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.

[1]  Alessandro Giuliani,et al.  Quantitative Structure—Activity Relationships of Mutagenic and Carcinogenic Aromatic Amines , 2000 .

[2]  J. Huff,et al.  The carcinogenesis bioassay in perspective: application in identifying human cancer hazards. , 1995, Environmental health perspectives.

[3]  R Benigni,et al.  Quantitative structure-based modeling applied to characterization and prediction of chemical toxicity. , 1998, Methods.

[4]  R Benigni,et al.  Profiles of chemically-induced tumors in rodents: quantitative relationships. , 1998, Mutation research.

[5]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[6]  K S Crump,et al.  Correlation between carcinogenic potency of chemicals in animals and humans. , 1988, Risk Analysis.

[7]  R Benigni,et al.  QSAR models for discriminating between mutagenic and nonmutagenic aromatic and heteroaromatic amines , 1998, Environmental and molecular mutagenesis.

[8]  L. Gold,et al.  Supplement to the Carcinogenic Potency Database (CPDB): results of animal bioassays published in the general literature in 1993 to 1994 and by the National Toxicology Program in 1995 to 1996. , 1999, Environmental health perspectives.

[9]  C. Russom,et al.  Predicting modes of toxic action from chemical structure: Acute toxicity in the fathead minnow (Pimephales promelas) , 1997 .

[10]  R Benigni,et al.  Prediction of rodent carcinogenicity of aromatic amines: a quantitative structure-activity relationships model. , 2001, Carcinogenesis.

[11]  T. Fujita.  Recent Success Stories Leading to Commercializable Bioactive Compounds with the Aid of Traditional QSAR Procedures , 1997 .

[12]  E Novellino,et al.  Toward a quantitative comparative toxicology of organic compounds. , 1989, Critical reviews in toxicology.

[13]  Weida Tong,et al.  Prediction of estrogen receptor binding for 58,000 chemicals using an integrated system of a tree-based model with structural alerts. , 2001, Environmental health perspectives.

[14]  A.M. Richard,et al.  AI and SAR approaches for predicting chemical carcinogenicity: Survey and status report , 2002, SAR and QSAR in environmental research.

[15]  A. Debnath,et al.  A QSAR investigation of the role of hydrophobicity in regulating mutagenicity in the ames test: 1. Mutagenicity of aromatic and heteroaromatic amines in Salmonella typhimurium TA98 and TA100 , 1992, Environmental and molecular mutagenesis.

[16]  H. Könemann.  Quantitative structure-activity relationships in fish toxicity studies. Part 1: relationship for 50 industrial pollutants. , 1981, Toxicology.

[17]  R Benigni.  The first US National Toxicology Program exercise on the prediction of rodent carcinogenicity: definitive results. , 1997, Mutation research.

[18]  J. Hermens,et al.  Classifying environmental pollutants: Part 3. External validation of the classification system. , 2000, Chemosphere.

[19]  Joop L. M. Hermens,et al.  Quantitative Structure-Activity Relationships of Environmental Pollutants , 1989 .

[20]  Alessandro Giuliani,et al.  Tumor profiles and carcinogenic potency in rodents and humans: Value for cancer risk assessment , 1999 .

[21]  Corwin Hansch,et al.  Comparative QSAR: Toward a Deeper Understanding of Chemicobiological Interactions. , 1996, Chemical reviews.

[22]  R. Tennant,et al.  Prediction of the outcome of rodent carcinogenicity bioassays currently being conducted on 44 chemicals by the National Toxicology Program. , 1990, Mutagenesis.

[23]  Exploring QSAR. , 1995, Environmental science & technology.

[24]  J. Hermens,et al.  Classifying environmental pollutants , 1992 .

[25]  J. Huff,et al.  Evolution of cancer etiology and primary prevention. , 2001, Environmental health perspectives.

[26]  Romualdo Benigni,et al.  The Development and Validation of Expert Systems for Predicting Toxicity The Report and Recommendations of an ECVAM / ECB Workshop ( ECVAM Workshop 24 ) , 2002 .

[27]  C. Hansch,et al.  Comparative QSAR: Radical Reactions of Benzene Derivatives in Chemistry and Biology , 1998 .

[28]  Jack A. Taylor,et al.  Avoided and avoidable risks of cancer. , 1997, Carcinogenesis.

[29]  Alessandro Giuliani,et al.  Quantitative Structure-Activity Relationship (QSAR) - Studies of Mutagens and Carcinogens , 1996 .

[30]  D. Bristol,et al.  The NIEHS Predictive-Toxicology Evaluation Project. , 1996, Environmental health perspectives.