What indication is common to different genotoxicity data bases?

Mutat Res. 1991 Oct;253(2):115-21. doi: 10.1016/0165-1161(91)90124-q.

Abstract

This paper studies the relationships among 4 in vitro assays: Salmonella mutation (STY), mouse lymphoma L5178Y cell mutation (MLY), chromosomal aberrations in CHO cells (CHA), and sister-chromatid exchanges in CHO cells (SCE), in 3 different data bases: U.S. National Toxicology Program (NTP), International Program for the Evaluation of Short-Term Tests for Carcinogens (IPESTTC), and International Program on Chemical Safety (IPCS). The analysis is performed by modeling each data base with factor analysis. With this tool, it has been possible to separate the different elements (or components) which play a role in each data base. It has also been possible to demonstrate that--together with some specificities of the data bases--there is a common effect which is independent of the data bases, and which typically represents the 'true' relationships among the assays. This element explains 69% of the information contained in NTP, 50% of that of IPESTTC, and 30% of that of IPCS. This common evidence indicates that the responses of STY and CHA to the 'universe' of chemicals are relatively similar, although STY is a bacterial mutation system and CHA is a mammalian cell test for chromosomal damage. The other similarity apparent from this analysis is the one between MLY (mutation in mouse cells) and SCE (cytogenetic evidence in hamster cells). The implication of this result is 2-fold. On the one hand, it is extremely reassuring that the 3 most important comparative studies agree and show common evidence, and this can be recognized rationally. On the other hand, this evidence implies that the scientists involved in mutagenicity research must face the task of exploring and explaining such relationships.

Publication types

  • Comparative Study

MeSH terms

  • Animals
  • CHO Cells
  • Carcinogenicity Tests / statistics & numerical data*
  • Chromosome Aberrations
  • Cricetinae
  • Databases, Factual / statistics & numerical data*
  • Factor Analysis, Statistical
  • Mice
  • Models, Theoretical
  • Mutagenicity Tests / statistics & numerical data*
  • Salmonella / genetics
  • Sister Chromatid Exchange
  • Tumor Cells, Cultured