Statistical exploration of four major genotoxicity data bases: an overview.
This report puts into perspective a series of exploratory statistical analyses carried out on the major genotoxicity data bases. While large compilations of data, even though computerized, suffer from their own size and are quite intractable to scientific reflection and judgement, the multivariate data analysis methods used by us are specifically designed for reorganising the information in a rational way and highlighting the underlying regularities of the data. The analyses reported here refer to the following data bases: the International Program for the Evaluation of Short-Term Tests for Carcinogens, the International Program on Chemical Safety Collaborative Study on In Vitro Assays, the Gene-Tox data base, and a subset of the U.S. National Toxicology Program data. Although the various data bases consisted of different sets of chemicals and had different underlying rationales, a number of invariant associations among short-term test performances were highlighted. The overall evidence indicated that the traditional classification of assays (according to the criteria of genetic end-point and phylogenetic position of the assays) was in contrast with the actual, operational similarities among assay performances, in that the experimental responses of the tests to the large variety of chemicals under consideration pointed to an alternative classification scheme. This consisted of three major classes: 1) a class comprising the in vivo assays; 2) a class grouping together many of the most widely used in vitro assays (Salmonella, chromosomal aberrations, and sister chromatid exchanges in Chinese hamster ovary cells, the various mutation tests in mammalian cell systems, etc.); 3) a second in vitro assay class (with Syrian hamster embryo cell transformation, Saccharomyces cerevisiae XV185-14C, B. subtilis rec-, Escherichia coli pol A). Such classes had clearly differentiated features with respect to carcinogenicity prediction. The implications of these findings for the current debate on mutagenicity testing are discussed.
Benigni
R
R
Istituto Superiore di Sanità, Rome, Italy.
Giuliani
A
A
D002273:Carcinogens / Q000494:pharmacology; D007256:Information Systems; D009152:Mutagenicity Tests / Q000379:methods*; D011237:Predictive Value of Tests; D013223:Statistics as Topic; D014116:Toxicology
D002273:Carcinogens