Carcinogenicity of the aromatic amines: from structure-activity relationships to mechanisms of action and risk assessment

Aromatic amines represent one of the most important classes of industrial and environmental chemicals: many of them have been reported to be powerful carcinogens and mutagens, and/or hemotoxicants. Their toxicity has been studied also with quantitative structure-activity relationship (QSAR) methods: these studies are potentially suitable for investigating mechanisms of action and for estimating the toxicity of compounds lacking experimental determinations. In this paper, we first summarized the QSAR models for the rodent carcinogenicity of the aromatic amines. The gradation of potency of the carcinogenic amines depended firstly on their hydrophobicity, and secondly on electronic (reactivity, propensity to be metabolically transformed) and steric properties. On the contrary, the difference between carcinogenic and non-carcinogenic aromatic amines depended mainly on electronic and steric properties. These QSARs can be used directly for estimating the carcinogenicity of aromatic amines. A two-step prediction is possible: (1) estimation of yes/no activity; (2) if the answer from step 1 is yes, then prediction of the degree of potency. The QSARs for rodent carcinogenicity were put in a wider context by comparing them with those for: (a) Salmonella mutagenicity; (b) general toxicity; (c) enzymatic reactions; (d) physical-chemical reactions. This comparative QSAR exercise generated a coherent global picture of the action mechanisms of the aromatic amines. The QSARs for carcinogenicity were similar to those for Salmonella mutagenicity, thus pointing to a similar mechanism of action. On the contrary, the general toxicity QSARs (both in vitro and in vivo systems) were mostly based on hydrophobicity, pointing to an aspecific mechanism of action much simpler than that for carcinogenicity and mutagenicity. The oxidation of the amines (first step in the main metabolic pathway leading to carcinogenic and mutagenic species) had identical QSARs in both enzymatic and physical-chemical systems, thus providing evidence for the link between simple chemical reactions and those in biological systems. The results show that it is possible to generate mechanistically and statistically sound QSAR models for rodent carcinogenicity, and indirectly that the rodent bioassay is a reliable source of good quality data.     

DCAMCP: A deep learning model based on capsule network and attention mechanism for molecular carcinogenicity prediction

The carcinogenicity of drugs can have a serious impact on human health, so carcinogenicity testing of new compounds is very necessary before being put on the market. Currently, many methods have been used to predict the carcinogenicity of compounds. However, most methods have limited predictive power and there is still much room for improvement. In this study, we construct a deep learning model based on capsule network and attention mechanism named DCAMCP to discriminate between carcinogenic and non-carcinogenic compounds. We train the DCAMCP on a dataset containing 1564 different compounds through their molecular fingerprints and molecular graph features. The trained model is validated by fivefold cross-validation and external validation. DCAMCP achieves an average accuracy (ACC) of 0.718 ± 0.009, sensitivity (SE) of 0.721 ± 0.006, specificity (SP) of 0.715 ± 0.014 and area under the receiver-operating characteristic curve (AUC) of 0.793 ± 0.012. Meanwhile, comparable results can be achieved on an external validation dataset containing 100 compounds, with an ACC of 0.750, SE of 0.778, SP of 0.727 and AUC of 0.811, which demonstrate the reliability of DCAMCP. The results indicate that our model has made progress in cancer risk assessment and could be used as an efficient tool in drug design.     

Update on genotoxicity and carcinogenicity testing of 472 marketed pharmaceuticals

