Literature DB >> 18996174

Use of toxicogenomics to understand mechanisms of drug-induced hepatotoxicity during drug discovery and development.

Eric A G Blomme1, Yi Yang, Jeffrey F Waring.   

Abstract

Hepatotoxicity is a common cause of failure in drug discovery and development and is also frequently the source of adverse drug reactions. Therefore, a better prediction, characterization and understanding of drug-induced hepatotoxicity could result in safer drugs and a more efficient drug discovery and development process. Among the 'omics technologies, toxicogenomics (or the use of gene expression profiling in toxicology) represents an attractive approach to predict toxicity and to gain a mechanistic understanding of toxic changes. In this review, we illustrate, using selected examples, how toxicogenomics can be applied to investigate drug-induced hepatotoxicity in animal models and in vitro systems. In general, this technology can not only improve the discipline of toxicology and risk assessment but also represent an extremely effective, hypothesis-generating alternative to rapidly understand mechanisms of hepatotoxicity.

Entities:  

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Year:  2008        PMID: 18996174     DOI: 10.1016/j.toxlet.2008.09.017

Source DB:  PubMed          Journal:  Toxicol Lett        ISSN: 0378-4274            Impact factor:   4.372


  30 in total

1.  Advanced molecular biologic techniques in toxicologic disease.

Authors:  Jeanine Ward; Gyongyi Szabo; David McManus; Edward Boyer
Journal:  J Med Toxicol       Date:  2011-12

2.  Predictive modeling of chemical hazard by integrating numerical descriptors of chemical structures and short-term toxicity assay data.

Authors:  Ivan Rusyn; Alexander Sedykh; Yen Low; Kathryn Z Guyton; Alexander Tropsha
Journal:  Toxicol Sci       Date:  2012-03-02       Impact factor: 4.849

Review 3.  Use of transcriptomics in understanding mechanisms of drug-induced toxicity.

Authors:  Yuxia Cui; Richard S Paules
Journal:  Pharmacogenomics       Date:  2010-04       Impact factor: 2.533

Review 4.  In vitro platforms for evaluating liver toxicity.

Authors:  Shyam Sundhar Bale; Lawrence Vernetti; Nina Senutovitch; Rohit Jindal; Manjunath Hegde; Albert Gough; William J McCarty; Ahmet Bakan; Abhinav Bhushan; Tong Ying Shun; Inna Golberg; Richard DeBiasio; Berk Osman Usta; D Lansing Taylor; Martin L Yarmush
Journal:  Exp Biol Med (Maywood)       Date:  2014-04-24

5.  Microengineered cell and tissue systems for drug screening and toxicology applications: Evolution of in-vitro liver technologies.

Authors:  O B Usta; W J McCarty; S Bale; M Hegde; R Jindal; A Bhushan; I Golberg; M L Yarmush
Journal:  Technology (Singap World Sci)       Date:  2015-03

6.  Enrichment with wood blocks does not affect toxicity assessment in an exploratory toxicology model using Sprague-Dawley rats.

Authors:  Amy C Ditewig; Natalie A Bratcher; Donna R Davila; Brian D Dayton; Paige Ebert; Philippe Lesuisse; Michael J Liguori; Jill M Wetter; Hyuna Yang; Wayne R Buck
Journal:  J Am Assoc Lab Anim Sci       Date:  2014-05       Impact factor: 1.232

7.  Effects of tris(1,3-dichloro-2-propyl)phosphate on pathomorphology and gene/protein expression related to thyroid disruption in rats.

Authors:  Fei Zhao; Jing Wang; Yanjun Fang; Jia Ding; Honglian Yang; Li Li; Zhuge Xi; Haixuan Qiao
Journal:  Toxicol Res (Camb)       Date:  2016-03-04       Impact factor: 3.524

8.  Cheminformatics analysis of assertions mined from literature that describe drug-induced liver injury in different species.

Authors:  Denis Fourches; Julie C Barnes; Nicola C Day; Paul Bradley; Jane Z Reed; Alexander Tropsha
Journal:  Chem Res Toxicol       Date:  2010-01       Impact factor: 3.739

9.  Gene expression profiling in male B6C3F1 mouse livers exposed to kava identifies--changes in drug metabolizing genes and potential mechanisms linked to kava toxicity.

Authors:  Lei Guo; Qiang Shi; Stacey Dial; Qingsu Xia; Nan Mei; Quan-zhen Li; Po-Chuen Chan; Peter Fu
Journal:  Food Chem Toxicol       Date:  2009-12-03       Impact factor: 6.023

10.  Prediction of pharmacological and xenobiotic responses to drugs based on time course gene expression profiles.

Authors:  Tao Huang; Weiren Cui; Lele Hu; Kaiyan Feng; Yi-Xue Li; Yu-Dong Cai
Journal:  PLoS One       Date:  2009-12-02       Impact factor: 3.240

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