Predicting chemical carcinogenesis in rodents: The state of the art in light of a comparative exercise

Within a recent comparative exercise, different approaches to the prediction of rodent carcinogenicity were challenged on a common set of chemicals bioassayed by the U.S. National Toxicology Program. The approaches were of very different natures. Some prediction systems looked for relationships between carcinogenicity and other, more quickly detectable biological events (activity-activity relationships, AAR). Some approaches tended to find structure-activity relationships (SAR). To give an objective evaluation of the results of the exercise, we have analyzed the rodent results and the predictions with the multivariate data analysis methods. The calculated performances varied according to the adopted carcinogenicity classification of the chemicals. When the four rodent results were summarized into a final + or − call, the Tennant approach (AAR method) showed the best performance (about 75% accuracy), whereas the best SAR systems had 60–65% accuracy. A common limitation of almost all the systems was the lack of specificity (too many false positives). Based on these results, better concordance was obtained when the input information was the very costly (and closer to the final endpoint) biological data, rather than the inexpensive (and farther from the endpoint) knowledge of the chemical structure. However, when the rodent results were summarized into a carcinogenicity classification that maintained, to some extent, the gradation intrinsic to the original experimental data, the performance of the AAR systems declined, and the SAR approaches showed a better performance. The difficulty in evaluating the various approaches was further complicated because of a fundamental difference in the approaches themselves: some approaches were ‘pure’ prediction methods (i.e. their predictions were rigorously based on information not inclusive of carcinogenicity); other approaches (e.g. Tennant, Weisburger) used ‘mixed’ information, inclusive of known carcinogenicity results from experiments performed before the NTP bioassays. As far as the SAR systems are concerned, their sets of predictions showed a fundamental similarity. This happened in spite of the extremely different procedures adopted to treat the chemical formula (initial information): very simple calculations (Benigni), intuition of the experts (Weisburger and Lijinsky), sophisticated computer programs (TOPKAT and CASE). The results of the Bakale Ke method, based on the experimental measurement of the chemical electrophilicity, and of the Salmonella typhimurium mutagenicity assay were similar to the patterns of predictions of the SAR methods.     

A survey of the Predictive Toxicology Challenge 2000-2001

MOTIVATION: The Predictive Toxicology Challenge (PTC) was initiated to stimulate the development of advanced techniques for predictive toxicology models. The goal of this challenge was to compare different approaches for the prediction of rodent carcinogenicity, based on the experimental results of the US National Toxicology Program (NTP). RESULTS: 111 sets of predictions for 185 compounds have been evaluated on quantitative and qualitative scales to select the most predictive models and those with the highest toxicological relevance. The accuracy of the submitted predictions was between 25 and 79 %. An evaluation of the most accurate models by toxicological experts showed, that it is still hard for domain experts to interpret the submitted models and to put them into relation with toxicological knowledge. AVAILABILITY: PTC details and data can be found at: http://www.predictive-toxicology.org/ptc/.     

The alkaline single cell gel electrophoresis assay with mouse multiple organs: results with 30 aromatic amines evaluated by the IARC and U.S. NTP

The genotoxicity of 30 aromatic amines selected from IARC (International Agency for Research on Cancer) groups 1, 2A, 2B and 3 and from the U.S. NTP (National Toxicology Program) carcinogenicity database were evaluated using the alkaline single cell gel electrophoresis (SCG) (Comet) assay in mouse organs. We treated groups of four mice once orally at the maximum tolerated dose (MTD) and sampled stomach, colon, liver, kidney, bladder, lung, brain, and bone marrow 3, 8 and 24 h after treatment. For the 20 aromatic amines that are rodent carcinogens, the assay was positive in at least one organ, suggesting a high predictive ability for the assay. For most of the SCG-positive aromatic amines, the organs exhibiting increased levels of DNA damage were not necessarily the target organs for carcinogenicity. It was rare, in contrast, for the target organs not to show DNA damage. Organ-specific genotoxicity, therefore, is necessary but not sufficient for the prediction of organ-specific carcinogenicity. For the 10 non-carcinogenic aromatic amines (eight were Ames test-positive and two were Ames test-negative), the assay was negative in all organs studied. In the safety evaluation of chemicals, it is important to demonstrate that Ames test-positive agents are not genotoxic in vivo. Chemical carcinogens can be classified as genotoxic (Ames test-positive) and putative non-genotoxic (Ames test-negative) carcinogens. The alkaline SCG assay, which detects DNA lesions, is not suitable for identifying non-genotoxic carcinogens. The present SCG study revealed a high positive response ratio for rodent genotoxic carcinogens and a high negative response ratio for rodent genotoxic non-carcinogens. These results suggest that the alkaline SCG assay can be usefully used to evaluate the in vivo genotoxicity of chemicals in multiple organs, providing for a good assessment of potential carcinogenicity.     

