Identifying Compounds with Genotoxicity Potential Using Tox21 High-Throughput Screening Assays.

Genotoxicity is a critical component of a comprehensive toxicological profile. The Tox21 Program used five quantitative high-throughput screening (qHTS) assays measuring some aspect of DNA damage/repair to provide information on the genotoxic potential of over 10 000 compounds. Included were assays detecting activation of p53, increases in the DNA repair protein ATAD5, phosphorylation of H2AX, and enhanced cytotoxicity in DT40 cells deficient in DNA-repair proteins REV3 or KU70/RAD54. Each assay measures a distinct component of the DNA damage response signaling network; >70% of active compounds were detected in only one of the five assays. When qHTS results were compared with results from three standard genotoxicity assays (bacterial mutation, in vitro chromosomal aberration, and in vivo micronucleus), a maximum of 40% of known, direct-acting genotoxicants were active in one or more of the qHTS genotoxicity assays, indicating low sensitivity. This suggests that these qHTS assays cannot in their current form be used to replace traditional genotoxicity assays. However, despite the low sensitivity, ranking chemicals by potency of response in the qHTS assays revealed an enrichment for genotoxicants up to 12-fold compared with random selection, when allowing a 1% false positive rate. This finding indicates these qHTS assays can be used to prioritize chemicals for further investigation, allowing resources to focus on compounds most likely to induce genotoxic effects. To refine this prioritization process, models for predicting the genotoxicity potential of chemicals that were active in Tox21 genotoxicity assays were constructed using all Tox21 assay data, yielding a prediction accuracy up to 0.83. Data from qHTS assays related to stress-response pathway signaling (including genotoxicity) were the most informative for model construction. By using the results from qHTS genotoxicity assays, predictions from models based on qHTS data, and predictions from commercial bacterial mutagenicity QSAR models, we prioritized Tox21 chemicals for genotoxicity characterization.

[1]  Chao Wei,et al.  Effects of double-strand break repair proteins on vertebrate telomere structure , 2002, Nucleic Acids Res..

[2]  Richard S Judson,et al.  On selecting a minimal set of in vitro assays to reliably determine estrogen agonist activity , 2017, Regulatory toxicology and pharmacology : RTP.

[3]  A. Dutra,et al.  DNA damage responses by human ELG1 in S phase are important to maintain genomic integrity , 2009, Cell cycle.

[4]  Ruili Huang,et al.  The Tox21 robotic platform for the assessment of environmental chemicals--from vision to reality. , 2013, Drug discovery today.

[5]  Hao Zhu,et al.  Profiling Animal Toxicants by Automatically Mining Public Bioassay Data: A Big Data Approach for Computational Toxicology , 2014, PloS one.

[6]  Raffaella Corvi,et al.  Updated recommended lists of genotoxic and non-genotoxic chemicals for assessment of the performance of new or improved genotoxicity tests. , 2016, Mutation research. Genetic toxicology and environmental mutagenesis.

[7]  Jui-Hua Hsieh Accounting Artifacts in High-Throughput Toxicity Assays. , 2016, Methods in molecular biology.

[8]  A. Hirner,et al.  The cyto- and genotoxicity of organotin compounds is dependent on the cellular uptake capability. , 2007, Toxicology.

[9]  D. Zalko,et al.  Assessment of a panel of cellular biomarkers and the kinetics of their induction in comparing genotoxic modes of action in HepG2 cells , 2018, Environmental and molecular mutagenesis.

[10]  I. Rusyn,et al.  Use of in Vitro HTS-Derived Concentration–Response Data as Biological Descriptors Improves the Accuracy of QSAR Models of in Vivo Toxicity , 2010, Environmental health perspectives.

[11]  Ruili Huang,et al.  Mechanism Profiling of Hepatotoxicity Caused by Oxidative Stress Using Antioxidant Response Element Reporter Gene Assay Models and Big Data , 2015, Environmental health perspectives.

[12]  B. Ames,et al.  Detection of carcinogens as mutagens in the Salmonella/microsome test: assay of 300 chemicals. , 1975, Proceedings of the National Academy of Sciences of the United States of America.

[13]  Ajay N. Jain,et al.  Recommendations for evaluation of computational methods , 2008, J. Comput. Aided Mol. Des..

[14]  Alessandro Giuliani,et al.  Improvement of quantitative structure–activity relationship (QSAR) tools for predicting Ames mutagenicity: outcomes of the Ames/QSAR International Challenge Project , 2018, Mutagenesis.

[15]  Ruili Huang,et al.  Identification of genotoxic compounds using isogenic DNA repair deficient DT40 cell lines on a quantitative high throughput screening platform. , 2015, Mutagenesis.

