Literature DB >> 11435125

Physiological function as regulation of large transcriptional programs: the cellular response to genotoxic stress.

S A Amundson1, M Bittner, P Meltzer, J Trent, A J Fornace.   

Abstract

The responses to ionizing radiation and other genotoxic environmental stresses are complex and are regulated by a number of overlapping molecular pathways. One such stress signaling pathway involves p53, which regulates the expression of over 100 genes already identified. It is also becoming increasingly apparent that the pattern of stress gene expression has some cell type specificity. It may be possible to exploit these differences in stress gene responsiveness as molecular markers through the use of a combined informatics and functional genomics approach. The techniques of microarray analysis potentially offer the opportunity to monitor changes in gene expression across the entire set of expressed genes in a cell or organism. As an initial step in the development of a functional genomics approach to stress gene analysis, we have recently demonstrated the utility of cDNA microarray hybridization to measure radiation-stress gene responses and identified a number of previously unknown radiation-regulated genes. The responses of some of these genes to DNA-damaging agents vary widely in cell lines from different tissues of origin and different genetic backgrounds. While this again highlights the importance of a cellular context to genotoxic stress responses, it also raises the prospect of expression-profiling of cell lines, tissues, and tumors. Such profiles may have a predictive value if they can define regions of 'expression space' that correlate with important endpoints, such as response to cancer therapy regimens, or identification of exposures to environmental toxins.

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Year:  2001        PMID: 11435125     DOI: 10.1016/s1096-4959(01)00389-x

Source DB:  PubMed          Journal:  Comp Biochem Physiol B Biochem Mol Biol        ISSN: 1096-4959            Impact factor:   2.231


  7 in total

1.  Characterization and interlaboratory comparison of a gene expression signature for differentiating genotoxic mechanisms.

Authors:  Heidrun Ellinger-Ziegelbauer; Jennifer M Fostel; Chinami Aruga; Daniel Bauer; Eric Boitier; Shibing Deng; Donna Dickinson; Anne-Celine Le Fevre; Albert J Fornace; Olivier Grenet; Yizhong Gu; Jean-Christophe Hoflack; Masako Shiiyama; Roger Smith; Ronald D Snyder; Catherine Spire; Gotaro Tanaka; Jiri Aubrecht
Journal:  Toxicol Sci       Date:  2009-05-22       Impact factor: 4.849

2.  Tau Ser262 phosphorylation is critical for Abeta42-induced tau toxicity in a transgenic Drosophila model of Alzheimer's disease.

Authors:  Koichi Iijima; Anthony Gatt; Kanae Iijima-Ando
Journal:  Hum Mol Genet       Date:  2010-05-12       Impact factor: 6.150

3.  Drosophila melanogaster MNK/Chk2 and p53 regulate multiple DNA repair and apoptotic pathways following DNA damage.

Authors:  Michael H Brodsky; Brian T Weinert; Garson Tsang; Yikang S Rong; Nadine M McGinnis; Kent G Golic; Donald C Rio; Gerald M Rubin
Journal:  Mol Cell Biol       Date:  2004-02       Impact factor: 4.272

4.  Analysis of common and specific mechanisms of liver function affected by nitrotoluene compounds.

Authors:  Youping Deng; Sharon A Meyer; Xin Guan; Barbara Lynn Escalon; Junmei Ai; Mitchell S Wilbanks; Ruth Welti; Natàlia Garcia-Reyero; Edward J Perkins
Journal:  PLoS One       Date:  2011-02-08       Impact factor: 3.240

5.  Analysis of Gene Expression Responses to a Salmonella Infection in Rugao Chicken Intestine Using GeneChips.

Authors:  D Q Luan; G B Chang; Z W Sheng; Y Zhang; W Zhou; Z Z Li; Y Liu; G H Chen
Journal:  Asian-Australas J Anim Sci       Date:  2012-02-01       Impact factor: 2.509

6.  Evaluation of toxicogenomics approaches for assessing the risk of nongenotoxic carcinogenicity in rat liver.

Authors:  Johannes Eichner; Clemens Wrzodek; Michael Römer; Heidrun Ellinger-Ziegelbauer; Andreas Zell
Journal:  PLoS One       Date:  2014-05-14       Impact factor: 3.240

7.  A Qualitative Modeling Approach for Whole Genome Prediction Using High-Throughput Toxicogenomics Data and Pathway-Based Validation.

Authors:  Saad Haider; Michael B Black; Bethany B Parks; Briana Foley; Barbara A Wetmore; Melvin E Andersen; Rebecca A Clewell; Kamel Mansouri; Patrick D McMullen
Journal:  Front Pharmacol       Date:  2018-10-02       Impact factor: 5.810

  7 in total

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