toxicogenetics

Summary

Summary: The study of existing genetic knowledge, and the generation of new genetic data, to understand and thus avoid DRUG TOXICITY and adverse effects from toxic substances from the environment.

Top Publications

  1. Cheng F, Theodorescu D, Schulman I, Lee J. In vitro transcriptomic prediction of hepatotoxicity for early drug discovery. J Theor Biol. 2011;290:27-36 pubmed publisher
  2. Davis A, King B, Mockus S, Murphy C, Saraceni Richards C, Rosenstein M, et al. The Comparative Toxicogenomics Database: update 2011. Nucleic Acids Res. 2011;39:D1067-72 pubmed publisher
    ..Together, this wealth of expanded chemical-gene-disease data continues to help users generate testable hypotheses about the molecular mechanisms of environmental diseases. CTD is freely available at http://ctd.mdibl.org. ..
  3. King B, Davis A, Rosenstein M, Wiegers T, Mattingly C. Ranking transitive chemical-disease inferences using local network topology in the comparative toxicogenomics database. PLoS ONE. 2012;7:e46524 pubmed publisher
    ..We present several CTD inferences as case studies to demonstrate the value of this metric and the biological relevance of the inferences. ..
  4. Beekman J, Boess F, Hildebrand H, Kalkuhl A, Suter L. Gene expression analysis of the hepatotoxicant methapyrilene in primary rat hepatocytes: an interlaboratory study. Environ Health Perspect. 2006;114:92-9 pubmed
    ..The identified genes are involved in cellular processes that are associated to the exposure of primary hepatocytes to MP. Whether they are specific for MP and are cause or consequence of the toxicity requires further investigations...
  5. Xirasagar S, Gustafson S, Huang C, Pan Q, Fostel J, Boyer P, et al. Chemical effects in biological systems (CEBS) object model for toxicology data, SysTox-OM: design and application. Bioinformatics. 2006;22:874-82 pubmed
    ..gov/cebsdownloads. Currently, the public toxicological data in CEBS can be queried via a web application based on the SysTox-OM at http://cebs.niehs.nih.gov xirasagars@saic.com Supplementary data are available at Bioinformatics online. ..
  6. Lema C, Cunningham M. MicroRNAs and their implications in toxicological research. Toxicol Lett. 2010;198:100-5 pubmed publisher
    ..The implications of miRNAs in toxicogenomics as well as the new avenues of research of miRNAs in toxicology are discussed. ..
  7. Mattingly C, Rosenstein M, Colby G, Forrest J, Boyer J. The Comparative Toxicogenomics Database (CTD): a resource for comparative toxicological studies. J Exp Zool A Comp Exp Biol. 2006;305:689-92 pubmed
    ..Similarly, these approaches will be valuable for exploring the molecular mechanisms of action of environmental chemicals and the genetic basis of differential susceptibility. ..
  8. Van Aggelen G, Ankley G, Baldwin W, Bearden D, Benson W, Chipman J, et al. Integrating omic technologies into aquatic ecological risk assessment and environmental monitoring: hurdles, achievements, and future outlook. Environ Health Perspect. 2010;118:1-5 pubmed publisher
  9. Afshari C, Hamadeh H, Bushel P. The evolution of bioinformatics in toxicology: advancing toxicogenomics. Toxicol Sci. 2011;120 Suppl 1:S225-37 pubmed publisher
    ..This review will cover the evolution of the field of toxicogenomics in the context of informatics integration its current promise, and limitations. ..
  10. Davis A, Murphy C, Saraceni Richards C, Rosenstein M, Wiegers T, Mattingly C. Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks. Nucleic Acids Res. 2009;37:D786-92 pubmed publisher
    ..This wealth of chemical-gene-disease information yields testable hypotheses for understanding the effects of environmental chemicals on human health. CTD is freely available at http://ctd.mdibl.org. ..

Detail Information

Publications62

  1. Cheng F, Theodorescu D, Schulman I, Lee J. In vitro transcriptomic prediction of hepatotoxicity for early drug discovery. J Theor Biol. 2011;290:27-36 pubmed publisher
  2. Davis A, King B, Mockus S, Murphy C, Saraceni Richards C, Rosenstein M, et al. The Comparative Toxicogenomics Database: update 2011. Nucleic Acids Res. 2011;39:D1067-72 pubmed publisher
    ..Together, this wealth of expanded chemical-gene-disease data continues to help users generate testable hypotheses about the molecular mechanisms of environmental diseases. CTD is freely available at http://ctd.mdibl.org. ..
