Quantum Mechanical Assessment of Nitrosamine Potency.

Nitrosamines are in the cohort of concern (CoC) as determined by regulatory guidance. CoC compounds are considered highly potent carcinogens that need to be limited below the threshold of toxicological concern, 1.5 µg/day. Nitrosamines like NDMA and NDEA require strict control, while novel nitrosamine drug substance-related impurities (NDSRIs) may or may not be characterized as potent carcinogens. A risk assessment based on the structural features of NDSRIs is important in order to predict potency because they lack substance-specific carcinogenicity. Herein, we present a quantum mechanical (QM)-based analysis on structurally diverse sets of nitrosamines to better understand how structure influences the reactivity that could result in carcinogenicity. We describe the potency trend through activation energies corresponding to α-hydroxylation, aldehyde formation, diazonium intermediate formation, reaction with DNA base, and hydrolysis reactions, and other probable metabolic pathways associated with the carcinogenicity of nitrosamines. We evaluated activation energies for selected cases such as N-nitroso pyrrolidines, N-nitroso piperidines, N-nitroso piperazines, N-nitroso morpholines, N-nitroso thiomorpholine, N-methyl nitroso aromatic, fluorine-substituted nitrosamines, and substituted aliphatic nitrosamines. We compare these results to the recent framework of the carcinogenic potency characterization approach (CPCA) proposed by health authorities which is meant to give guidance on acceptable intakes (AI) for NDSRIs lacking substance-specific carcinogenicity data. We show examples where QM modeling and CPCA are aligned and examples where CPCA both underestimates and overestimates the AI. In cases where CPCA predicts high potency for NDSRIs, QM modeling can help better estimate an AI. Our results suggest that a combined mechanistic understanding of α-hydroxylation, aldehyde formation, hydrolysis, and reaction with DNA bases could help identify the structural features that underpin the potency of nitrosamines. We anticipate this work will be a valuable addition to the CPCA and provide a more analytical way to estimate AI for novel NDSRIs.

Mutagenic impurities in pharmaceuticals: A critical assessment of the cohort of concern with a focus on N-nitrosamines.

The TTC (Threshold of Toxicological Concern; set at 1.5 µg/day for pharmaceuticals) defines an acceptable patient intake for any unstudied chemical posing a negligible risk of carcinogenicity or other toxic effects. A group of high potency mutagenic carcinogens, defined solely by the presence of particular structural alerts, are referred to as the "cohort of concern" (CoC); aflatoxin-like-, N-nitroso-, and alkyl-azoxy compounds are considered to pose a significant carcinogenic risk at intakes below the TTC. Kroes et al. (2004) derived values for the TTC and CoC in the context of food components, employing a non-transparent dataset never placed in the public domain. Using a reconstructed all-carcinogen dataset from relevant publications, it is now clear that there are exceptions for all three CoC structural classes. N-Nitrosamines represent 62% of the N-nitroso class in the reconstructed dataset. Employing a contemporary dataset, 20% are negative in rodent carcinogenicity bioassays with less than 50% of all N-nitrosamines estimated to fall into the highest risk category. It is recommended that CoC nitrosamines are identified by compound-specific data rather than structural alerts. Thus, it should be possible to distinguish CoC from non-CoC N-nitrosamines in the context of mutagenic impurities described in ICH M7 (R1).

Carcinogenicity prediction using the index of ideality of correlation.

Carcinogenicity testing is necessary to protect human health and comply with regulations, but testing it with the traditionally used two-year rodent studies is time-consuming and expensive. In certain cases, such as for impurities, alternative methods may be convenient. Thus there is an urgent need for alternative approaches for reliable and robust assessments of carcinogenicity. The Monte Carlo technique with CORAL software is a tool to tackle this task for unknown compounds using available experimental data for a representative set of compounds. The models can be constructed with the simplified molecular input line entry system without additional physicochemical descriptors. We describe here a model based on a data set of 1167 substances. Matthew's correlation coefficient values for calibration and validation sets are 0.747 and 0.577, respectively. Double bonds between carbon atoms and double bonds of oxygen atoms are the molecular features that indicate the carcinogenic potential of a compound.

In Silico Methods for Carcinogenicity Assessment.