This survey is a compendium of genotoxicity and carcinogenicity information of 838 marketed drugs, whose expected clinical use is continuous for at least 6 months or intermittent over an extended period of time. Of these 838 drugs, 366 (43.7%) do not have retrievable genotoxicity or carcinogenicity data. The remaining 472 (56.3%) have at least one genotoxicity or carcinogenicity test result. Of the 449 drugs with at least one genotoxicity test result, 183 (40.8%) have at least one positive finding. Of the 338 drugs with at least one carcinogenicity test result, 160 (47.3%) have at least one positive result. Concerning the predictivity of genetic toxicology findings for long-term carcinogenesis assays, of the 315 drugs which have both genotoxicity and carcinogenicity data 116 (36.8%) are neither genotoxic nor carcinogenic, 50 (15.9%) are non-carcinogens which test positive in at least one genotoxicity assay, 75 (23.8%) are carcinogenic in at least one sex of mice or rats but test negative in genotoxicity assays, and 74 (23.5%) are both genotoxic and carcinogenic. Only 208 (24.8%) of the 838 drugs considered have all data required by current guidelines for testing of pharmaceuticals. However, it should be noted that a large fraction of the drugs considered were developed and marketed prior to the present regulatory climate. Although the laws do not require re-testing based on revised standards, in the absence of epidemiological studies excluding a carcinogenic risk to humans, a re-evalutation would be appropriate.     

2D-QSAR model development and analysis on variant groups of anti-tuberculosis drugs

A quantitative structure activity relationship study was performed on different groups of anti-tuberculosis drug compound for establishing quantitative relationship between biological activity and their physicochemical /structural properties. In recent years, a large number of herbal drugs are promoted in treatment of tuberculosis especially due to the emergence of MDR (multi drug resistance) and XDR (extensive drug resistance) tuberculosis. Multidrug-resistant TB (MDR-TB) is resistant to front-line drugs (isoniazid and rifampicin, the most powerful anti-TB drugs) and extensively drug-resistant TB (XDR-TB) is resistant to front-line and second-line drugs. The possibility of drug resistance TB increases when patient does not take prescribed drugs for defined time period. Natural products (secondary metabolites) isolated from the variety of sources including terrestrial and marine plants and animals, and microorganisms, have been recognized as having antituberculosis action and have recently been tested preclinically for their growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. A quantitative structure activity relationship (QSAR) studies were performed to explore the antituberculosis compound from the derivatives of natural products . Theoretical results are in accord with the in vitro experimental data with reported growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. Antitubercular activity was predicted through QSAR model, developed by forward feed multiple linear regression method with leave-one-out approach. Relationship correlating measure of QSAR model was 74% (R(2) = 0.74) and predictive accuracy was 72% (RCV(2) = 0.72). QSAR studies indicate that dipole energy and heat of formation correlate well with anti-tubercular activity. These results could offer useful references for understanding mechanisms and directing the molecular design of new lead compounds with improved anti-tubercular activity. The generated QSAR model revealed the importance of structural, thermodynamic and electro topological parameters. The quantitative structure activity relationship provides important structural insight in designing of potent antitubercular agent.     

Nickel Carcinogenicity in Relation to the Health Risks from Residual Oil Fly Ash

Epidemiological studies of workers in the nickel industry, animal exposure studies, and reports on the potential mechanisms of nickel-induced toxicity and carcinogenicity indicate that only crystalline sulfidic nickel compounds have been clearly established as carcinogenic or potentially carcinogenic in humans. This observation indicates the need to modify and update regulatory approaches for nickel to reflect noncancer toxicity values for some individual nickel species. Analysis of nickel compounds in residual oil fly ash (ROFA) indicates that sulfidic nickel compounds (e.g., nickel subsulfide, nickel sulfide) are not present. Thus, the potential for emission of carcinogenic nickel compounds from residual oil fly ash appears to be low. Preliminary reference concentrations (RfCs) for a number of nickel compounds, based on non-carcinogenic endpoints, are proposed on the basis of the benchmark dose approach in conjunction with NTP data for nickel species.     

