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

doi:10.1016/0027-5107(91)90159-L

Mutation Research/Fundamental and Molecular Mechanisms of Mutagenesis

Volume 250, Issues 1–2, September–October 1991, Pages 25-33

https://doi.org/10.1016/0027-5107(91)90159-L Get rights and content

Abstract

The CASE structure-activity relational method was used to predict the mutagenicity, cytogenotoxicity, carcinogenicity, sensory irritation, male rat-specific α2μ-nephrotoxicity and maximum tolerated dose of a population of molecules (N⩾1300). 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.

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Cited by (5)

Computational predictive programs (expert systems) in toxicology
1997, Toxicology
The increasing number of pollutants in the environment raises the problem of the toxicological risk evaluation of these chemicals. Several so called expert systems (ES) have been claimed to be able to predict toxicity of certain chemical structures. Different approaches are currently used for these ES, based on explicit rules derived from the knowledge of human experts that compiled lists of toxic moieties — for instance in the case of programs called HazardExpert and DEREK — or relying on statistical approaches, as in the CASE and TOPKAT programs. Here we describe and compare these and other intelligent computer programs because of their utility in obtaining at least a first rough indication of the potential toxic activity of chemicals.
Application of SAR methods to non-congeneric data bases assocated with carcinogenicity and mutagenicity: Issues and approachs
1994, Mutation Research - Fundamental and Molecular Mechanisms of Mutagenesis
In both industry and government, structure-activity relationships (SAR) are capable of playing an important decision-support role in estimating the potential mutagenicity or carcinogenicity of chemicals for which bioassay test results are unavailable. Traditional SAR modeling approaches, however, are usually restricted to the consideration of structurally similar chemical congeners. The highly structurally diverse nature of current carcinogenicity and mutagenicity data bases has motivated development of more general SAR approaches, potentially applicable to the treatment of diverse, non-congeneric mutagenicity and carcinogenicity data bases. Three specific approaches are considered in some detail — Ashby's structural alert moedl, classified as a “rule-based” SAR approach, and the computerized CASE fragment-base method and TOPKAT linear discriminant equation method, both classified as “correlative” SAR approaches. Relative strengths and limitations, and a number of common features and important distinctions betwee these 3 methods are discussed. Rule-base methods are highly flexible and able to incorporate many different types of relevant information, yet are biased towards current knowledge, viewpoints, and mechanistic assumptions, that may or may not hold true. Correlative SAR methods are less biased and offer the promise of “discorvering” potentially new SAR associations that could lend fresh insight into the basis for a structure-activity association. However, problems associated with their application to non-congeneric data bases relate to: modeling multiple or overlapping mechanisms of action with a single relationship; defining the range of applicability of models in complex multi-dimensional structure-activity space; assigning confidence levels to predictions in the absence of knowledge concerning mechanisms of activity; and determining the potential mechanistic significance of diervse model parameters. It is argued that many of these concerns can be partially alleviated by careful application of statistical procedures, scrutiny of model results, and estabilishment of reasoned limits to the range of model applicability. The most significant confidence-building measure, however, will be a rationalization of the correlative SAR model and model parameters in terms of principles of chemical reactivity and postulated molecular mechanism(s) for the biological activity. Hence, it is recommended that models and model descriptors be designed to facilitate mechanistic interpretation and hypothesis generation. Finally, problems in comparing the relative predictive capabilities of different SAR approaches are discussed, and strategies for SAR investigation involving integration of existing techniques are suggested.
1,4-Dioxane: prediction of in vivo clastogenicity
1992, Mutation Research/Genetic Toxicology
1,4-Dioxane was analyzed with the CASE program to determine the structural basis of its potential genotoxicity and carcinogenicity. These investigations led to the prediction that while 1,4-dioxane was not genotoxic in vitro, it was an inducer of micronuclei in the bone marrow of rats and a carcinogen for both rats and mice. If it is assumed that the induction of micronuclei is the result of DNA damage, then this potential and the previous report of the in vivo induction of DNA strand breaks in rat liver raise the possibility of a genotoxic action for 1,4-dioxane. However it is also conceivable that we have identified a structural feature which contributes to the induction of micronuclei by a non-genotoxic mechanism.
Quantification of the predictivity of some short-term assays for carcinogenicity in rodents
1991, Mutation Research/Environmental Mutagenesis and Related Subjects
QSAR in Toxicology. 3. Prediction of Chronic Toxicities
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Research paperImplications of newly recognized relationships between mutagenicity, genotoxicity and carcinogenicity of molecules

Abstract

Mutation Res.

Mutation Res.

Mutation Res.

Mutation Res.

Fund. Appl. Toxicol.

Mutation Res.

Toxicol. Appl. Pharmacol.

Mutation Res.

Toxicol. Appl. Pharmacol.

Chem. -Biol. Interact.

Mutation Res.

Mutation Res.

Mutation Res.

Mutation Res.

Toxicol. Appl. Pharmacol.

Mutation Res.

Reg. Toxicol. Pharmacol.

Sensory irritation by airborne chemicals

CRC Crit. Rev. Toxicol.

Sensory irritation by airborne chemicals: A basis to establish acceptable levels of exposure

Fundamental structural alerts to potential carcinogenicity or non-carcinogenecity

Environ. Mutagen.

Toxicity and carcinogenic potency

Risk Anal.

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