Screening compounds for potential carcinogenicity is of major importance for prevention of environmentally induced cancers. A large sequence of predictive models, ranging from short-term biological assays (e.g., mutagenicity tests) to theoretical models, has been attempted in this field. Theoretical approaches such as (Q)SAR are highly desirable for identifying carcinogens, since they actively promote the replacement, reduction, and refinement of animal tests. This chapter reports and describes some of the most noted (Q)SAR models based on human expert knowledge and statistical approaches, aiming at predicting the carcinogenicity of chemicals. Additionally, the performance of the selected models has been evaluated, and the results are interpreted in details by applying these predictive models to some pharmaceutical molecules.

Follow-up genotoxicity assessment of Ames-positive/equivocal chemicals using the improved thymidine kinase gene mutation assay in DNA repair-deficient human TK6 cells.

Genotoxicity testing plays an important role in the safety assessment of pharmaceuticals, pesticides and chemical substances. Among the guidelines for various genotoxicity tests, the in vitro genotoxicity test battery comprises the bacterial Ames test and mammalian cell assays. Several chemicals exhibit conflicting results for the bacterial Ames test and mammalian cell genotoxicity studies, which may stem from the differences in DNA repair capacity or metabolism, between different cell types or species. For better understanding the mechanistic implications regarding conflict outcomes between different assay systems, it is necessary to develop in vitro genotoxicity testing approaches with higher specificity towards DNA-damaging reagents. We have recently established an improved thymidine kinase (TK) gene mutation assay (TK assay) i.e. deficient in DNA excision repair system using human lymphoblastoid TK6 cells lacking XRCC1 and XPA (XRCC1-/-/XPA-/-), the core factors of base excision repair (BER) and nucleotide excision repair (NER), respectively. This DNA repair-deficient TK6 cell line is expected to specifically evaluate the genotoxic potential of chemical substances based on the DNA damage. We focussed on four reagents, N-(1-naphthyl)ethylenediamine dihydrochloride (NEDA), p-phenylenediamine (PPD), auramine and malachite green (MG) as the Ames test-positive chemicals. In our assay, assessment using XRCC1-/-/XPA-/- cells revealed no statistically significant increase in the mutant frequencies after treatment with NEDA, PPD and MG, suggesting the chemicals to be non-genotoxic in humans. The observations were consistent with that of the follow-up in vivo studies. In contrast, the mutant frequency was markedly increased in XRCC1-/-/XPA-/- cells after treatment with auramine. The results suggest that auramine is the genotoxic reagent that preferentially induces DNA damages resolved by BER and/or NER in mammals. Taken together, BER/NER-deficient cell-based genotoxicity testing will contribute to elucidate the mechanism of genotoxicity and therefore play a pivotal role in the accurate safety assessment of chemical substances.

Determination of Toxic Pyrrolizidine Alkaloids in Traditional Chinese Herbal Medicines by UPLC-MS/MS and Accompanying Risk Assessment for Human Health.

Pyrrolizidine alkaloids (PAs) are a class of natural toxins with hepatotoxicity, genotoxicity and carcinogenicity. They are endogenous and adulterated toxic components widely found in food and herbal products. In this study, a sensitive and efficient ultra-high performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was used to detect the PAs in 386 kinds of Chinese herbal medicines recorded in the Chinese Pharmacopoeia (2020). The estimated daily intake (EDI) of 0.007 µg/kg body weight (bw)/day was adopted as the safety baseline. The margin of exposure (MOE) approach was applied to evaluate the chronic exposure risk for the genotoxic and carcinogenic potential of PAs. Results showed that PAs was detected in 271 out of 386 samples with a content of 0.1-25,567.4 µg/kg, and there were 20 samples with EDI values above the baseline, 0.007 µg/kg bw/day. Beyond that, the MOE values for 10 out of 271 positive samples were below 10,000. Considering the actual situation, Haber's rule was used to assume two weeks exposure every year during lifetime, and still the MOE values for four out of 271 positive samples were under 10,000, indicating these products may have potential health risk. The developed method was successfully applied to detect the PAs-containing Chinese herbal medicines. This study provides convincing data that can support risk management actions in China and a meaningful reference for the rational and safe use of Chinese herbal medicines.

