Predictions of genotoxic potential, mode of action, molecular targets, and potency via a tiered multiflow® assay data analysis strategy

Abstract

The in vitro MultiFlow® DNA Damage Assay multiplexes γH2AX, p53, phospho-histone H3, and polyploidization biomarkers into a single flow cytometric analysis. The current report describes a tiered sequential data analysis strategy based on data generated from exposure of human TK6 cells to a previously described 85 chemical training set and a new pharmaceutical-centric test set (n = 40). In each case, exposure was continuous over a range of closely spaced concentrations, and cell aliquots were removed for analysis following 4 and 24 hr of treatment. The first data analysis step focused on chemicals’ genotoxic potential, and for this purpose, we evaluated the performance of a machine learning (ML) ensemble, a rubric that considered fold increases in biomarkers against global evaluation factors (GEFs), and a hybrid strategy that considered ML and GEFs. This first tier further used ML output and/or GEFs to classify genotoxic activity as clastogenic and/or aneugenic. Test set results demonstrated the generalizability of the first tier, with particularly good performance from the ML ensemble: 35/40 (88%) concordance with a priori genotoxicity expectations and 21/24 (88%) agreement with expected mode of action (MoA). A second tier applied unsupervised hierarchical clustering to the biomarker response data, and these analyses were found to group certain chemicals, especially aneugens, according to their molecular targets. Finally, a third tier utilized benchmark dose analyses and MultiFlow biomarker responses to rank genotoxic potency. The relevance of these rankings is supported by the strong agreement found between benchmark dose values derived from MultiFlow biomarkers compared to those generated from parallel in vitro micronucleus analyses. Collectively, the results suggest that a tiered MultiFlow data analysis pipeline is capable of rapidly and effectively identifying genotoxic hazards while providing additional information that is useful for modern risk assessments—MoA, molecular targets, and potency.

Evidence for an Aneugenic Mechanism of Action for Micronucleus Induction by Black Cohosh Extract

“…“Compound” was selected as the covariate, and the resulting 95% confidence intervals (CIs) were used to represent the relative potency of the compounds. These methods were the same as those described previously (Dertinger et al ), with the exception that the analyses described herein utilized RIVM PROAST Web software v65.2 (https://proastweb.rivm.nl; accessed June 27, 2019).…”

“…Data analyses were restricted to the lowest precipitating concentration, and those that did not exceed the assay's cytotoxicity limit. Specifically, the top concentration of each chemical had to exhibit ≤80% reduction to RNC at the 24 h time point, and a maximum of two concentrations within the cytotoxicity range 70%–80% were permitted (Dertinger et al ). Based on these criteria, the top analyzable concentrations were 250 and 500 μg/mL for NTP BCE and BC XRM, respectively.…”

“…As described previously, genotoxic potential and genotoxic MoA (ie, clastogen vs. aneugen) predictions were made in two manners: comparing fold‐increase values against a global evaluation factor (GEF) rubric, and via an ML ensemble (Dertinger et al ). An overall genotoxic call was made when either the GEF rubric or ML ensemble provided evidence of genotoxicity.…”

“…Unsupervised clustering was performed for test articles predicted to have aneugenic activity by the MultiFlow DNA Damage Assay. As described previously, aneugens group broadly into two subclasses: tubulin binders vs. mitotic kinase inhibitors (Dertinger et al ). The clustering analysis was performed with JMP software (v12.0.1) and utilized area‐under‐the‐curve (AUC) values based on the following four biomarkers: 4 h p‐H3, and 24 h p‐H3, p53, and polyploidy.…”

“…The biomarker responses include phosphorylation of H2AX (γH2AX), translocation of p53 to the nucleus, phosphorylation of histone H3 at serine 10 (p‐H3), and induction of polyploidy. Together with information on cytotoxicity at 24 h, the machine‐learning algorithms translate the collection of MultiFlow responses into predictions about predominant MoA—clastogenic, aneugenic, or non‐genotoxic (Bryce et al ; Bryce et al ; Bryce et al ; Dertinger et al ). The NTP BCE and BC XRM samples were characterized by the MultiFlow assay as having aneugenic activity (Smith‐Roe et al ).…”