Computer-aided rodent carcinogenicity prediction

The potential of the computer program PASS (Prediction Activity Spectra for Substances) to predict rodent carcinogenicity for chemical compounds was studied. PASS predicts carcinogenicity of chemical compounds on the basis of their structural formula and of structure-activity relationship analysis of known carcinogens and non-carcinogens. The data on structures and experimental results of 2-year carcinogenicity assays for 412 chemicals from the NTP (National Toxicological Program) and 1190 chemicals from the CPDB (Carcinogenic Potency Database) were used in our study. The predictions take into consideration information about species and sex of animals. For evaluation of the predictive accuracy we used two procedures: leave-one-out cross-validation (LOO CV) and leave-20%-out cross-validation. In the last case we randomly divided the studied data set 20 times into two subsets. The data from the first subset, containing 80% of the compounds, were added to the PASS training set (which includes about 46,000 compounds with about 1500 biological activity types collected during the last 20 years to predict biological activity spectra), the second subset with 20% of the compounds was used as an evaluation set. The mean accuracy of prediction calculated by LOO CV is about 73% for NTP compounds in the 'equivocal' category of carcinogenic activity and 80% for NTP compounds in the 'evidence' category of carcinogenicity. The mean accuracy of prediction for the CPDB database is 89.9% calculated by LOO CV and 63.4% calculated by leave-20%-out cross-validation. Influence of incorporation of species and sex data on the accuracy of carcinogenicity prediction was also investigated. It was shown that the accuracy was increased only for data on male animals.     

Structure-activity relationships in the rat hepatocyte DNA-repair test for 300 chemicals

312 chemicals/mixtures were tested for genotoxicity in the rat hepatocyte/DNA-repair test. A variety of structure-activity relationships was evident. Of the 309 pure chemicals, 142 were positive. Of these, 43 were judged by IARC to have sufficient or limited evidence of carcinogenicity and none of the remainder was a proven noncarcinogen. Among the 167 negative chemicals, 44 were carcinogens. Some of these are known to be genotoxic in other systems, but based on several lines of evidence, many are considered to be epigenetic carcinogens that lack the ability to react with DNA and rather lead to neoplasia by nongenotoxic mechanisms.     

Classification according to chemical structure, mutagenicity to Salmonella and level of carcinogenicity of a further 42 chemicals tested for carcinogenicity by the U.S. National Toxicology Program