  3. King B, Davis A, Rosenstein M, Wiegers T, Mattingly C. Ranking transitive chemical-disease inferences using local network topology in the comparative toxicogenomics database. PLoS ONE. 2012;7:e46524 pubmed publisher
    ..We present several CTD inferences as case studies to demonstrate the value of this metric and the biological relevance of the inferences. ..
  4. Beekman J, Boess F, Hildebrand H, Kalkuhl A, Suter L. Gene expression analysis of the hepatotoxicant methapyrilene in primary rat hepatocytes: an interlaboratory study. Environ Health Perspect. 2006;114:92-9 pubmed
    ..The identified genes are involved in cellular processes that are associated to the exposure of primary hepatocytes to MP. Whether they are specific for MP and are cause or consequence of the toxicity requires further investigations...
  5. Xirasagar S, Gustafson S, Huang C, Pan Q, Fostel J, Boyer P, et al. Chemical effects in biological systems (CEBS) object model for toxicology data, SysTox-OM: design and application. Bioinformatics. 2006;22:874-82 pubmed
    ..gov/cebsdownloads. Currently, the public toxicological data in CEBS can be queried via a web application based on the SysTox-OM at http://cebs.niehs.nih.gov xirasagars@saic.com Supplementary data are available at Bioinformatics online. ..
  6. Lema C, Cunningham M. MicroRNAs and their implications in toxicological research. Toxicol Lett. 2010;198:100-5 pubmed publisher
    ..The implications of miRNAs in toxicogenomics as well as the new avenues of research of miRNAs in toxicology are discussed. ..
  7. Mattingly C, Rosenstein M, Colby G, Forrest J, Boyer J. The Comparative Toxicogenomics Database (CTD): a resource for comparative toxicological studies. J Exp Zool A Comp Exp Biol. 2006;305:689-92 pubmed
    ..Similarly, these approaches will be valuable for exploring the molecular mechanisms of action of environmental chemicals and the genetic basis of differential susceptibility. ..
  8. Van Aggelen G, Ankley G, Baldwin W, Bearden D, Benson W, Chipman J, et al. Integrating omic technologies into aquatic ecological risk assessment and environmental monitoring: hurdles, achievements, and future outlook. Environ Health Perspect. 2010;118:1-5 pubmed publisher
  9. Afshari C, Hamadeh H, Bushel P. The evolution of bioinformatics in toxicology: advancing toxicogenomics. Toxicol Sci. 2011;120 Suppl 1:S225-37 pubmed publisher
    ..This review will cover the evolution of the field of toxicogenomics in the context of informatics integration its current promise, and limitations. ..
  10. Davis A, Murphy C, Saraceni Richards C, Rosenstein M, Wiegers T, Mattingly C. Comparative Toxicogenomics Database: a knowledgebase and discovery tool for chemical-gene-disease networks. Nucleic Acids Res. 2009;37:D786-92 pubmed publisher
    ..This wealth of chemical-gene-disease information yields testable hypotheses for understanding the effects of environmental chemicals on human health. CTD is freely available at http://ctd.mdibl.org. ..
  11. Boverhof D, Burgoon L, Tashiro C, Sharratt B, Chittim B, Harkema J, et al. Comparative toxicogenomic analysis of the hepatotoxic effects of TCDD in Sprague Dawley rats and C57BL/6 mice. Toxicol Sci. 2006;94:398-416 pubmed
  12. Boverhof D, Zacharewski T. Toxicogenomics in risk assessment: applications and needs. Toxicol Sci. 2006;89:352-60 pubmed
  13. Fostel J, Choi D, Zwickl C, Morrison N, Rashid A, Hasan A, et al. Chemical effects in biological systems--data dictionary (CEBS-DD): a compendium of terms for the capture and integration of biological study design description, conventional phenotypes, and 'omics data. Toxicol Sci. 2005;88:585-601 pubmed
    ..N. Heinloth et al., 2004, Toxicol. Sci. 80, 193-202). ..
  14. Andrade R, Agundez J, Lucena M, Martinez C, Cueto R, Garcia Martin E. Pharmacogenomics in drug induced liver injury. Curr Drug Metab. 2009;10:956-70 pubmed
    ..We identify potential sources of heterogeneity in studies carried out so far as well as new genetic targets which require further investigation. ..
