BMP-6 promotes E-cadherin expression through repressing δEF1 in breast cancer cells

<p>Abstract</p> <p>Background</p> <p>Bone morphogenetic protein-6 (BMP-6) is critically involved in many developmental processes. Recent studies indicate that BMP-6 is closely related to tumor differentiation and metastasis.</p> <p>Methods</p> <p>Quantitative RT-PCR was used to determine the expression of BMP-6, E-cadherin, and δEF1 at the mRNA level in MCF-7 and MDA-MB-231 breast cancer cells, as well as in 16 breast cancer specimens. Immunoblot analysis was used to measure the expression of δEF1 at the protein level in δEF1-overexpressing and δEF1-interfered MDA-MB-231 cells. Luciferase assay was used to determine the rhBMP-6 or δEF1 driven transcriptional activity of the E-cadherin promoter in MDA-MB-231 cells. Quantitative CHIP assay was used to detect the direct association of δEF1 with the E-cadherin proximal promoter in MDA-MB-231 cells.</p> <p>Results</p> <p>MCF-7 breast cancer cells, an ER⁺cell line that expressed high levels of BMP-6 and E-cadherin exhibited very low levels of δEF1 transcript. In contrast, MDA-MB-231 cells, an ER^-cell line had significantly reduced BMP-6 and E-cadherin mRNA levels, suggesting an inverse correlation between BMP-6/E-cadherin and δEF1. To determine if the same relationship exists in human tumors, we examined tissue samples of breast cancer from human subjects. In 16 breast cancer specimens, the inverse correlation between BMP-6/E-cadherin and δEF1 was observed in both ER⁺cases (4 of 8 cases) and ER^-cases (7 of 8 cases). Further, we found that BMP-6 inhibited δEF1 transcription, resulting in an up-regulation of E-cadherin mRNA expression. This is consistent with our analysis of the E-cadherin promoter demonstrating that BMP-6 was a potent transcriptional activator. Interestingly, ectopic expression of δEF1 was able to block BMP-6-induced transactivation of E-cadherin, whereas RNA interference-mediated down-regulation of endogenous δEF1 in breast cancer cells abolished E-cadherin transactivation by BMP-6. In addition to down-regulating the expression of δEF1, BMP-6 also physically dislodged δEF1 from E-cadherin promoter to allow the activation of E-cadherin transcription.</p> <p>Conclusion</p> <p>We conclude that repression of δEF1 plays a key role in mediating BMP-6-induced transcriptional activation of E-cadherin in breast cancer cells. Consistent with the fact that higher level of δEF1 expression is associated with more invasive phenotype of breast cancer cells, our collective data suggests that δEF1 is likely the switch through which BMP-6 restores E-cadherin-mediated cell-to-cell adhesion and prevents breast cancer metastasis.</p

Targets of the Entamoeba histolytica Transcription Factor URE3-BP

The Entamoeba histolytica transcription factor Upstream Regulatory Element 3-Binding Protein (URE3-BP) is a calcium-responsive regulator of two E. histolytica virulence genes, hgl5 and fdx1. URE3-BP was previously identified by a yeast one-hybrid screen of E. histolytica proteins capable of binding to the sequence TATTCTATT (Upstream Regulatory Element 3 (URE3)) in the promoter regions of hgl5 and fdx1. In this work, precise definition of the consensus URE3 element was performed by electrophoretic mobility shift assays (EMSA) using base-substituted oligonucleotides, and the consensus motif validated using episomal reporter constructs. Transcriptome profiling of a strain induced to produce a dominant-positive URE3-BP was then used to identify additional genes regulated by URE3-BP. Fifty modulated transcripts were identified, and of these the EMSA defined motif T[atg]T[tc][cg]T[at][tgc][tg] was found in over half of the promoters (54% p<0.0001). Fifteen of the URE3-BP regulated genes were potential membrane proteins, suggesting that one function of URE3-BP is to remodel the surface of E. histolytica in response to a calcium signal. Induction of URE3-BP leads to an increase in tranwell migration, suggesting a possible role in the regulation of cellular motility

Meta-Profiles of Gene Expression during Aging: Limited Similarities between Mouse and Human and an Unexpectedly Decreased Inflammatory Signature

Background: Skin aging is associated with intrinsic processes that compromise the structure of the extracellular matrix while promoting loss of functional and regenerative capacity. These processes are accompanied by a large-scale shift in gene expression, but underlying mechanisms are not understood and conservation of these mechanisms between humans and mice is uncertain. Results: We used genome-wide expression profiling to investigate the aging skin transcriptome. In humans, age-related shifts in gene expression were sex-specific. In females, aging increased expression of transcripts associated with T-cells, B-cells and dendritic cells, and decreased expression of genes in regions with elevated Zeb1, AP-2 and YY1 motif density. In males, however, these effects were contrasting or absent. When age-associated gene expression patterns in human skin were compared to those in tail skin from CB6F1 mice, overall human-mouse correspondence was weak. Moreover, inflammatory gene expression patterns were not induced with aging of mouse tail skin, and well-known aging biomarkers were in fact decreased (e.g., Clec7a, Lyz1 and Lyz2). These unexpected patterns and weak human-mouse correspondence may be due to decreased abundance of antigen presenting cells in mouse tail skin with age. Conclusions: Aging is generally associated with a pro-inflammatory state, but we have identified an exception to this pattern with aging of CB6F1 mouse tail skin. Aging therefore does not uniformly heighten inflammatory status across all mouse tissues. Furthermore, we identified both intercellular and intracellular mechanisms of transcriptome aging, including those that are sex- and species-specific

Meta-analysis of breast cancer microarray studies in conjunction with conserved <it>cis</it>-elements suggest patterns for coordinate regulation

<p>Abstract</p> <p>Background</p> <p>Gene expression measurements from breast cancer (BrCa) tumors are established clinical predictive tools to identify tumor subtypes, identify patients showing poor/good prognosis, and identify patients likely to have disease recurrence. However, diverse breast cancer datasets in conjunction with diagnostic clinical arrays show little overlap in the sets of genes identified. One approach to identify a set of consistently dysregulated candidate genes in these tumors is to employ meta-analysis of multiple independent microarray datasets. This allows one to compare expression data from a diverse collection of breast tumor array datasets generated on either cDNA or oligonucleotide arrays.</p> <p>Results</p> <p>We gathered expression data from 9 published microarray studies examining estrogen receptor positive (ER+) and estrogen receptor negative (ER-) BrCa tumor cases from the Oncomine database. We performed a meta-analysis and identified genes that were universally up or down regulated with respect to ER+ versus ER- tumor status. We surveyed both the proximal promoter and 3' untranslated regions (3'UTR) of our top-ranking genes in each expression group to test whether common sequence elements may contribute to the observed expression patterns. Utilizing a combination of known transcription factor binding sites (TFBS), evolutionarily conserved mammalian promoter and 3'UTR motifs, and microRNA (miRNA) seed sequences, we identified numerous motifs that were disproportionately represented between the two gene classes suggesting a common regulatory network for the observed gene expression patterns.</p> <p>Conclusion</p> <p>Some of the genes we identified distinguish key transcripts previously seen in array studies, while others are newly defined. Many of the genes identified as overexpressed in ER- tumors were previously identified as expression markers for neoplastic transformation in multiple human cancers. Moreover, our motif analysis identified a collection of specific <it>cis</it>-acting target sites which may collectively play a role in the differential gene expression patterns observed in ER+ versus ER- breast cancer tumors. Importantly, the gene sets and associated DNA motifs provide a starting point with which to explore the mechanistic basis for the observed expression patterns in breast tumors.</p