MicroRNA-194 inhibits epithelial to mesenchymal transition of endometrial cancer cells by targeting oncogene BMI-1

<p>Abstract</p> <p>Background</p> <p>Epithelial-mesenchymal transition (EMT) is the key process driving cancer metastasis. Oncogene/self renewal factor BMI-1 has been shown to induce EMT in cancer cells. Recent studies have implied that noncoding microRNAs (miRNAs) act as crucial modulators for EMT. The aims of this study was to determine the roles of BMI-1 in inducing EMT of endometrial cancer (EC) cells and the possible role of miRNA in controlling BMI-1 expression.</p> <p>Methods and results</p> <p>We evaluated the expression of BMI-1 gene in a panel of EC cell lines, and detected a strong association with invasive capability. Stable silencing of BMI-1 in invasive mesenchymal-type EC cells up-regulated the epithelial marker E-cadherin, down-regulated mesenchymal marker Vimentin, and significantly reduced cell invasion <it>in vitro</it>. Furthermore, we discovered that the expression of BMI-1 was suppressed by miR-194 via direct binding to the BMI-1 3'-untranslated region 3'-UTR). Ectopic expression of miR-194 in EC cells induced a mesenchymal to epithelial transition (MET) by restoring E-cadherin, reducing Vimentin expression, and inhibiting cell invasion <it>in vitro</it>. Moreover, BMI-1 knockdown inhibited <it>in vitro </it>EC cell proliferation and clone growth, correlated with either increased p16 expression or decreased expression of stem cell and chemoresistance markers (SOX-2, KLF4 and MRP-1).</p> <p>Conclusion</p> <p>These findings demonstrate the novel mechanism for BMI-1 in contributing to EC cell invasion and that repression of BMI-1 by miR-194 could have a therapeutic potential to suppress EC metastasis.</p

Risk prediction models for dementia constructed by supervised principal component analysis using miRNA expression data

Alzheimer’s disease (AD) is the most common subtype of dementia, followed by Vascular Dementia (VaD), and Dementia with Lewy Bodies (DLB). Recently, microRNAs (miRNAs) have received a lot of attention as the novel biomarkers for dementia. Here, using serum miRNA expression of 1,601 Japanese individuals, we investigated potential miRNA biomarkers and constructed risk prediction models, based on a supervised principal component analysis (PCA) logistic regression method, according to the subtype of dementia. The final risk prediction model achieved a high accuracy of 0.873 on a validation cohort in AD, when using 78 miRNAs: Accuracy = 0.836 with 86 miRNAs in VaD; Accuracy = 0.825 with 110 miRNAs in DLB. To our knowledge, this is the first report applying miRNA-based risk prediction models to a dementia prospective cohort. Our study demonstrates our models to be effective in prospective disease risk prediction, and with further improvement may contribute to practical clinical use in dementia

Use of Non-Amplified RNA Samples for Microarray Analysis of Gene Expression

Demand for high quality gene expression data has driven the development of revolutionary microarray technologies. The quality of the data is affected by the performance of the microarray platform as well as how the nucleic acid targets are prepared. The most common method for target nucleic acid preparation includes in vitro transcription amplification of the sample RNA. Although this method requires a small amount of starting material and is reported to have high reproducibility, there are also technical disadvantages such as amplification bias and the long, laborious protocol. Using RNA derived from human brain, breast and colon, we demonstrate that a non-amplification method, which was previously shown to be inferior, could be transformed to a highly quantitative method with a dynamic range of five orders of magnitude. Furthermore, the correlation coefficient calculated by comparing microarray assays using non-amplified samples with qRT-PCR assays was approximately 0.9, a value much higher than when samples were prepared using amplification methods. Our results were also compared with data from various microarray platforms studied in the MicroArray Quality Control (MAQC) project. In combination with micro-columnar 3D-Gene™ microarray, this non-amplification method is applicable to a variety of genetic analyses, including biomarker screening and diagnostic tests for cancer

Emerging Therapeutic Biomarkers in Endometrial Cancer

Although clinical trials of molecular therapies targeting critical biomarkers (mTOR, epidermal growth factor receptor/epidermal growth factor receptor 2, and vascular endothelial growth factor) in endometrial cancer show modest effects, there are still challenges that might remain regarding primary/acquired drug resistance and unexpected side effects on normal tissues. New studies that aim to target both genetic and epigenetic alterations (noncoding microRNA) underlying malignant properties of tumor cells and to specifically attack tumor cells using cell surface markers overexpressed in tumor tissue are emerging. More importantly, strategies that disrupt the cancer stem cell/epithelial-mesenchymal transition-dependent signals and reactivate antitumor immune responses would bring new hope for complete elimination of all cell compartments in endometrial cancer. We briefly review the current status of molecular therapies tested in clinical trials and mainly discuss the potential therapeutic candidates that are possibly used to develop more effective and specific therapies against endometrial cancer progression and metastasis

Protein related to DAN and cerberus is a bone morphogenetic protein antagonist that participates in ovarian paracrine regulation

Bone morphogenetic proteins (BMPs) are important for body patterning and morphogenesis, whereas several BMP antagonists regulate the functions of BMPs during embryonic development and tissue differentiation. Protein related to DAN and cerberus (PRDC) is a secreted protein with a cystine knot structure identified by gene trapping in embryonic stem cells. Although PRDC shows sequence homology with proteins of the BMP antagonist family, its biological activity and physiological functions are unclear. We generated recombinant PRDC and its paralog, gremlin, and tested their ability to suppress actions initiated by diverse BMP proteins. Similar to the known BMP antagonist, gremlin, PRDC blocked ligand signaling induced by BMP2 and BMP4 but had minimal effects on reporter gene activation induced by GDF-9, activin, or transforming growth factor-beta. Co-precipitation assays further demonstrated the direct protein-protein interactions between PRDC and BMP2 or BMP4. Reverse transcriptase-PCR analyses indicated that PRDC transcripts are widely expressed showing higher levels in ovary, brain, and spleen. In mouse ovary, PRDC transcripts were increased following gonadotropin treatment. In situ hybridization analyses further indicated that ovarian PRDC transcripts are localized in granulosa cells of selective follicles. In addition, co-treatment with PRDC antagonized the inhibitory effects of BMP4 on the follicle-stimulating hormone stimulation of progesterone production by cultured rat granulosa cells. Thus, PRDC is a potent BMP antagonist with a wide tissue expression pattern, and ovarian PRDC expressed in granulosa cells could be involved in follicular development by antagonizing the actions of theca cell-derived BMPs