  15. Wiegers T, Davis A, Cohen K, Hirschman L, Mattingly C. Text mining and manual curation of chemical-gene-disease networks for the comparative toxicogenomics database (CTD). BMC Bioinformatics. 2009;10:326 pubmed publisher
    ..Our study presents a feasible and cost-effective approach for developing a text mining solution to enhance manual curation throughput and efficiency. ..
  16. Davis A, Murphy C, Johnson R, Lay J, Lennon Hopkins K, Saraceni Richards C, et al. The Comparative Toxicogenomics Database: update 2013. Nucleic Acids Res. 2013;41:D1104-14 pubmed publisher
    ..Together, this wealth of expanded chemical-gene-disease data, combined with novel ways to analyze and view content, continues to help users generate testable hypotheses about the molecular mechanisms of environmental diseases. ..
  17. Davis A, Wiegers T, Johnson R, Lay J, Lennon Hopkins K, Saraceni Richards C, et al. Text mining effectively scores and ranks the literature for improving chemical-gene-disease curation at the comparative toxicogenomics database. PLoS ONE. 2013;8:e58201 pubmed publisher
    ..Here, we demonstrate how fully incorporating text mining-based DRS scoring into our curation pipeline enhances manual curation by prioritizing more relevant articles, thereby increasing data content, productivity, and efficiency...
  18. Lobenhofer E, Auman J, Blackshear P, Boorman G, Bushel P, Cunningham M, et al. Gene expression response in target organ and whole blood varies as a function of target organ injury phenotype. Genome Biol. 2008;9:R100 pubmed publisher
    ..The results of the study demonstrate the classification of histopathological differences, likely reflecting differences in mechanisms of cell-specific toxicity, using either liver tissue or blood transcriptomic data. ..
  19. McHale C, Zhang L, Hubbard A, Smith M. Toxicogenomic profiling of chemically exposed humans in risk assessment. Mutat Res. 2010;705:172-83 pubmed publisher
  20. Waters M, Stasiewicz S, Merrick B, Tomer K, Bushel P, Paules R, et al. CEBS--Chemical Effects in Biological Systems: a public data repository integrating study design and toxicity data with microarray and proteomics data. Nucleic Acids Res. 2008;36:D892-900 pubmed
    ..niehs.nih.gov. BID can be accessed via the user interface from https://dir-apps.niehs.nih.gov/arc/. Requests for a copy of BID and for depositing data into CEBS or BID are available at http://www.niehs.nih.gov/cebs-df/. ..
  21. Moggs J. Molecular responses to xenoestrogens: mechanistic insights from toxicogenomics. Toxicology. 2005;213:177-93 pubmed
    ..This review illustrates how these toxicogenomic approaches are providing an unprecedented amount of mechanistic information on the molecular responses to xenoestrogens and how they are likely to impact on hazard and risk assessment. ..
  22. Lobenhofer E, Boorman G, Phillips K, Heinloth A, Malarkey D, Blackshear P, et al. Application of visualization tools to the analysis of histopathological data enhances biological insight and interpretation. Toxicol Pathol. 2006;34:921-8 pubmed
  23. Guo L, Lobenhofer E, Wang C, Shippy R, Harris S, Zhang L, et al. Rat toxicogenomic study reveals analytical consistency across microarray platforms. Nat Biotechnol. 2006;24:1162-9 pubmed
  24. Lee S, Choi J, Park K, Song M, Lee D. Discovering context-specific relationships from biological literature by using multi-level context terms. BMC Med Inform Decis Mak. 2012;12 Suppl 1:S1 pubmed publisher
    ..By utilizing multi-level context terms, our model shows better performance than the previous ABC model. ..
  25. Vickers A, Fisher R. Precision-cut organ slices to investigate target organ injury. Expert Opin Drug Metab Toxicol. 2005;1:687-99 pubmed
  26. Foster W, Chen S, He A, Truong A, Bhaskaran V, Nelson D, et al. A retrospective analysis of toxicogenomics in the safety assessment of drug candidates. Toxicol Pathol. 2007;35:621-35 pubmed
  27. Zidek N, Hellmann J, Kramer P, Hewitt P. Acute hepatotoxicity: a predictive model based on focused illumina microarrays. Toxicol Sci. 2007;99:289-302 pubmed
    ..Two unknown test compounds were used for prevalidating the screening test system, with both being correctly predicted. We conclude that focused gene microarrays are sufficient to classify compounds with respect to toxicity prediction. ..