This paper is an extension and update of an earlier review published in this journal (Ashby and Tennant, 1988). A summary of the rodent carcinogenicity bioassay data on a further 42 chemicals tested by the U.S. National Toxicology Program (NTP) is presented. An evaluation of each chemical for structural alerts to DNA-reactivity is also provided, together with a summary of its mutagenicity to Salmonella. The 42 chemicals were numbered and evaluated as an extension of the earlier analysis of 222 NTP chemicals. The activity patterns and conclusions derived from the earlier study remain unchanged for the larger group of 264 chemicals. Based on the extended database of 264 NTP chemicals, the sensitivity of the Salmonella assay for rodent carcinogens is 58% and the specificity for the non-carcinogens is 73%. A total of 32 chemicals were defined as equivocal for carcinogenicity and, of these, 11 (34%) are mutagenic to Salmonella. An evaluation is made of instances where predictions of carcinogenicity, based on structural alerts, disagree with the Salmonella mutagenicity result (12% of the database). The majority of the disagreements are for structural alerts on non-mutagens, and that places these alerts as a sensitive primary screen with a specificity lower than that of the Salmonella assay. That analysis indicates some need for assays complementary to the Salmonella test when screening for potential genotoxic carcinogens. It also reveals that the correlation between structural alerts and mutagenicity to Salmonella is probably greater than 90%. Chemicals predicted to show Michael-type alkylating activity (i.e., CH2 = CHX; where X = an electron-withdrawing group, e.g. acrylamide) have been confirmed as a structural alert, and the halomethanes (624 are possible) have been classified as structurally-alerting. To this end an extended carcinogen-alert model structure is presented. Among the 138 NTP carcinogens now reviewed, 45 (33%) are non-mutagenic to Salmonella and possess a chemical structure that does not alert to DNA-reactivity. These carcinogens therefore either illustrate the need for complementary genetic screening tests to the Salmonella assay, or they represent the group of non-genotoxic carcinogens referred to most specifically by Weisburger and Williams (1981); the latter concept is favoured.     

Putting the Predictive Toxicology Challenge into perspective: reflections on the results

MOTIVATION: Chemical carcinogenicity is of primary interest, because it drives much of the current regulatory actions regarding new and existing chemicals, and its experimental determination involves time-consuming and expensive animal testing. Both academia and private companies are actively trying to develop SAR and QSAR models. This paper reviews the new Predictive Toxicology Challenge (PTC) results, by putting them into the context of previous attempts. RESULTS: A marked dependency of the prediction ability of the different algorithms on the training sets was observed, pointing to a still insufficient coverage of the chemical carcinogens 'universe'. A theoretical treatment of the possible developments of the Artificial Intelligence approaches is sketched.     

Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action

Background

Despite an overall decrease in incidence of and mortality from cancer, about 40% of Americans will be diagnosed with the disease in their lifetime, and around 20% will die of it. Current approaches to test carcinogenic chemicals adopt the 2-year rodent bioassay, which is costly and time-consuming. As a result, fewer than 2% of the chemicals on the market have actually been tested. However, evidence accumulated to date suggests that gene expression profiles from model organisms exposed to chemical compounds reflect underlying mechanisms of action, and that these toxicogenomic models could be used in the prediction of chemical carcinogenicity.

Results

In this study, we used a rat-based microarray dataset from the NTP DrugMatrix Database to test the ability of toxicogenomics to model carcinogenicity. We analyzed 1,221 gene-expression profiles obtained from rats treated with 127 well-characterized compounds, including genotoxic and non-genotoxic carcinogens. We built a classifier that predicts a chemical''s carcinogenic potential with an AUC of 0.78, and validated it on an independent dataset from the Japanese Toxicogenomics Project consisting of 2,065 profiles from 72 compounds. Finally, we identified differentially expressed genes associated with chemical carcinogenesis, and developed novel data-driven approaches for the molecular characterization of the response to chemical stressors.

Conclusion

Here, we validate a toxicogenomic approach to predict carcinogenicity and provide strong evidence that, with a larger set of compounds, we should be able to improve the sensitivity and specificity of the predictions. We found that the prediction of carcinogenicity is tissue-dependent and that the results also confirm and expand upon previous studies implicating DNA damage, the peroxisome proliferator-activated receptor, the aryl hydrocarbon receptor, and regenerative pathology in the response to carcinogen exposure.     

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.     

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.     

Implications of newly recognized relationships between mutagenicity, genotoxicity and carcinogenicity of molecules

The CASE structure-activity relational method was used to predict the mutagenicity, cytogenotoxicity, carcinogenicity, sensory irritation, male rat-specific 2μ-nephrotoxicity and maximum tolerated dose of a population of molecules (N1300). These chemicals were then sorted out by their predicted responses to specific tests and sub-populations of molecules with different prevalence with respect to described endpoints were constructed, i.e. 0–100% prevalences of mutagens, rodent carcinogens and SCE inducers. The predited properties of these populations were analyzed and the ovelap among tests was determined. The false-positive and false-negative predictions.     

