OpenTox 2022 Virtual Conference
Application of the ToxTracker assay to investigate the mode-of-action of genotoxic compounds.
ToxTracker is a mammalian stem cell-based reporter assay that detects activation of specific cellular signaling pathways upon chemical exposure. ToxTracker contains six different GFP-tagged reporter cell lines that together allow the accurate identification of genotoxic substances and discrimination between induction of DNA damage, oxidative stress and/or protein damage in a single test. Various extensions of the assay were developed to allow the discrimination between clastogenic and aneugenic compounds and to assess indirect genotoxicity caused by high levels of oxidative stress. The specificity of the ToxTracker reporter cell lines was extensively validated using different libraries of reference compounds. Over 95% of all tested chemicals were classified correctly, confirming the outstanding performance of the assay. Importantly, compounds that are often erroneously identified as genotoxic compounds by the conventional in vitro genotoxicity tests were identified by the assay as causing predominantly oxidative stress, explaining their positive results.
The ToxTracker assay is currently being evaluated in a large international inter-laboratory validation study, approved by the OECD. The goal of this prospective validation study is to explore the applicability of ToxTracker for regulatory applications, establish the transferability and reproducibility of the assay and to explore how it can be applied to improve the in vitro genotoxicity testing strategies. The validation has been conducted strictly following OECD guidance document 34.
During the presentation, a number of case studies will be presented in which ToxTracker was used to investigate the mode-of-action of genotoxic substances. Also an update about the ongoing OECD validation of the assay will be presented.
The evaluation of genotoxicity by using novel prediction models based on biomarker genes in human HepaRGTM cells.
List of Authors:
Anouck Thienpont1, Stefaan Verhulst2, Leo A. van Grunsven2, Vera Rogiers1*, Tamara Vanhaecke1* and Birgit Mertens3*
1Department of In Vitro Toxicology and Dermato-Cosmetology, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussels, Belgium
2 Liver Cell Biology research group, Vrije Universiteit Brussel (VUB), Laarbeeklaan 103, 1090 Brussels, Belgium
3Department of Chemical and Physical Health Risks, Sciensano, Juliette Wytsmanstraat 14, 1050 Brussels, Belgium
*Equally contributing last authors
Transcriptomics-based biomarkers are promising new approach methodologies (NAMs) to detect molecular events underlying the genotoxic mode of action of chemicals. Previously, we developed the GENOMARK biomarker, consisting of 84 genes selected from whole genomics DNA microarray profiles of 24 (non-)genotoxic reference chemicals covering different modes of action in metabolically competent human HepaRG™ cells. The biomarker was combined with a prediction model to classify the compounds as genotoxic or non-genotoxic using the expression data for the 84 genes. Recently, we created two new prediction models based on supervised machine learning algorithms (i.e. support vector machine (SVM) and random forest (RF)) taking into account an extended reference dataset of 38 chemicals. The novel models demonstrated a high performance for predicting misleading positive compounds based on qPCR data and for known (non-)genotoxic compounds based on an existing gene expression dataset generated with RNA-Seq. In addition, we also investigated the quantitative application of the GENOMARK gene expression data. More specifically, the potencies of two known in vivo genotoxic chemicals, aflatoxin B1 (AFB1) and ethyl methanesulfonate (EMS), were compared by using the benchmark dose (BMD) modelling approach. Briefly, three different batches of HepaRGTM cells were exposed to AFB1 or EMS in a concentration range around the IC10 and gene expression data were collected with qPCR. Next, the covariate approach with a benchmark response of 10% was applied on the GENOMARK genes with a fold change higher than either 1.5 or 2. Quantitative BMD modelling confirmed that AFB1 is more potent than EMS in HepaRGTM cells. Currently, data for additional compounds are being generated with TempO-Seq to explore the applicability of GENOMARK for quantitative genotoxicity assessment of data generated with high-throughput sequencing approaches. The preliminary results of this study together with our previous data suggest that GENOMARK does not only allow hazard identification but also provides quantitative genotoxicity information highlighting its potential use for risk assessment.