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Impact of p53 Knockout and Topotecan Treatment on Gene Expression Profiles in Human Colon Carcinoma Cells

A Pharmacogenomic Study

Department of Pharmaceutical Sciences, Washington State University, Pullman, Washington 99164-6510 [S. S. D.], and Mathematical and Statistical Computing Laboratory, Center for Information Technology [P. J. M., L. Y., V. V. P.] and Laboratory of Molecular Pharmacology, Center for Cancer Research [W. R., Q. Y., J. L., K. W. K., J. N. W., Y. P.], National Cancer Institute, NIH, Bethesda, Maryland 20892-4255

To uncover transcriptional stress responses related to p53, we used cDNA microarrays (National Cancer Institute Oncochips comprising 6500 different genes) to characterize the gene expression profiles of wild-type p53 HCT-116 cells and an isogenic p53 knockout counterpart after treatment with topotecan, a specific topoisomerase I inhibitor. The use of the p53 knockout cells had the advantage over p53-overexpressing systems in that p53 activation is mediated physiologically. RNA was extracted after low (0.1 µM)- and high (1 µM)-dose topotecan at multiple time points within the first 6 h of treatment. To facilitate simultaneous study of the p53 status and pharmacological effects on gene expression, we developed a novel "cross-referenced network" experimental design and used multiple linear least squares fitting to optimize estimates of relative transcript levels in the network of experimental conditions. Approximately 10% of the transcripts were up- or down-regulated in response to topotecan in the p53+/+ cells, whereas only 1% of the transcripts changed in the p53-/- cells, indicating that p53 has a broad effect on the transcriptional response to this stress. Individual transcripts and their relationships were analyzed using clustered image maps and by a novel two-dimensional analysis/visualization, gene expression map, in which each gene expression level is represented as a function of both the genotypic/phenotypic difference (i.e., p53 status) and the treatment effect (i.e., of topotecan dose and time of exposure). Overall, drug-induced p53 activation was associated with a coherent genetic program leading to cell cycle arrest and apoptosis. We identified novel p53-induced and DNA damage-induced genes (the proapoptotic SIVA gene and a set of transforming growth factor ß-related genes). Genes induced independently of p53 included the antiapoptotic cFLIP gene and known stress genes related to the mitogen-activated protein kinase pathway and the Fos/Jun pathway. Genes that were negatively regulated by p53 included members of the antiapoptotic protein chaperone heat shock protein 70 family. Finally, among the p53-dependent genes whose expression was independent of drug treatment was S100A4, a small Ca²⁺-binding protein that has recently been implicated in p53 binding and regulation. The new experimental design and gene expression map analysis introduced here are applicable to a wide range of studies that encompass both treatment effects and genotypic or phenotypic differences.

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