manner whether after a 24 h exposure or a three-day repeated treatment. Globally, the release period decreases the genotoxicity measurement substantially. For DNA damaging agents, after high concentration treatments, γH2AX induction was always observed after a three-day release period. In contrast, for DNA topoisomerase inhibitors, no effect could be observed after the release period. In conclusion, in the HepaRP cell line, there are some important differences between a one-day acute and a three-day repeated treatment protocol, indicating that different cell treatment procedures may differentiate chemical genotoxic mechanisms of action more efficiently.