Ochratoxin A and 2'R-Ochratoxin A in Selected Foodstuffs and Dietary Risk Assessment.

The aim of this study was to estimate the contamination of grain coffee, roasted coffee, instant coffee, and cocoa purchased in local markets with ochratoxin A (OTA) and its isomerization product 2'R-ochratoxin A (2'R-OTA), and to assess risk of dietary exposure to the mycotoxins. OTA and 2'R-OTA content was determined using the HPLC chromatography with immunoaffinity columns dedicated to OTA. OTA levels found in all the tested samples were below the maximum limits specified in the European Commission Regulation EC 1881/2006. Average OTA concentrations calculated for positive samples of grain coffee/roasted coffee/instant coffee/cocoa were 0.94/0.79/3.00/0.95 µg/kg, with the concentration ranges: 0.57-1.97/0.44-2.29/0.40-5.15/0.48-1.97 µg/kg, respectively. Average 2'R-OTA concentrations calculated for positive samples of roasted coffee/instant coffee were 0.90/1.48 µg/kg, with concentration ranges: 0.40-1.26/1.00-2.12 µg/kg, respectively. In turn, diastereomer was not found in any of the tested cocoa samples. Daily intake of both mycotoxins with coffee/cocoa would be below the TDI value even if the consumed coffee/cocoa were contaminated with OTA/2'R-OTA at the highest levels found in this study. Up to now only a few papers on both OTA and 2'R-OTA in roasted food products are available in the literature, and this is the first study in Poland.

QSAR Models for Human Carcinogenicity: An Assessment Based on Oral and Inhalation Slope Factors.

Carcinogenicity is a crucial endpoint for the safety assessment of chemicals and products. During the last few decades, the development of quantitative structure-activity relationship ((Q)SAR) models has gained importance for regulatory use, in combination with in vitro testing or expert-based reasoning. Several classification models can now predict both human and rat carcinogenicity, but there are few models to quantitatively assess carcinogenicity in humans. To our knowledge, slope factor (SF), a parameter describing carcinogenicity potential used especially for human risk assessment of contaminated sites, has never been modeled for both inhalation and oral exposures. In this study, we developed classification and regression models for inhalation and oral SFs using data from the Risk Assessment Information System (RAIS) and different machine learning approaches. The models performed well in classification, with accuracies for the external set of 0.76 and 0.74 for oral and inhalation exposure, respectively, and r2 values of 0.57 and 0.65 in the regression models for oral and inhalation SFs in external validation. These models might therefore support regulators in (de)prioritizing substances for regulatory action and in weighing evidence in the context of chemical safety assessments. Moreover, these models are implemented on the VEGA platform and are now freely downloadable online.

Emission profiles, ozone formation potential and health-risk assessment of volatile organic compounds in rubber footwear industries in China.

The emission characteristics of VOCs in the rubber footwear industry (RFI) and its effect on human health are poorly understood to date. Herein, up to 68 VOCs, sorted into seven classes including alkanes, alkenes, acetylene, aromatics, halocarbons, carbon disulfide, and oxygenated VOCs, were monitored. VOCs emitted from three main processing stages of RFI, including shaping, painting and vulcanizing, were 383, 1507 and 1026 mg/m3, respectively. The top 10 VOCs contributing to the concentration and ozone formation potential were identified. Generally, alkanes were the major component emitted from three stages, contributing 48.58%-63.07% of the total VOCs. Alkenes contributed most to the OFP, accounting for 37.2%-69.1%. Based on the risk assessment, a definite cancer risk for workers in shaping workshop should be noticed. Several VOCs with a life carcinogenic risk higher than 10-4, especially benzene, bromodichloromethane, ethylbenzene and 1,1,2-trichloroethane, should be focused on. Therefore, more attention should be taken for the extended-ranges of VOCs in subordinate RFI, except for the publicly concerned aromatics in rubber industry. A VOCs emission inventory from the production process of Chinese RFI in 2000-2016 was compiled. It is estimated that Chinese RFIs have emitted a total of 319 × 104 t VOCs in those past 17 years.