The carcinogenicity prediction and battery selection (CPBS) method: a Bayesian approach

Recently, a large number of relatively inexpensive in vitro short-term tests have been developed to help predict the carcinogenicity of chemicals. The carcinogenicity prediction and battery selection (CPBS) method utilizes the results of such short-term tests to screen for chemicals that are most likely to cause cancer. The method is an integrated approach for analyzing large, often sparsely filled, data bases containing short-term test results, which often have only marginal representation of known non-carcinogens. The CPBS method is developed for the purpose of (i) determining the reliability and predictive capability of individual and batteries of short-term tests, and (ii) developing a strategy for formulating and selecting optimally preferred batteries of short-term tests for screening chemicals for further testing. The term 'optimally preferred' connotes the best acceptable combination of tests in terms of trade-offs among the multiple attributes of each test and resulting battery (e.g., cost, sensitivity, specificity, etc). The CPBS method consists of 5 major tasks: (1) data consolidation, (2) parameter estimation, (3) predictivity calculation, (4) battery selection and (5) risk assessment. Although there is a great need for more research and improvement, the CPBS method at its present stage should add an important method to the maze of the thousands of new chemicals that are introduced into drugs, foods, consumer goods and to the environment every year. This method should also provide an enhanced identification procedure for classifying chemicals more accurately as suspected carcinogens or non-carcinogens.     

Investigating the Different Mechanisms of Genotoxic and Non-Genotoxic Carcinogens by a Gene Set Analysis

Based on the process of carcinogenesis, carcinogens are classified as either genotoxic or non-genotoxic. In contrast to non-genotoxic carcinogens, many genotoxic carcinogens have been reported to cause tumor in carcinogenic bioassays in animals. Thus evaluating the genotoxicity potential of chemicals is important to discriminate genotoxic from non-genotoxic carcinogens for health care and pharmaceutical industry safety. Additionally, investigating the difference between the mechanisms of genotoxic and non-genotoxic carcinogens could provide the foundation for a mechanism-based classification for unknown compounds. In this study, we investigated the gene expression of HepG2 cells treated with genotoxic or non-genotoxic carcinogens and compared their mechanisms of action. To enhance our understanding of the differences in the mechanisms of genotoxic and non-genotoxic carcinogens, we implemented a gene set analysis using 12 compounds for the training set (12, 24, 48 h) and validated significant gene sets using 22 compounds for the test set (24, 48 h). For a direct biological translation, we conducted a gene set analysis using Globaltest and selected significant gene sets. To validate the results, training and test compounds were predicted by the significant gene sets using a prediction analysis for microarrays (PAM). Finally, we obtained 6 gene sets, including sets enriched for genes involved in the adherens junction, bladder cancer, p53 signaling pathway, pathways in cancer, peroxisome and RNA degradation. Among the 6 gene sets, the bladder cancer and p53 signaling pathway sets were significant at 12, 24 and 48 h. We also found that the DDB2, RRM2B and GADD45A, genes related to the repair and damage prevention of DNA, were consistently up-regulated for genotoxic carcinogens. Our results suggest that a gene set analysis could provide a robust tool in the investigation of the different mechanisms of genotoxic and non-genotoxic carcinogens and construct a more detailed understanding of the perturbation of significant pathways.     

Structural basis of carcinogenicity in rodents of genotoxicants and non-genotoxicants

