Genomic dose response: Successes, challenges, and next steps

Schena, 1995, Quantitative monitoring of gene expression patterns with a complementary DNA microarray, Science, 270, 467, 10.1126/science.270.5235.467 Nuwaysir, 1999, Microarrays and toxicology: the advent of toxicogenomics, Mol Carcinog, 24, 153, 10.1002/(SICI)1098-2744(199903)24:3<153::AID-MC1>3.0.CO;2-P Cui, 2010, Use of transcriptomics in understanding mechanisms of drug-induced toxicity, Pharmacogenomics, 11, 573, 10.2217/pgs.10.37 Wang, 2014, The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance, Nat Biotechnol, 32, 926, 10.1038/nbt.3001 Hamadeh, 2002, Prediction of compound signature using high density gene expression profiling, Toxicol Sci, 67, 232, 10.1093/toxsci/67.2.232 Natsoulis, 2008, The liver pharmacological and xenobiotic gene response repertoire, Mol Syst Biol, 4, 175, 10.1038/msb.2008.9 Ganter, 2005, Development of a large-scale chemogenomics database to improve drug candidate selection and to understand mechanisms of chemical toxicity and action, J Biotechnol, 119, 219, 10.1016/j.jbiotec.2005.03.022 Uehara, 2010, The Japanese toxicogenomics project: application of toxicogenomics, Mol Nutr Food Res, 54, 218, 10.1002/mnfr.200900169 Suter, 2011, EU framework 6 project: predictive toxicology (PredTox)--overview and outcome, Toxicol Appl Pharmacol, 252, 73, 10.1016/j.taap.2010.10.008 Lamb, 2006, The connectivity map: using gene-expression signatures to connect small molecules, genes, and disease, Science, 313, 1929, 10.1126/science.1132939 Barel, 2018, Network and pathway analysis of toxicogenomics data, Front Genet, 9, 484, 10.3389/fgene.2018.00484 Waters, 2011, Characterizing and predicting carcinogenicity and mode of action using conventional and toxicogenomics methods, Mutat Res Rev Mutat Res, 705, 184, 10.1016/j.mrrev.2010.04.005 Lobenhofer, 2004, Exploration of low-dose estrogen effects: identification of no observed transcriptional effect level (NOTEL), Toxicol Pathol, 32, 482, 10.1080/01926230490483324 Burgoon, 2008, Automated quantitative dose-response modeling and point of departure determination for large toxicogenomic and high-throughput screening data sets, Toxicol Sci, 104, 412, 10.1093/toxsci/kfn083 Yu, 2006, A system-based approach to interpret dose- and time-dependent microarray data: quantitative integration of gene ontology analysis for risk assessment, Toxicol Sci:Off J Soc Toxicol, 92, 560, 10.1093/toxsci/kfj184 Thomas, 2007, A method to integrate benchmark dose estimates with genomic data to assess the functional effects of chemical exposure, Toxicol Sci:Off J Soc Toxicol, 98, 240, 10.1093/toxsci/kfm092 Boorman, 2002, Toxicogenomics, drug discovery, and the pathologist, Toxicol Pathol, 30, 15, 10.1080/01926230252824671 Yang, 2007, BMDExpress: a software tool for the benchmark dose analyses of genomic data, BMC Genomics, 8, 10.1186/1471-2164-8-387 Hall, 2012, Liver hypertrophy: a review of adaptive (adverse and non-adverse) changes--conclusions from the 3rd international ESTP expert workshop, Toxicol Pathol, 40, 971, 10.1177/0192623312448935 Sipes, 2017, An intuitive approach for predicting potential human health risk with the Tox21 10k library, Environ Sci Technol, 51, 10786, 10.1021/acs.est.7b00650 Brown, 1999, Exploring the new world of the genome with DNA microarrays, Nat Genet, 21, 33, 10.1038/4462 Denny, 2017, Chapter 5 - acute, subacute, subchronic, and chronic general toxicity testing for preclinical drug development, 109 Thomas, 2013, Incorporating new technologies into toxicity testing and