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A genotoxic screen: rapid analysis of cellular dose-response to a wide range of agents that either damage DNA or alter genome maintenance pathways
Authors:Marple Teresa  Li Han  Hasty Paul
Institution:The Department of Molecular Medicine, The University of Texas Health Science Center at San Antonio, 15355 Lambda Drive, 78245-3207, USA.
Abstract:SNP analysis has come to the forefront of genomics since the mouse and human genomes have been sequenced. High throughput functional screens are necessary to evaluate these sequence databases. Described here is a genotoxic screen: a rapid method that determines the cellular dose-response to a wide range of agents that either damage DNA or alter basic cellular pathways important for maintaining genomic integrity. Importantly, a single person utilizing standard tissue culture equipment may perform these assays composed of 20 agents that attack genomic integrity or maintenance at many different levels. Thus, a small lab may perform this screen to determine the integrity of a wide range of DNA repair, chromatin metabolism, and response pathways without the limitations of investigator bias. A genotoxic screen will be useful when analyzing cells with either known genetic alterations (generated directly by the investigator or derived from individuals with known mutations) or unknown genetic alterations (cells with spontaneous mutations such as cancer-derived cells). Screening many genotoxins at one time will aid in determining the biological importance of these altered genes. Here we show the dose-response curves of mouse embryonic stem (ES) cells and HeLa cells exposed to 20 genotoxic agents. ES cells were chosen since they are amenable to genetic alteration by the investigator. HeLa cells were chosen since they were derived from cancer and are commonly used. Comparing the dose-response curves of these two cell lines show their relative sensitivity to these agents and helps define their genotoxic profile. As a part of phenomics, a large genotoxic profile database for cancer-derived cells, when integrated with other databases such as expression profiles and comparative genomic hybridization, may aid in maximizing the effectiveness of developing anti-cancer protocols.
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