A set of 189 chemicals tested in the National Toxicology Program Cancer Bioassay was subjected to analysis by CASE, the Computer-Automated Structure Evaluation system. In the data set, 63% of the chemicals were carcinogens, approx. 40% of the carcinogens were non-genotoxic, i.e., they possessed neither "structural alerts" for DNA reactivity as defined by Ashby and Tennant, 1988, nor were they mutagenic for Salmonella. The data base can be characterized as a "combined rodent" compilation as chemicals were characterized as "carcinogenic" if they were carcinogenic in either rats or mice or both. CASE identified 23 fragments which accounted for the carcinogenicity, or lack thereof, of most of the chemicals. The sensitivity and specificity were unexpectedly high: 1.00 and 0.86, respectively. Based upon the identified biophores and biophobes, CASE performed exceedingly well in predicting the activity of chemicals not included among the 189 in the original set. CASE predicted correctly the carcinogenicity of non-genotoxic carcinogens thereby suggesting a structural commonality in the action of this group of carcinogens. As a matter of fact biophores restricted to non-genotoxic carcinogens were identified as were "non-electrophilic" biophores shared by genotoxic and non-genotoxic carcinogens. The findings suggest that the CASE program may help in the elucidation of the basis of the action of non-genotoxic carcinogens.     

Genetic toxicology: can we design predictive in vivo assays?

The present analysis examines the assumptions in, the perceptions and predictivity of and the need for short-term tests (STTs) for genotoxicity in light of recent findings that most noncarcinogens from the National Toxicology Program are genotoxic (i.e., positive in one or more in vitro STTs). Reasonable assumptions about the prevalence for carcinogens (1-10% of all chemicals), the sensitivity of these STTs (ca. 90% of all carcinogens are genotoxic) and their estimated "false positive" incidence (60-75%) imply that the majority of chemicals elicit genotoxic responses and, consequently, that most in vitro genotoxins are likely to be noncarcinogenic. Thus, either the usual treatment conditions used in these in vitro STTS are producing a large proportion of artifactual and meaningless positive results or else in vitro mutagenicity is too common a property of chemicals to serve as a useful predictor of carcinogenicity or other human risk. In contrast, the limited data base on in vivo STTs suggests that the current versions of these assays may have low sensitivity which appears unlikely to improve without dropping either their 'short-term' aspect or the rodent carcinogenicity benchmark. It is suggested that in vivo genotoxicity protocols be modified to take into consideration both the fundamentals of toxicology as well as the lessons learned from in vitro genetic toxicology. In the meantime, while in vivo assays are undergoing rigorous validation, genetic toxicology, as currently practiced, should not be a formal aspect of chemical or drug development on the grounds that it is incapable of providing realistic and reliable information on human risk. It is urged that data generated in new, unvalidated in vivo genotoxicity assays be exempted from the normal regulatory reporting requirements in order to encourage industry to participate in the laborious and expensive development of this next phase of genetic toxicology.     

Dose-response and threshold-mediated mechanisms in mutagenesis: statistical models and study design

The objective of this paper is to review the use, in mutagenesis, of various mathematical models to describe the dose-response relationship and to try to identify thresholds. It is often taken as axiomatic that genotoxic carcinogens could damage DNA at any level of exposure, leading to a mutation, and that this could ultimately result in tumour development. This has led to the assumption that for genotoxic chemicals, there is no discernible threshold. This assumption is increasingly being challenged in the case of aneugens. The distinction between 'absolute' and 'pragmatic' thresholds is made and the difficulties in determining 'absolute' thresholds using hypothesis testing approaches are described. The potential of approaches, based upon estimation rather than statistical significance for the characterization of dose-response relationships, is stressed. The achievement of a good fit of a mathematical model to experimental data is not proof that the mechanism supposedly underlying this model is operating. It has been argued, in the case of genotoxic chemicals, that any effects produced by a genotoxic chemical which augments that producing a background incidence in unexposed individuals will lead to a dose-response relationship that is non-thresholded and is linear at low doses. The assumptions underlying this presumption are explored in the context of the increasing knowledge of the mechanistic basis of mutagenicity and carcinogenicity. The possibility that exposure to low levels of genotoxic chemicals may induce and enhance defence and repair mechanisms is not easily incorporated into many of the existing mathematical models and should be an objective in the development of the next generation of biologically based dose-response (BB-DR) models. Studies aimed at detecting or characterizing non-linearities in the dose-response relationship need appropriate experimental designs with careful attention to the choice of biomarker, number and selection of dose levels, optimum allocation of experimental units and appropriate levels of replication within and repetition of experiments. The characterization of dose-response relationships with appropriate measures of uncertainty can help to identify 'pragmatic' thresholds based upon biologically relevant criteria which can help in the regulatory process.     

