Interpreting in vitro micronucleus positive results: simple biomarker matrix discriminates clastogens, aneugens, and misleading positive agents.

Abstract

The specificity of in vitro mammalian cell genotoxicity assays is low, as they yield a high incidence of positive results that are not observed in animal genotoxicity and carcinogenicity tests, that is, "misleading" or "irrelevant" positives. We set out to develop a rapid and effective follow-up testing strategy that would predict whether apparent in vitro micronucleus-inducing effects are due to a clastogenic, aneugenic, or secondary irrelevant mode(s) of action. Priority was given to biomarkers that could be multiplexed onto flow cytometric acquisition of micronucleus frequencies, or that could be accomplished in parallel using a homogeneous-type assay. A training set of 30 chemicals comprised of clastogens, aneugens, and misleading positive chemicals was studied. These experiments were conducted with human TK6 cells over a range of closely spaced concentrations in a continuous exposure design. In addition to micronucleus frequency, the following endpoints were investigated, most often at time of harvest: cleaved Parp-positive chromatin, cleaved caspase 3-positive chromatin, ethidium monoazide bromide-positive chromatin, polyploid nuclei, phospho-histone H3-positive (metaphase) cells, tetramethylrhodamine ethyl ester-negative cells, cellular ATP levels, cell cycle perturbation, and shift in γ-H2AX fluorescence relative to solvent control. Logistic regression was used to identify endpoints that effectively predict chemicals' a priori classification. Cross validation using a leave-one-out approach indicated that a promising base model includes γ-H2AX shift and change in phospho-histone H3-positive events (25/30 correct calls). Improvements were realized when one or two additional endpoints were included (26-30/30 correct calls). These models were further evaluated with a test set of 10 chemicals, and also by evaluating 3 chemicals at a collaborating laboratory. The resulting data support the hypothesis that a matrix of high throughput-compatible biomarkers can effectively delineate two important modes of genotoxic action as well as identify cytotoxicity that can lead to irrelevant positive results.