risk assessment: moving from 21st century vision to a data-driven framework, Toxicol Sci:Off J Soc Toxicol, 136, 4, 10.1093/toxsci/kft178 Thomas, 2011, Application of transcriptional benchmark dose values in quantitative cancer and noncancer risk assessment, Toxicol Sci:Off J Soc Toxicol, 120, 194, 10.1093/toxsci/kfq355 Thomas, 2012, Integrating pathway-based transcriptomic data into quantitative chemical risk assessment: a five chemical case study, Mutat Res Genet Toxicol Environ Mutagen, 746, 135, 10.1016/j.mrgentox.2012.01.007 Thomas, 2013, Cross-species transcriptomic analysis of mouse and rat lung exposed to chloroprene, Toxicol Sci, 131, 629, 10.1093/toxsci/kfs314 Thomas, 2013, Temporal concordance between apical and transcriptional points of departure for chemical risk assessment, Toxicol Sci, 134, 180, 10.1093/toxsci/kft094 Phillips, 2018, BMDExpress 2: enhanced transcriptomic dose-response analysis workflow, Bioinformatics NTP, 2018 Andersen, 2008, Genomic signatures and dose-dependent transitions in nasal epithelial responses to inhaled formaldehyde in the rat, Toxicol Sci, 105, 368, 10.1093/toxsci/kfn097 Bhat, 2013, Concordance of transcriptional and apical benchmark dose levels for conazole-induced liver effects in mice, Toxicol Sci, 136, 205, 10.1093/toxsci/kft182 Chauhan, 2016, Transcriptional benchmark dose modeling: exploring how advances in chemical risk assessment may be applied to the radiation field, Environ Mol Mutagen, 57, 589, 10.1002/em.22043 Clewell, 2014, Transcriptional responses in the rat nasal epithelium following subchronic inhalation of naphthalene vapor, Toxicol Appl Pharmacol, 280, 78, 10.1016/j.taap.2014.06.015 Clewell, 2011, Concentration- and time-dependent genomic changes in the mouse urinary bladder following exposure to arsenate in drinking water for up to 12 weeks, Toxicol Sci, 123, 421, 10.1093/toxsci/kfr199 Dunnick, 2017, Hepatic transcriptomic alterations for N,N-dimethyl-p-toluidine (DMPT) and p-toluidine after 5-day exposure in rats, Arch Toxicol, 91, 1685, 10.1007/s00204-016-1831-7 Efremenko, 2014, Time- and concentration-dependent genomic responses of the rat airway to inhaled nickel subsulfide, Toxicol Appl Pharmacol, 279, 441, 10.1016/j.taap.2014.06.007 Hester, 2016, Dose-response analysis of RNA-seq profiles in archival formalin-fixed paraffin-embedded samples, Toxicol Sci, 154, 202, 10.1093/toxsci/kfw161 Jackson, 2014, Case study on the utility of hepatic global gene expression profiling in the risk assessment of the carcinogen furan, Toxicol Appl Pharmacol, 274, 63, 10.1016/j.taap.2013.10.019 Malik, 2013, Hepatic genotoxicity and toxicogenomic responses in MutaMouse males treated with dibenz a,h anthracene, Mutagenesis, 28, 543, 10.1093/mutage/get031 Moffat, 2015, Comparison of toxicogenomics and traditional approaches to inform mode of action and points of departure in human health risk assessment of benzo a pyrene in drinking water, Crit Rev Toxicol, 45, 1, 10.3109/10408444.2014.973934 Thomas, 2012, Integrating pathway-based transcriptomic data into quantitative chemical risk assessment: a five chemical case study, Mutat Res, 746, 135, 10.1016/j.mrgentox.2012.01.007 Thomas, 2013, Cross-species transcriptomic analysis of mouse and rat lung exposed to chloroprene, Toxicol Sci:Off J Soc Toxicol, 131, 629, 10.1093/toxsci/kfs314 Thomas, 2013, Temporal concordance between apical and transcriptional points of departure for chemical risk assessment, Toxicol Sci:Off J Soc Toxicol, 134, 180, 10.1093/toxsci/kft094 Thompson, 2016, Transcriptomic responses in