Analysis of Negative Historical Control Group Data from the In Vitro Micronucleus Assay Using TK6 Cells

  • Publication Date :
  • Publication Type : Journal Article
  • Author(s) : Lovell DP, Fellows M, Marchetti F, Christiansen J, Elhajouji A, Hashimoto K, Kasamoto S, Li Y, Masayasu O, Moore MM, Schuler M, Smith R, Stankowski Jr. LF, Tanaka J, Tanir JY, Thybaud V, Van Goethem F, & Whitwell J
  • Journal Name : Mutation Research/Genetic Toxicology and Environmental Mutagenesis

The recent revisions of the Organisation for Economic Co-operation and Development (OECD) genetic toxicology test guidelines emphasize the importance of historical negative controls both for data quality and interpretation. The goal of a HESI Genetic Toxicology (GTTC) Committee workgroup was to collect data from participating laboratories and to conduct a statistical analysis to understand and publish the range of values that are normally seen in experienced laboratories using TK6 cells to conduct the in vitro micronucleus assay. Data from negative control samples from in vitro micronucleus assays using TK6 cells from 13 laboratories were collected using a standard collection form. Although in some cases statistically significant differences can be seen within laboratories for different test conditions, they were very small. The mean incidence of micronucleated cells/1000 cells ranged from 3.2/1000 to 13.8/1000. These almost four-fold differences in micronucleus levels cannot be explained by differences in scoring method, presence or absence of exogenous metabolic activation (S9), length of treatment, presence or absence of cytochalasin B or different solvents used as vehicles. The range of means from the four laboratories using flow cytometry methods (3.7-fold: 3.5–12.9 micronucleated cells/1000 cells) was similar to that from the nine laboratories using other scoring methods (4.3-fold: 3.2–13.8 micronucleated cells/1000 cells). No laboratory could be identified as an outlier or as showing unacceptably high variability.

Quality Control (QC) methods applied to analyse the intra-laboratory variability showed that there was evidence of inter-experimental variability greater than would be expected by chance (i.e. over-dispersion). However, in general, this was low.

This study demonstrates the value of QC methods in helping to analyse the reproducibility of results, building up a ‘normal’ range of values, and as an aid to identify variability within a laboratory in order to implement processes to maintain and improve uniformity.

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