  28. Hudder A, Novak R. miRNAs: effectors of environmental influences on gene expression and disease. Toxicol Sci. 2008;103:228-40 pubmed publisher
    ..The role of miRNAs in signal transduction and cellular stress is reviewed. Lastly, we identify new exciting avenues of research on the role of miRNAs in toxicogenomics and the possibility of epigenetic effects on gene expression. ..
  29. Yauk C, Berndt M. Review of the literature examining the correlation among DNA microarray technologies. Environ Mol Mutagen. 2007;48:380-94 pubmed
    ..We suggest several key factors that should be controlled in comparing across technologies, and are good microarray practice in general. ..
  30. Uehara T, Hirode M, Ono A, Kiyosawa N, Omura K, Shimizu T, et al. A toxicogenomics approach for early assessment of potential non-genotoxic hepatocarcinogenicity of chemicals in rats. Toxicology. 2008;250:15-26 pubmed publisher
  31. Kopec A, Burgoon L, Ibrahim Aibo D, Mets B, Tashiro C, Potter D, et al. PCB153-elicited hepatic responses in the immature, ovariectomized C57BL/6 mice: comparative toxicogenomic effects of dioxin and non-dioxin-like ligands. Toxicol Appl Pharmacol. 2010;243:359-71 pubmed publisher
    ..Collectively, these results suggest that the hepatocellular effects elicited by PCB153 are qualitatively and quantitatively different from TCDD and suggestive of CAR/PXR regulation. ..
  32. Foley J, Collins J, Umbach D, Grissom S, Boorman G, Heinloth A. Optimal sampling of rat liver tissue for toxicogenomic studies. Toxicol Pathol. 2006;34:795-801 pubmed
    ..Additionally, a powdered sample provided the advantages of a homogenous sample pool and the ability to use sample aliquots for other analyses to include proteomics, metabonomics, and other molecular techniques. ..
  33. Thompson C, Gregory Hixon J, Proctor D, Haws L, Suh M, Urban J, et al. Assessment of genotoxic potential of Cr(VI) in the mouse duodenum: an in silico comparison with mutagenic and nonmutagenic carcinogens across tissues. Regul Toxicol Pharmacol. 2012;64:68-76 pubmed publisher
    ..These findings may be useful as part of a full weight of evidence MOA evaluation for Cr(VI)-induced intestinal carcinogenesis. Limitations to this analysis will also be discussed...
  34. Williams Devane C, Wolf M, Richard A. Toward a public toxicogenomics capability for supporting predictive toxicology: survey of current resources and chemical indexing of experiments in GEO and ArrayExpress. Toxicol Sci. 2009;109:358-71 pubmed publisher
    ..Chemical indexing of public genomics databases is a first important step toward integrating chemical, toxicological and genomics data into predictive toxicology. ..
  35. Mattingly C. Chemical databases for environmental health and clinical research. Toxicol Lett. 2009;186:62-5 pubmed publisher
  36. Guguen Guillouzo C, Guillouzo A. General review on in vitro hepatocyte models and their applications. Methods Mol Biol. 2010;640:1-40 pubmed publisher
    ..All models will benefit from new developments in throughput screening based on cell chips coupled with high-content imaging and in toxicogenomics technologies. ..
  37. Gómez Lechón M, Castell J, Donato M. The use of hepatocytes to investigate drug toxicity. Methods Mol Biol. 2010;640:389-415 pubmed publisher
    ..In this regard, cytomic, proteomic, toxicogenomic and metabonomic approaches help to define patterns of hepatotoxicity for early identification of potential adverse effects of the drug to the liver. ..
  38. Hrach J, Mueller S, Hewitt P. Development of an in vitro liver toxicity prediction model based on longer term primary rat hepatocyte culture. Toxicol Lett. 2011;206:189-96 pubmed publisher
  39. Corvi R, Ahr H, Albertini S, Blakey D, Clerici L, Coecke S, et al. Meeting report: Validation of toxicogenomics-based test systems: ECVAM-ICCVAM/NICEATM considerations for regulatory use. Environ Health Perspect. 2006;114:420-9 pubmed
    ..In this report we summarize the discussions and describe in detail the recommendations for future direction and priorities. ..
