Literature DB >> 11323195

Microarray analysis of hepatotoxins in vitro reveals a correlation between gene expression profiles and mechanisms of toxicity.

J F Waring1, R Ciurlionis, R A Jolly, M Heindel, R G Ulrich.   

Abstract

A rate-limiting step that occurs in the drug discovery process is toxicological evaluation of new compounds. New techniques that use small amounts of the experimental compound and provide a high degree of predictivity would greatly improve this process. The field of microarray technology, which allows one to monitor thousands of gene expression changes simultaneously, is rapidly advancing and is already being applied to numerous areas in toxicology. However, it remains to be determined if compounds with similar toxic mechanisms produce similar changes in transcriptional expression. In addition, it must be determined if gene expression changes caused by an agent in vitro would reflect those produced in vivo. In order to address these questions, we treated rat hepatocytes with 15 known hepatoxins (carbon tetrachloride, allyl alcohol, aroclor 1254, methotrexate, diquat, carbamazepine, methapyrilene, arsenic, diethylnitrosamine, monocrotaline, dimethyl-formamide, amiodarone, indomethacin, etoposide, and 3-methylcholanthrene) and used microarray technology to characterize the compounds based on gene expression changes. Our results showed that gene expressional profiles for compounds with similar toxic mechanisms indeed formed clusters, suggesting a similar effect on transcription. There was not complete identity, however, indicating that each compound produced a unique signature. These results show that large-scale analysis of gene expression using microarray technology has promise as a diagnostic tool for toxicology.

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Year:  2001        PMID: 11323195     DOI: 10.1016/s0378-4274(01)00267-3

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


  41 in total

1.  Prediction of clinical drug efficacy by classification of drug-induced genomic expression profiles in vitro.

Authors:  Erik C Gunther; David J Stone; Robert W Gerwien; Patricia Bento; Melvyn P Heyes
Journal:  Proc Natl Acad Sci U S A       Date:  2003-07-17       Impact factor: 11.205

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.  The evolution of bioinformatics in toxicology: advancing toxicogenomics.

Authors:  Cynthia A Afshari; Hisham K Hamadeh; Pierre R Bushel
Journal:  Toxicol Sci       Date:  2010-12-22       Impact factor: 4.849

4.  Transcriptional profiling and biological pathway analysis of human equivalence PCB exposure in vitro: indicator of disease and disorder development in humans.

Authors:  Somiranjan Ghosh; Partha S Mitra; Christopher A Loffredo; Tomas Trnovec; Lubica Murinova; Eva Sovcikova; Svetlana Ghimbovschi; Shizhu Zang; Eric P Hoffman; Sisir K Dutta
Journal:  Environ Res       Date:  2015-02-27       Impact factor: 6.498

5.  Classification of a large microarray data set: algorithm comparison and analysis of drug signatures.

Authors:  Georges Natsoulis; Laurent El Ghaoui; Gert R G Lanckriet; Alexander M Tolley; Fabrice Leroy; Shane Dunlea; Barrett P Eynon; Cecelia I Pearson; Stuart Tugendreich; Kurt Jarnagin
Journal:  Genome Res       Date:  2005-05       Impact factor: 9.043

6.  Gene expression profiling and its practice in drug development.

Authors:  Murty V Chengalvala; Vargheese M Chennathukuzhi; Daniel S Johnston; Panayiotis E Stevis; Gregory S Kopf
Journal:  Curr Genomics       Date:  2007-06       Impact factor: 2.236

Review 7.  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

8.  Blood gene expression markers to detect and distinguish target organ toxicity.

Authors:  Christina Umbright; Rajendran Sellamuthu; Shengqiao Li; Michael Kashon; Michael Luster; Pius Joseph
Journal:  Mol Cell Biochem       Date:  2009-09-26       Impact factor: 3.396

9.  Transformation of SV40-immortalized human uroepithelial cells by 3-methylcholanthrene increases IFN- and Large T Antigen-induced transcripts.

Authors:  Lynn M Crosby; Tanya M Moore; Michael George; Lawrence W Yoon; Marilyn J Easton; Hong Ni; Kevin T Morgan; Anthony B DeAngelo
Journal:  Cancer Cell Int       Date:  2010-02-23       Impact factor: 5.722

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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