Characteristics, distribution, source apportionment, and potential health risk assessment of polycyclic aromatic hydrocarbons in urban street dust of Kerman metropolis, Iran.

In this study, the concentrations of street dust-bound polycyclic aromatic hydrocarbons (PAHs) in Kerman metropolis as a typical arid urban area were determined to investigate the contamination, molecular composition, toxicity, and sources of PAHs. Sixteen individual PAHs on the United States Environmental Protection Agency priority list were analyzed using gas chromatography-mass spectrometry in street dust samples from 30 sites. ∑PAHs ranged between 165 and 5314.7 µg·kg-1 with a mean of 770.8 µg·kg-1. The most abundant individual PAHs were fluoranthene, phenanthrene, pyrene, and chrysene, respectively. High molecular weight PAHs (4-6 rings) made 74.8% of ∑PAHs mass and were dominant in all sites. Source apportionment was performed using ring classification, diagnostic ratios, and principal component analysis-multiple linear regression. The results indicated that primary contributors of PAHs in the street dust of Kerman could be liquid fossil fuel combustion, natural gas combustion, and petrogenic sources, accounting for 82.4%, 11.5%, and 6.1%, respectively. The calculated incremental lifetime cancer risk is 8.13 × 10-4 for children and 6.27 × 10-4 for adults. Hence, both children and adults in Kerman are potentially exposed to a high carcinogenic risk via ingestion and dermal contact.

The reduction of toxic metals of various rice types by different preparation and cooking processes - Human health risk assessment in Tehran households, Iran.

In this study, the effect of washing, soaking (1, 5 and 12 h), and cooking rice methods including Rinsed (boiling in excess water) and Kateh (conventional) cooking on the reduction of the arsenic (As), lead (Pb), and cadmium (Cd) were evaluated. The results showed that the rinsed cooking has higher efficiency for removal of toxic metals (As = 42.3%, Pb = 42.9% and = 27.6%) than Kateh method (As = 26.9%, Pb = 26.9% and = 20.9%). Additionally, by increasing of rice soaking time from 1 to 12 h, the toxic metals removal was increased up to 37.1%, 42.6% and 16.6% for As, Pb and Cd, respectively. Although the toxic metals reduction was such that the non-carcinogenic risk was regarded as acceptable level after all processes, for arsenic, these reductions did not lower the carcinogenic risk to an acceptable level. Finally, it is suggested that Tehran households, after washing and soaking to 5 h, then cook it by rinse method.

Chemical carcinogenicity revisited 3: Risk assessment of carcinogenic potential based on the current state of knowledge of carcinogenesis in humans.

Over 50 years, we have learned a great deal about the biology that underpins cancer but our approach to testing chemicals for carcinogenic potential has not kept up. Only a small number of chemicals has been tested in animal-intensive, time consuming, and expensive long-term bioassays in rodents. We now recommend a transition from the bioassay to a decision-tree matrix that can be applied to a broader range of chemicals, with better predictivity, based on the premise that cancer is the consequence of DNA coding errors that arise either directly from mutagenic events or indirectly from sustained cell proliferation. The first step is in silico and in vitro assessment for mutagenic (DNA reactive) activity. If mutagenic, it is assumed to be carcinogenic unless evidence indicates otherwise. If the chemical does not show mutagenic potential, the next step is assessment of potential human exposure compared to the threshold for toxicological concern (TTC). If potential human exposure exceeds the TTC, then testing is done to look for effects associated with the key characteristics that are precursors to the carcinogenic process, such as increased cell proliferation, immunosuppression, or significant estrogenic activity. Protection of human health is achieved by limiting exposures to below NOEALs for these precursor effects. The decision tree matrix is animal-sparing, cost effective, and in step with our growing knowledge of the process of cancer formation.

A decision tree-based integrated testing strategy for tailor-made carcinogenicity evaluation of test substances using genotoxicity test results and chemical spaces.