  40. Alestrom P, Holter J, Nourizadeh Lillabadi R. Zebrafish in functional genomics and aquatic biomedicine. Trends Biotechnol. 2006;24:15-21 pubmed
    ..As detailed in this review, the zebrafish is a versatile and well-characterized model with applications in many fields of study. ..
  41. Luhe A, Suter L, Ruepp S, Singer T, Weiser T, Albertini S. Toxicogenomics in the pharmaceutical industry: hollow promises or real benefit?. Mutat Res. 2005;575:102-15 pubmed
  42. N jai A, Boverhof D, Dere E, Burgoon L, Tan Y, Rowlands J, et al. Comparative temporal toxicogenomic analysis of TCDD- and TCDF-mediated hepatic effects in immature female C57BL/6 mice. Toxicol Sci. 2008;103:285-97 pubmed publisher
  43. Tarr P, Telenti A. Toxicogenetics of antiretroviral therapy: genetic factors that contribute to metabolic complications. Antivir Ther. 2007;12:999-1013 pubmed
    ..linked to the genetic background of patients, as regards efficacy and susceptibility to adverse reactions (toxicogenetics)...
  44. Halappanavar S, Jackson P, Williams A, Jensen K, Hougaard K, Vogel U, et al. Pulmonary response to surface-coated nanotitanium dioxide particles includes induction of acute phase response genes, inflammatory cascades, and changes in microRNAs: a toxicogenomic study. Environ Mol Mutagen. 2011;52:425-39 pubmed publisher
    ..The role of these miRNAs in pulmonary response to inhaled particles is unknown and warrants further research. ..
  45. Mattingly C, Rosenstein M, Davis A, Colby G, Forrest J, Boyer J. The comparative toxicogenomics database: a cross-species resource for building chemical-gene interaction networks. Toxicol Sci. 2006;92:587-95 pubmed
    ..Here we describe these new features and our novel cross-species curation of chemical-gene and chemical-protein interactions. ..
  46. Nie A, McMillian M, Parker J, Leone A, Bryant S, Yieh L, et al. Predictive toxicogenomics approaches reveal underlying molecular mechanisms of nongenotoxic carcinogenicity. Mol Carcinog. 2006;45:914-33 pubmed
    ..Predictive genes confirm prior work and suggest pathways critical for early stages of carcinogenesis. ..
  47. Davis A, Wiegers T, Rosenstein M, Murphy C, Mattingly C. The curation paradigm and application tool used for manual curation of the scientific literature at the Comparative Toxicogenomics Database. Database (Oxford). 2011;2011:bar034 pubmed publisher
    ..We have incorporated this strategy into a web-based curation tool to further increase efficiency and productivity, implement quality control in real-time and accommodate biocurators working remotely. Database URL: http://ctd.mdibl.org. ..
  48. Ellinger Ziegelbauer H, Gmuender H, Bandenburg A, Ahr H. Prediction of a carcinogenic potential of rat hepatocarcinogens using toxicogenomics analysis of short-term in vivo studies. Mutat Res. 2008;637:23-39 pubmed
    ..We would like to present this study as proof of the concept that a classification of carcinogens based on short-term studies may be feasible. ..
  49. Takashima K, Mizukawa Y, Morishita K, Okuyama M, Kasahara T, Toritsuka N, et al. Effect of the difference in vehicles on gene expression in the rat liver--analysis of the control data in the Toxicogenomics Project Database. Life Sci. 2006;78:2787-96 pubmed
    ..These results would be useful for usage of the database especially when drugs with different vehicle control are compared. ..
  50. Choi J, Kim K, Song M, Lee D. Generation and application of drug indication inference models using typed network motif comparison analysis. BMC Med Inform Decis Mak. 2013;13 Suppl 1:S2 pubmed publisher
    ..By utilizing inference models from the topological patterns, we were able to improve inference power in drug indication inferences. ..
  51. Elferink M, Olinga P, van Leeuwen E, Bauerschmidt S, Polman J, Schoonen W, et al. Gene expression analysis of precision-cut human liver slices indicates stable expression of ADME-Tox related genes. Toxicol Appl Pharmacol. 2011;253:57-69 pubmed publisher
    ..These results indicate that precision-cut human liver slices are relatively stable during 24h of incubation and represent a valuable model for human in vitro hepatotoxicity testing despite the human inter-individual variability. ..
