Survivin is an inhibitor of apoptosis protein, which is over-expressed in most tumors. Aberrant expression of survivin and loss of wild-type p53 in many tumors prompted us to investigate a possible link between these two events. Here we show that wild-type p53 represses survivin expression at both mRNA and protein levels. Transient transfection analyses revealed that the expression of wild-type p53, but not mutant p53, was associated with strong repression of the survivin promoter in various cell types. The over-expression of exogenous survivin protein rescues cells from p53-induced apoptosis in a dose-dependent manner, suggesting that loss of survivin mediates, at least, in part the p53-dependent apoptotic pathway. In spite of the presence of two putative p53-binding sites in the survivin promoter, deletion and mutation analyses suggested that neither site is required for transcriptional repression of survivin expression. This was con®rmed by chromatin immunoprecipitation assays. Further analyses suggested that the modi®cation of chromatin within the survivin promoter could be a molecular explanation for silencing of survivin gene transcription by p53.

Here we present a strategy to identify genes regulated by specific transcription factors in the human genome, and apply it to p53. We first collected promoters or introns of all genes available using two methods: GenBank TM annotation and a computationally derived transcript map. 4,852 genes analyzed in this way contained at least one p53 consensus binding sequence. Of 13 genes randomly selected for mRNA analysis, 11 were shown to respond to p53 expression. Five promoters were analyzed by chromatin immunoprecipitation, which revealed that all were bound by p53 in vivo. We then analyzed 33,615 unique human genes on cDNA microarrays, identifying 1,501 genes that respond to p53 expression. A parameter was derived that demonstrates that in silico prediction greatly enriches for genes that are activated and repressed by p53 and assists us to suggest other signaling pathways that may be connected to p53. The methods shown here illustrate a novel approach to analysis of global gene regulatory network through the integration of human genomic sequence information and genomewide gene expression analysis.

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