Genotoxicity and carcinogenicity studies of antihypertensive agents

This survey is a compendium of genotoxicity and carcinogenicity information of antihypertensive drugs. Data from 164 marketed drugs were collected. Of the 164 drugs, 65 (39.6%) had no retrievable genotoxicity or carcinogenicity data; this group was comprised largely of drugs marketed in a limited number of countries. The remaining 99 (60.4%) had at least one genotoxicity or carcinogenicity test result. Of these 99, 48 (48.5%) had at least one positive finding: 32 tested positive in at least one genotoxicity assay, 26 in at least one carcinogenicity assay, and 10 gave a positive result in both at least one genotoxicity assay and at least one carcinogenicity assay. In terms of correlation between results of the various genotoxicity assays and absence of carcinogenic activity in both mice and rats 2 of 44 non-carcinogenic drugs tested positive in the in vitro bacterial mutagenesis assay, 2 of 9 tested positive in the mouse lymphoma assay, none of 14 tested positive for gene mutation at the hprt locus, 5 of 25 tested positive in in vitro cytogenetic assays, none of 31 in in vivo cytogenetic assays, and none of 14 in inducing DNA damage and/or repair in in vitro and/or in vivo assays. Concerning the predictivity of genetic toxicology findings for long-term carcinogenesis assays, 75 drugs had both genotoxicity and carcinogenicity data; of these 37 (49.3%) were neither genotoxic nor carcinogenic, 14 (18.7%) were non-carcinogens which tested positive in at least one genotoxicity assay, 14 (18.7%) were carcinogenic in at least one sex of mice or rats but tested negative in genotoxicity assays, and 10 (13.3%) were both genotoxic and carcinogenic. Only 42 of the 164 marketed antihypertensives (25.6%) had all data required by the guidelines for testing of pharmaceuticals.     

Animal carcinogenicity studies: 1. Poor human predictivity

The regulation of human exposure to potentially carcinogenic chemicals constitutes society's most important use of animal carcinogenicity data. Environmental contaminants of greatest concern within the USA are listed in the Environmental Protection Agency's (EPA's) Integrated Risk Information System (IRIS) chemicals database. However, of the 160 IRIS chemicals lacking even limited human exposure data but possessing animal data that had received a human carcinogenicity assessment by 1 January 2004, we found that in most cases (58.1%; 93/160), the EPA considered animal carcinogenicity data inadequate to support a classification of probable human carcinogen or non-carcinogen. For the 128 chemicals with human or animal data also assessed by the World Health Organisation's International Agency for Research on Cancer (IARC), human carcinogenicity classifications were compatible with EPA classifications only for those 17 having at least limited human data (p = 0.5896). For those 111 primarily reliant on animal data, the EPA was much more likely than the IARC to assign carcinogenicity classifications indicative of greater human risk (p < 0.0001). The IARC is a leading international authority on carcinogenicity assessments, and its significantly different human carcinogenicity classifications of identical chemicals indicate that: 1) in the absence of significant human data, the EPA is over-reliant on animal carcinogenicity data; 2) as a result, the EPA tends to over-predict carcinogenic risk; and 3) the true predictivity for human carcinogenicity of animal data is even poorer than is indicated by EPA figures alone. The EPA policy of erroneously assuming that tumours in animals are indicative of human carcinogenicity is implicated as a primary cause of these errors.     

The carcinoGENOMICS project: critical selection of model compounds for the development of omics-based in vitro carcinogenicity screening assays

Recent changes in the European legislation of chemical-related substances have forced the scientific community to speed up the search for alternative methods that could partly or fully replace animal experimentation. The Sixth Framework Program project carcinoGENOMICS was specifically raised to develop omics-based in vitro screens for testing the carcinogenic potential of chemical compounds in a pan-European context. This paper provides an in-depth analysis of the complexity of choosing suitable reference compounds used for creating and fine-tuning the in vitro carcinogenicity assays. First, a number of solid criteria for the selection of the model compounds are defined. Secondly, the strategy followed, including resources consulted, is described and the selected compounds are briefly illustrated. Finally, limitations and problems encountered during the selection procedure are discussed. Since selecting an appropriate set of chemicals is a frequent impediment in the early stages of similar research projects, the information provided in this paper might be extremely valuable.     

