Novel candidate targets of beta-catenin/T-cell factor signaling identified by gene expression profiling of ovarian endometrioid adenocarcinomas.

The activity of beta-catenin (beta-cat), a key component of the Wnt signaling pathway, is deregulated in about 40% of ovarian endometrioid adenocarcinomas (OEAs), usually as a result of CTNNB1 gene mutations. The function of beta-cat in neoplastic transformation is dependent on T-cell factor (TCF) transcription factors, but specific genes activated by the interaction of beta-cat with TCFs in OEAs and other cancers with Wnt pathway defects are largely unclear. As a strategy to identify beta-cat/TCF transcriptional targets likely to contribute to OEA pathogenesis, we used oligonucleotide microarrays to compare gene expression in primary OEAs with mutational defects in beta-cat regulation (n = 11) to OEAs with intact regulation of beta-cat activity (n = 17). Both hierarchical clustering and principal component analysis based on global gene expression distinguished beta-cat-defective tumors from those with intact beta-cat regulation. We identified 81 potential beta-cat/TCF targets by selecting genes with at least 2-fold increased expression in beta-cat-defective versus beta-cat regulation-intact tumors and significance in a t test (P < 0.05). Seven of the 81 genes have been previously reported as Wnt/beta-cat pathway targets (i.e., BMP4, CCND1, CD44, FGF9, EPHB3, MMP7, and MSX2). Differential expression of several known and candidate target genes in the OEAs was confirmed. For the candidate target genes CST1 and EDN3, reporter and chromatin immunoprecipitation assays directly implicated beta-cat and TCF in their regulation. Analysis of presumptive regulatory elements in 67 of the 81 candidate genes for which complete genomic sequence data were available revealed an apparent difference in the location and abundance of consensus TCF-binding sites compared with the patterns seen in control genes. Our findings imply that analysis of gene expression profiling data from primary tumor samples annotated with detailed molecular information may be a powerful approach to identify key downstream targets of signaling pathways defective in cancer cells.