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.
Original language | English (US) |
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Pages (from-to) | 703-710 |
Number of pages | 8 |
Journal | Comparative Biochemistry and Physiology - B Biochemistry and Molecular Biology |
Volume | 129 |
Issue number | 4 |
DOIs | |
State | Published - Jan 1 2001 |
Keywords
- Biomarkers
- Cancer
- Functional genomics
- Gene expression
- Ionizing radiation
- Stress
- cDNA microarray
- p53
ASJC Scopus subject areas
- Biochemistry
- Physiology
- Molecular Biology