Application of in vitro cell transformation assays in regulatory toxicology for pharmaceuticals, chemicals, food products and cosmetics

Two year rodent bioassays play a key role in the assessment of carcinogenic potential of chemicals to humans. The seventh amendment to the European Cosmetics Directive will ban in 2013 the marketing of cosmetic and personal care products that contain ingredients that have been tested in animal models. Thus 2-year rodent bioassays will not be available for cosmetics/personal care products. Furthermore, for large testing programs like REACH, in vivo carcinogenicity testing is impractical. Alternative ways to carcinogenicity assessment are urgently required. In terms of standardization and validation, the most advanced in vitro tests for carcinogenicity are the cell transformation assays (CTAs). Although CTAs do not mimic the whole carcinogenesis process in vivo, they represent a valuable support in identifying transforming potential of chemicals. CTAs have been shown to detect genotoxic as well as non-genotoxic carcinogens and are helpful in the determination of thresholds for genotoxic and non-genotoxic carcinogens. The extensive review on CTAs by the OECD (OECD (2007) Environmental Health and Safety Publications, Series on Testing and Assessment, No. 31) and the proven within- and between-laboratories reproducibility of the SHE CTAs justifies broader use of these methods to assess carcinogenic potential of chemicals.     

Multi-target spectral moment QSAR versus ANN for antiparasitic drugs against different parasite species

There are many of pathogen parasite species with different susceptibility profile to antiparasitic drugs. Unfortunately, almost QSAR models predict the biological activity of drugs against only one parasite species. Consequently, predicting the probability with which a drug is active against different species with a single unify model is a goal of the major importance. In so doing, we use Markov Chains theory to calculate new multi-target spectral moments to fit a QSAR model that predict by the first time a mt-QSAR model for 500 drugs tested in the literature against 16 parasite species and other 207 drugs no tested in the literature using spectral moments. The data was processed by linear discriminant analysis (LDA) classifying drugs as active or non-active against the different tested parasite species. The model correctly classifies 311 out of 358 active compounds (86.9%) and 2328 out of 2577 non-active compounds (90.3%) in training series. Overall training performance was 89.9%. Validation of the model was carried out by means of external predicting series. In these series the model classified correctly 157 out 190, 82.6% of antiparasitic compounds and 1151 out of 1277 non-active compounds (90.1%). Overall predictability performance was 89.2%. In addition we developed four types of non Linear Artificial neural networks (ANN) and we compared with the mt-QSAR model. The improved ANN model had an overall training performance was 87%. The present work report the first attempts to calculate within a unify framework probabilities of antiparasitic action of drugs against different parasite species based on spectral moment analysis.     

QSAR-based solubility model for drug-like compounds

Solubility plays a very important role in the selection of compounds for drug screening. In this context, a QSAR model was developed for predicting water solubility of drug-like compounds. First, a set of relevant parameters for establishing a drug-like chemical space was defined. The comparison of chemical structures from the FDAMDD and PHYSPROP databases allowed the selection of properties that were more efficient in discriminating drug-like compounds from other chemicals. These filters were later on applied to the PHYSPROP database and 1174 chemicals fulfilling these criteria and with experimental solubility information available at 25 °C were retained. Several QSAR solubility models were developed from this set of compounds, and the best one was selected based on the accuracy of correct classifications obtained for randomly chosen training and validation subsets. Further validation of the model was performed with a set of 102 drugs for which experimental solubility data have been recently reported. A good agreement between the predictions and the experimental values confirmed the reliability of the QSAR model.     

Update of carcinogenicity studies in animals and humans of 535 marketed pharmaceuticals

This survey is a compendium of information retrieved on carcinogenicity in animals and humans of 535 marketed pharmaceuticals whose expected clinical use is continuous for at least 6 months or intermittent over an extended period of time. Of the 535 drugs, 530 have the result of at least one carcinogenicity assay in animals, and 279 (52.1%) of them gave a positive response in at least one assay. Only 186 drugs (34.8%) have retrievable information on carcinogenicity in humans, and 104 of them gave to a variable extent evidence of a potential carcinogenic activity. Concerning the correlation between results obtained in animals and epidemiological findings, 58 drugs gave at least one positive result in carcinogenicity assays performed in animals and to a variable extent displayed evidence of carcinogenicity in humans, but 97 drugs tested positive in animals and were noncarcinogenic in humans or vice versa. Our findings, which are in agreement with previous studies, indicate that the evaluation of the benefit/carcinogenic risk ratio should be always made in prescribing a drug.