  52. Silkworth J, Carlson E, McCulloch C, Illouz K, Goodwin S, Sutter T. Toxicogenomic analysis of gender, chemical, and dose effects in livers of TCDD- or aroclor 1254-exposed rats using a multifactor linear model. Toxicol Sci. 2008;102:291-309 pubmed publisher
    ..This study extends the findings of previous rodent bioassays by identifying groups of genes, other than the well-characterized AHR response genes, whose disruption may be important in the tumorigenic mechanism in this rat strain. ..
  53. Fan X, Lobenhofer E, Chen M, Shi W, Huang J, Luo J, et al. Consistency of predictive signature genes and classifiers generated using different microarray platforms. Pharmacogenomics J. 2010;10:247-57 pubmed publisher
    ..The study reveals an opportunity for possible translation of biomarkers identified using microarrays to clinically validated non-array gene expression assays. ..
  54. Ghosh P, Banerjee M, Giri A, Ray K. Toxicogenomics of arsenic: classical ideas and recent advances. Mutat Res. 2008;659:293-301 pubmed publisher
    ..Our goal in this article has been to present the current state of research on this area to help formulate strategies for future studies. ..
  55. Schug M, Heise T, Bauer A, Storm D, Blaszkewicz M, Bedawy E, et al. Primary rat hepatocytes as in vitro system for gene expression studies: comparison of sandwich, Matrigel and 2D cultures. Arch Toxicol. 2008;82:923-31 pubmed publisher
    ..In conclusion, the presented data strongly suggest that sandwich cultures are most adequate for detection of MPy-induced gene expression alterations and the effect of MPy was detected at in vivo relevant concentrations...
  56. Mei N, Fuscoe J, Lobenhofer E, Guo L. Application of microarray-based analysis of gene expression in the field of toxicogenomics. Methods Mol Biol. 2010;597:227-41 pubmed publisher
  57. Phillips D, Arlt V. Genotoxicity: damage to DNA and its consequences. EXS. 2009;99:87-110 pubmed
    ..Characterisation of gene mutations in human tumours, in common with the known mutagenic profiles of genotoxins in experimental systems, may provide further insight into the role of environmental mutagens in human cancer. ..
  58. Ding Y, Song M, Han J, Yu Q, Yan E, Lin L, et al. Entitymetrics: measuring the impact of entities. PLoS ONE. 2013;8:e71416 pubmed publisher
    ..The comparison demonstrates the usefulness of entitymetrics to detect most of the outstanding interactions manually curated in CTD. ..
  59. Wu X, Song Y. Preferential regulation of miRNA targets by environmental chemicals in the human genome. BMC Genomics. 2011;12:244 pubmed publisher
    ..Our analyses indicated that miRNAs and their targets played important roles in cellular responses to ECs. Association analyses of miRNAs and ECs will help to broaden the understanding of the pathogenesis of such chemical components. ..
  60. Mahadevan B, Snyder R, Waters M, Benz R, Kemper R, Tice R, et al. Genetic toxicology in the 21st century: reflections and future directions. Environ Mol Mutagen. 2011;52:339-54 pubmed publisher
    ..Progress and challenges, including the pressing need to incorporate metabolic activation capability, are summarized. ..
  61. Audouze K, Juncker A, Roque F, Krysiak Baltyn K, Weinhold N, Taboureau O, et al. Deciphering diseases and biological targets for environmental chemicals using toxicogenomics networks. PLoS Comput Biol. 2010;6:e1000788 pubmed publisher
    ..The chemical-protein associations are supported through recent published studies, which illustrate the power of our approach that integrates toxicogenomics data with other data types. ..
  62. Kienhuis A, van de Poll M, Wortelboer H, van Herwijnen M, Gottschalk R, Dejong C, et al. Parallelogram approach using rat-human in vitro and rat in vivo toxicogenomics predicts acetaminophen-induced hepatotoxicity in humans. Toxicol Sci. 2009;107:544-52 pubmed publisher
    ..The present study is the first that used a toxicogenomics-based parallelogram approach, extrapolating in vitro to in vivo and interspecies, to reveal relevant mechanisms indicative of APAP-induced liver toxicity in humans in vivo. ..