[16]  Robert J Kavlock,et al.  Toxicity Testing in the 21st Century: Implications for Human Health Risk Assessment , 2009, Risk analysis : an official publication of the Society for Risk Analysis.

[17]  David M. Reif,et al.  Endocrine Profiling and Prioritization of Environmental Chemicals Using ToxCast Data , 2010, Environmental health perspectives.

[18]  W. Alkema,et al.  BioVenn – a web application for the comparison and visualization of biological lists using area-proportional Venn diagrams , 2008, BMC Genomics.

[19]  S. Glaberman,et al.  Application of the CometChip platform to assess DNA damage in field‐collected blood samples from turtles , 2018, Environmental and molecular mutagenesis.

[20]  A. Tolcher,et al.  A Phase I Dose-Escalation Study of SR271425, an Intravenously Dosed Thioxanthone Analog, Administered Weekly in Patients With Refractory Solid Tumors , 2009, American journal of clinical oncology.

[21]  Ruili Huang,et al.  Assessment of the DNA damaging potential of environmental chemicals using a quantitative high‐throughput screening approach to measure p53 activation , 2017, Environmental and molecular mutagenesis.

[22]  Ruili Huang,et al.  Characterization of environmental chemicals with potential for DNA damage using isogenic DNA repair‐deficient chicken DT40 cell lines , 2011, Environmental and molecular mutagenesis.

[23]  M D Shelby,et al.  Micronucleated erythrocyte frequency in peripheral blood of B6C3F1 mice from short‐term, prechronic, and chronic studies of the NTP carcinogenesis bioassay program , 2000, Environmental and molecular mutagenesis.

[24]  Andrew Williams,et al.  Using a gene expression biomarker to identify DNA damage‐inducing agents in microarray profiles , 2018, Environmental and molecular mutagenesis.

[25]  Xavier Robin,et al.  pROC: an open-source package for R and S+ to analyze and compare ROC curves , 2011, BMC Bioinformatics.

[26]  Yuhong Wang,et al.  Correction of Microplate Data from High-Throughput Screening. , 2016, Methods in molecular biology.

[27]  H. Saya,et al.  Multiple Roles of Vertebrate REV Genes in DNA Repair and Recombination , 2005, Molecular and Cellular Biology.

[28]  Trevor Hastie,et al.  Regularization Paths for Generalized Linear Models via Coordinate Descent. , 2010, Journal of statistical software.

[29]  H. Zou,et al.  Regularization and variable selection via the elastic net , 2005 .

[30]  Stephen D Dertinger,et al.  Investigating the Generalizability of the MultiFlow ® DNA Damage Assay and Several Companion Machine Learning Models With a Set of 103 Diverse Test Chemicals , 2018, Toxicological sciences : an official journal of the Society of Toxicology.

[31]  M. Berchtold,et al.  The chicken B cell line DT40: a novel tool for gene disruption experiments. , 2001, Journal of immunological methods.

[32]  Alexander Sedykh CurveP Method for Rendering High-Throughput Screening Dose-Response Data into Digital Fingerprints. , 2016, Methods in molecular biology.

[33]  J. M. Mason,et al.  Chemical mutagenesis testing in Drosophila. X. Results of 70 coded chemicals tested for the national toxicology‐program , 1994, Environmental and molecular mutagenesis.

[34]  David M. Reif,et al.  Profiling of the Tox21 10K compound library for agonists and antagonists of the estrogen receptor alpha signaling pathway , 2014, Scientific Reports.

[35]  O. Ozdemir,et al.  Genotoxicity testing: progress and prospects for the next decade , 2017, Expert opinion on drug metabolism & toxicology.

[36]  Ruili Huang,et al.  High-throughput genotoxicity assay identifies antioxidants as inducers of DNA damage response and cell death , 2012, Proceedings of the National Academy of Sciences.

[37]  J. M. Mason,et al.  Chemical mutagenesis testing in Drosophila. IX. Results of 50 coded compounds tested for the National Toxicology Program. , 1994, Environmental and molecular mutagenesis.

[38]  I. Kawamura,et al.  FK317: a novel substituted dihydrobenzoxazine with potent antitumor activity which does not induce vascular leak syndrome , 1998, Cancer Chemotherapy and Pharmacology.

[39]  Alexander Lex,et al.  UpSetR: an R package for the visualization of intersecting sets and their properties , 2017, bioRxiv.

[40]  J. Corton,et al.  Identification of p53 Activators in a Human Microarray Compendium. , 2019, Chemical research in toxicology.

[41]  Ruili Huang,et al.  A Data Analysis Pipeline Accounting for Artifacts in Tox21 Quantitative High-Throughput Screening Assays , 2015, Journal of biomolecular screening.