the oral cavity of F344 rats and B6C3F1 mice following exposure to Cr(VI): implications for risk assessment, Environ Mol Mutagen, 57, 706, 10.1002/em.22064 Kopec, 2010, Automated dose-response analysis and comparative toxicogenomic evaluation of the hepatic effects elicited by TCDD, TCDF, and PCB126 in C57BL/6 mice, Toxicol Sci:Off J Soc Toxicol, 118, 286, 10.1093/toxsci/kfq236 Auerbach, 2016, 113 Farmahin, 2017, Recommended approaches in the application of toxicogenomics to derive points of departure for chemical risk assessment, Arch Toxicol, 91, 2045, 10.1007/s00204-016-1886-5 Auerbach, 2010, Predicting the hepatocarcinogenic potential of alkenylbenzene flavoring agents using toxicogenomics and machine learning, Toxicol Appl Pharmacol, 243, 300, 10.1016/j.taap.2009.11.021 National Toxicology Program, 2016 Hester, 2015, Developing toxicogenomics as a research tool by applying benchmark dose-response modelling to inform chemical mode of action and tumorigenic potency, Int J Biotechnol, 14, 28, 10.1504/IJBT.2015.074796 Ellinger-Ziegelbauer, 2008, Prediction of a carcinogenic potential of rat hepatocarcinogens using toxicogenomics analysis of short-term in vivo studies, Mutat Res, 637, 23, 10.1016/j.mrfmmm.2007.06.010 Fielden, 2007, A gene expression biomarker provides early prediction and mechanistic assessment of hepatic tumor induction by nongenotoxic chemicals, Toxicol Sci:Off J Soc Toxicol, 99, 90, 10.1093/toxsci/kfm156 Low, 2011, Predicting drug-induced hepatotoxicity using QSAR and toxicogenomics approaches, Chem Res Toxicol, 10.1021/tx200148a Uehara, 2011, Prediction model of potential hepatocarcinogenicity of rat hepatocarcinogens using a large-scale toxicogenomics database, Toxicol Appl Pharmacol, 255, 297, 10.1016/j.taap.2011.07.001 Eichner, 2013, A toxicogenomic approach for the prediction of murine hepatocarcinogenesis using ensemble feature selection, PLoS One, 8, 10.1371/journal.pone.0073938 Gusenleitner, 2014, Genomic models of short-term exposure accurately predict long-term chemical carcinogenicity and identify putative mechanisms of action, PLoS One, 9, 10.1371/journal.pone.0102579 Wu, 2018, Machine learning based toxicity prediction: from chemical structural description to transcriptome analysis, Int J Mol Sci, 19, 10.3390/ijms19082358 Smalley, 2010, Application of connectivity mapping in predictive toxicology based on gene-expression similarity, Toxicology, 268, 143, 10.1016/j.tox.2009.09.014 Low, 2013, Integrative chemical-biological read-across approach for chemical hazard classification, Chem Res Toxicol, 26, 1199, 10.1021/tx400110f Jones, 2016, Looking to the future of organ-on-chip and toxicity assessment: a regulator's opinion, Future Sci OA, 2, FSO153, 10.4155/fsoa-2016-0068 Lamb, 2007, The connectivity map: a new tool for biomedical research, Nat Rev Canc, 7, 54, 10.1038/nrc2044 Santos, 2017, A comprehensive map of molecular drug targets, Nat Rev Drug Discov, 16, 19, 10.1038/nrd.2016.230 Hur, 2018, Tox21 enricher: web-based chemical/biological functional annotation analysis tool based on Tox21 toxicity screening platform, Mol Inform, 37, 10.1002/minf.201700129 Zhang, 2018, Bridging the data gap from in vitro toxicity testing to chemical safety assessment through computational modeling, Front Public Health, 6, 261, 10.3389/fpubh.2018.00261 Bourdon-Lacombe, 2015, Technical guide for applications of gene expression profiling in human health risk assessment of environmental chemicals, Regul Toxicol Pharmacol : RTP (Regul Toxicol Pharmacol), 72, 292, 10.1016/j.yrtph.2015.04.010