Genotoxicity evaluation has been widely used to estimate the carcinogenicity of test substances during safety evaluation. However, the latest strategies using genotoxicity tests give more weight to sensitivity; therefore, their accuracy has been very low. For precise carcinogenicity evaluation, we attempted to establish an integrated testing strategy for the tailor-made carcinogenicity evaluation of test materials, considering the relationships among genotoxicity test results (Ames, in vitro mammalian genotoxicity and in vivo micronucleus), carcinogenicity test results and chemical properties (molecular weight, logKow and 179 organic functional groups). By analyzing the toxicological information and chemical properties of 230 chemicals, including 184 carcinogens in the Carcinogenicity Genotoxicity eXperience database, a decision tree for carcinogenicity evaluation was optimised statistically. A decision forest model was generated using a machine-learning method-random forest-which comprises thousands of decision trees. As a result, balanced accuracies in cross-validation of the optimised decision tree and decision forest model, considering chemical space (71.5% and 75.5%, respectively), were higher than balanced accuracy of an example regulatory decision tree (54.1%). Moreover, the statistical optimisation of tree-based models revealed significant organic functional groups that would cause false prediction in standard genotoxicity tests and non-genotoxic carcinogenicity (e.g., organic amide and thioamide, saturated heterocyclic fragment and aryl halide). In vitro genotoxicity tests were the most important parameters in all models, even when in silico parameters were integrated. Although external validation is required, the findings of the integrated testing strategies established herein will contribute to precise carcinogenicity evaluation and to determine new mechanistic hypotheses of carcinogenicity.

Assessment of Genotoxic Effects by Constructing a 3D Cellular System with Highly Sensitive Mutagenic Human-Hamster Hybrid Cells.

Owing to complex microenvironmental conditions, it is challenging to reflect the actual biological responses of tissues or the body in a two-dimensional (2D) cellular system. In the present study, a low-attachment-cultivation technique was employed to establish a highly sensitive 3D human-hamster hybrid (AL) model to study the mutagenic effects of environmental pollutants. The results showed that the established 3D system has apparent organizational characteristics. The average diameter and average cell number of the 3D cells were approximately 240 µm and 1500, respectively. The expression of stemness and cell-junction genes (biomarkers for 3D cells) was higher than that in 2D cells. The present study analyzed the mutagenic effects of the environmental carcinogens arsenite and silver nanoparticles using the established 3D system to demonstrate its efficiency in mutagenic assessment. The results showed that the mutagenic effects of arsenite (10 µM) and silver nanoparticles (10 µg/mL) were 70 ± 3 and 99 ± 7 per 105 survivors, respectively. These values were much lower than those from 2D AL cells and comparable to those from the in vivo system. These results suggest that the developed 3D-cell-culture model based on the 2D AL cellular system more effectively reflects the actual gene-mutation frequency of mutagens in vivo.

CORAL: QSAR models for carcinogenicity of organic compounds for male and female rats.

Quantitative structure - activity relationships (QSARs) for carcinogenicity (rats, TD50) have been built up using the CORAL software. Different molecular features, which are extracted from simplified molecular input-line entry system (SMILES) serve as the basis for building up a model. Correlation weights for the molecular features are calculated by means of the Monte Carlo optimization. Using the numerical data on the correlation weights, one can calculate a model of carcinogenicity as a mathematical function of descriptors, which are sum of the corresponding correlation weights. In other words, the correlation weights provide the maximal correlation coefficient between the descriptor and carcinogenicity, for the training set. This correlation was assessed via external validation set. Finally, lists of molecular alerts in aspects of carcinogenicity for male rats and for female rats were compared and their differences were discussed.

Patulin and ochratoxin A co-occurrence and their bioaccessibility in processed cereal-based foods: A contribution for Portuguese children risk assessment.

Patulin (PAT) and ochratoxin A (OTA) are well known enteropathogenic mycotoxins that are present in several foodstuffs. Processed cereal-based foods are among the first solid foods eaten by children, a particularly vulnerable population group. There is a lack of knowledge related to the co-occurrence of PAT and OTA in food intended for children consumption and their potential interactions during the digestion process. The present study aims to evaluate, for the first time, the co-occurrence of PAT and OTA in processed cereal-based foods for children consumption, the bioaccessibility of these two mycotoxins, and the contribution of the bioaccessibility data for human health risk assessment. PAT and OTA incidence were 75% and 50%, respectively. These mycotoxins co-occurred in 40% of analysed samples. Bioaccessibility assays revealed mean values of 52% and 56% for PAT, alone and combined with OTA; and 100% and 106% for OTA, alone and combined with PAT. Considering the human health risk assessment, and taking into account the co-occurrence and the bioaccessibility results, this study indicates a tolerable exposure to these mycotoxins representing a low risk for Portuguese children. The present work reinforces the importance of a holistic approach for risk assessment which gathers data from occurrence, exposure and bioaccessibility.