Heritable and cancer risks of exposures to anticancer drugs: inter-species comparisons of covalent deoxyribonucleic acid-binding agents

In the past years, several methodologies were developed for potency ranking of genotoxic carcinogens and germ cell mutagens. In this paper, we analyzed six sub-classes of covalent deoxyribonucleic acid (DNA) binding antineoplastic drugs comprising a total of 37 chemicals and, in addition, four alkyl-epoxides, using four approaches for the ranking of genotoxic agents on a potency scale: the EPA/IARC genetic activity profile (GAP) database, the ICPEMC agent score system, and the analysis of qualitative and quantitative structure-activity and activity-activity relationships (SARs, AARs) between types of DNA modifications and genotoxic endpoints. Considerations of SARs and AARs focused entirely on in vivo data for mutagenicity in male germ cells (mouse, Drosophila), carcinogenicity (TD₅₀s) and acute toxicity (LD₅₀s) in rodents, whereas the former two approaches combined the entire database on in vivo and in vitro mutagenicity tests. The analysis shows that the understanding and prediction of rank positions of individual genotoxic agents requires information on their mechanism of action. Based on SARs and AARs, the covalent DNA binding antineoplastic drugs can be divided into three categories. Category 1 comprises mono-functional alkylating agents that primarily react with N7 and N3 moieties of purines in DNA. Efficient DNA repair is the major protective mechanism for their low and often not measurable genotoxic effects in repair-competent germ cells, and the need of high exposure doses for tumor induction in rodents. Due to cell type related differences in the efficiency of DNA repair, a strong target cell specificity in various species regarding the potency of these agents for adverse effects is found. Three of the four evaluation systems rank category 1 agents lower than those of the other two categories. Category 2 type mutagens produce O-alkyl adducts in DNA in addition to N-alkyl adducts. In general, certain O-alkyl DNA adducts appear to be slowly repaired, or even not at all, which make this kind of agents potent carcinogens and germ cell mutagens. Especially the inefficient repair of O-alkyl—pyrimidines causes the high mutational response of cells to these agents. Agents of this category give high potency scores in all four expert systems. The major determinant for the high rank positions on any scale of genotoxic of category 3 agents is their ability to induce primarily structural chromosomal changes. These agents are able to cross-link DNA. Their high intrinsic genotoxic potency appears to be related to the number of DNA cross-links per target dose unit they can induce. A confounding factor among category 3 agents is that often the genotoxic endpoints occur closed to or toxic levels, and that the width of the mutagenic dose range, i.e., the dose area between the lowest observed effect level and the LD₅₀, is smaller (usually no more than 1 logarithmic unit) than for chemicals of the other two categories. For all three categories of genotoxic agents, strong correlations are observed between their carcinogenic potency, acute toxicity and germ cell specificity.     

Thalidomide and metabolites: indications of the absence of 'genotoxic' carcinogenic potentials

Because of the reintroduction into human therapeutics of thalidomide, a recognized developmental toxicant in humans, there has been concern about its potential for inducing other health effects as well. The present study is concerned with the possible mutagenicity and carcinogenicity of this chemical. Using the expert system, META, a series of putative metabolites of thalidomide was generated. In addition to the known or hypothesized metabolites of thalidomide (N=12), a number of additional putative metabolites (N=131) were identified by META. The structures of these chemicals were subjected to structure-activity analyses using predictive CASE/MULTICASE models of developmental toxicity, rodent carcinogenicity and mutagenicity in Salmonella. While thalidomide and some of its putative metabolites were predicted to be developmental toxicants, none of them were predicted to be rodent carcinogens. Putative metabolites containing the hydroxamic acid or hydroxylamine moieties were predicted to be mutagens. None of the 'known' metabolites of thalidomide contained these reactive moieties. Whether such intermediates are indeed generated or whether they are generated and are either unstable in the presence of oxygen or react rapidly with nucleophiles is unknown.