Literature DB >> 10720767

Expression profiling in toxicology--potentials and limitations.

S Steiner1, N L Anderson.   

Abstract

Recent progress in genomics and proteomics technologies has created a unique opportunity to significantly impact the pharmaceutical drug development processes. The perception that cells and whole organisms express specific inducible responses to stimuli such as drug treatment implies that unique expression patterns, molecular fingerprints, indicative of a drug's efficacy and potential toxicity are accessible. The integration into state-of-the-art toxicology of assays allowing one to profile treatment-related changes in gene expression patterns promises new insights into mechanisms of drug action and toxicity. The benefits will be improved lead selection, and optimized monitoring of drug efficacy and safety in pre-clinical and clinical studies based on biologically relevant tissue and surrogate markers.

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Year:  2000        PMID: 10720767     DOI: 10.1016/s0378-4274(99)00236-2

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


  4 in total

1.  Transcriptional response of stress-regulated genes to cadmium exposure in the cockle Cerastoderma glaucum from the gulf of Gabès area (Tunisia).

Authors:  Sahar Karray; Justine Marchand; Brigitte Moreau; Emmanuelle Tastard; Stanislas Thiriet-Rupert; Alain Geffard; Laurence Delahaut; Françoise Denis; Amel Hamza-Chaffai; Benoît Chénais
Journal:  Environ Sci Pollut Res Int       Date:  2014-12-20       Impact factor: 4.223

2.  Human pharmacogenomics: the development of a science.

Authors:  Werner Kalow
Journal:  Hum Genomics       Date:  2004-08       Impact factor: 4.639

3.  Molecular identification and expression of differentially regulated genes of the European flounder, Platichthys flesus, submitted to pesticide exposure.

Authors:  J Marchand; A Tanguy; G Charrier; L Quiniou; E Plee-Gauthier; J Laroche
Journal:  Mar Biotechnol (NY)       Date:  2006-03-17       Impact factor: 3.619

4.  A computational toxicogenomics approach identifies a list of highly hepatotoxic compounds from a large microarray database.

Authors:  Héctor A Rueda-Zárate; Iván Imaz-Rosshandler; Roberto A Cárdenas-Ovando; Juan E Castillo-Fernández; Julieta Noguez-Monroy; Claudia Rangel-Escareño
Journal:  PLoS One       Date:  2017-04-27       Impact factor: 3.240

  4 in total

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