In Silico Methods for Carcinogenicity Assessment.

Screening compounds for potential carcinogenicity is of major importance for prevention of environmentally induced cancers. A large sequence of alternative predictive models, ranging from short-term biological assays (e.g. mutagenicity tests) to theoretical models, have been attempted in this field. Theoretical approaches such as (Q)SAR are highly desirable for identifying carcinogens, since they actively promote the replacement, reduction, and refinement of animal tests. This chapter reports and describes some of the most noted (Q)SAR models based on the human expert knowledge and statistically approach, aiming at predicting the carcinogenicity of chemicals. Additionally, the performance of the selected models has been evaluated and the results are interpreted in details by applying these prediction models to some pharmaceutical molecules.

Integrated approach to testing and assessment for predicting rodent genotoxic carcinogenicity.

We investigated the performance of an integrated approach to testing and assessment (IATA), designed to cover different genotoxic mechanisms causing cancer and to replicate measured carcinogenicity data included in a new consolidated database. Genotoxic carcinogenicity was predicted based on positive results from at least two genotoxicity tests: one in vitro and one in vivo (which were associated with mutagenicity categories according to the Globally Harmonized System classification). Substances belonging to double positives mutagenicity categories were assigned to be genotoxic carcinogens. In turn, substances that were positive only in a single mutagenicity test were assigned to be mutagens. Chemicals not classified by the selected genotoxicity endpoints were assigned to be negative genotoxic carcinogens and subsequently evaluated for their capability to elicit non-genotoxic carcinogenicity. However, non-genotoxic carcinogenicity mechanisms were not currently included in the developed IATA. The IATA is docked to the OECD Toolbox and uses measured data for different genotoxicity endpoints when available. Alternatively, the system automatically provides predictions by SAR genotoxicity models using the OASIS Tissue Metabolism Simulator platform. When the developed IATA was tested against the consolidated database, its performance was found to be high, with sensitivity of 74% and specificity of 83%, when measured carcinogenicity data were used along with predictions falling within the models' applicability domains. Performance of the IATA would be slightly changed to a sensitivity of 80% and specificity of 72% when the evaluation by non-genotoxic carcinogenicity mechanisms was taken into account. Copyright © 2016 John Wiley & Sons, Ltd.

Banana peel: an effective biosorbent for aflatoxins.

This work reports the application of banana peel as a novel bioadsorbent for in vitro removal of five mycotoxins (aflatoxins (AFB1, AFB2, AFG1, AFG2) and ochratoxin A). The effect of operational parameters including initial pH, adsorbent dose, contact time and temperature were studied in batch adsorption experiments. Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR) and point of zero charge (pHpzc) analysis were used to characterise the adsorbent material. Aflatoxins' adsorption equilibrium was achieved in 15 min, with highest adsorption at alkaline pH (6-8), while ochratoxin has not shown any significant adsorption due to surface charge repulsion. The experimental equilibrium data were tested by Langmuir, Freundlich and Hill isotherms. The Langmuir isotherm was found to be the best fitted model for aflatoxins, and the maximum monolayer coverage (Q0) was determined to be 8.4, 9.5, 0.4 and 1.1 ng mg(-1) for AFB1, AFB2, AFG1 and AFG2 respectively. Thermodynamic parameters including changes in free energy (ΔG), enthalpy (ΔH) and entropy (ΔS) were determined for the four aflatoxins. Free energy change and enthalpy change demonstrated that the adsorption process was exothermic and spontaneous. Adsorption and desorption study at different pH further demonstrated that the sorption of toxins was strong enough to sustain pH changes that would be experienced in the gastrointestinal tract. This study suggests that biosorption of aflatoxins by dried banana peel may be an effective low-cost decontamination method for incorporation in animal feed diets.