Prostate cancer is a leading cause of cancer-related mortality in men worldwide and there is a lack of effective treatment options for advanced (metastatic) prostate cancer. Currently, limited knowledge is available concerning the role of long non-coding RNAs in prostate cancer metastasis. In this study, we found that long non-coding RNA H19 (H19) and H19-derived microRNA-675 (miR-675) were significantly downregulated in the metastatic prostate cancer cell line M12 compared with the non-metastatic prostate epithelial cell line P69. Upregulation of H19 in P69 and PC3 cells significantly increased the level of miR-675 and repressed cell migration; however, ectopic expression of H19 in M12 cells could not increase the level of miR-675 and therefore had no effect on cell migration. Furthermore, we found that the expression level of either H19 or miR-675 in P69 cells was negatively associated with the expression of transforming growth factor b induced protein (TGFBI), an extracellular matrix protein involved in cancer metastasis. Dual luciferase reporter assays showed that miR-675 directly bound with 3 0 UTR of TGFBI mRNA to repress its translation. Taken together, we show for the first time that the H19-miR-675 axis acts as a suppressor of prostate cancer metastasis, which may have possible diagnostic and therapeutic potential for advanced prostate cancer. IntroductionProstate cancer is a leading cause of cancer-related mortality in men worldwide [1]. Bone metastases responsible for poor clinical outcomes are detectable in about 80% of advanced prostate cancer patients [2]. Since no effective treatment is available for advanced prostate cancer, it is urgent to understand the molecular mechanisms underlying prostate cancer metastasis, which may help identify novel diagnostic and therapeutic targets.Long non-coding RNAs (lncRNAs), with length > 200 nucleotides, have been considered as one type of gene expression regulator for decades. The first Abbreviations ECM, extracellular matrix; EGF, epidermal growth factor; GAPDH, glyceraldehyde-3-phosphate dehydrogenase; H19, lncRNA H19; hTGF-b-1, human transforming growth factor b-1; lncRNA, long non-coding RNA; miR-675, microRNA-675; miRNA, microRNA; RTCA, real-time cell analysis; TGFBI, transforming growth factor b induced protein.

Epithelial ovarian cancer (EOC) is the most common gynecologic malignancy. To identify the micro-ribonucleic acids (miRNAs) expression profile in EOC tissues that may serve as a novel diagnostic biomarker for EOC detection, the expression of 1722 miRNAs from 15 normal ovarian tissue samples and 48 ovarian cancer samples was profiled by using a quantitative real-time polymerase chain reaction (qRT-PCR) assay. A ten-microRNA signature (hsa-miR-1271-5p, hsa-miR-574-3p, hsa-miR-182-5p, hsa-miR-183-5p, hsa-miR-96-5p, hsa-miR-15b-5p, hsa-miR-182-3p, hsa-miR-141-5p, hsa-miR-130b-5p, and hsa-miR-135b-3p) was identified to be able to distinguish human ovarian cancer tissues from normal tissues with 97% sensitivity and 92% specificity. Two miRNA clusters of miR183-96-183 (miR-96-5p, and miR-182, miR183) and miR200 (miR-141-5p, miR200a, b, c and miR429) are significantly up-regulated in ovarian cancer tissue samples compared to those of normal tissue samples, suggesting theses miRNAs may be involved in ovarian cancer development.

Prostate cancer (PCa) is the most prevalent malignant carcinoma among males in western countries. Currently no treatments can cure advanced prostate cancers, so new diagnostic and therapeutic strategies are in urgent need. At present limited knowledge is available concerning the roles of dysregulated microRNAs in prostate cancer metastasis. In this study, we found that the expression of miR-130b was significantly down-regulated in prostate cancer cell lines and clinical prostate cancer tissues. Enforced over-expression of miR-130b in prostate cancer cells suppressed whereas knock-down of miR-130b increased cell migration and invasion. Using mouse model, we revealed that miR-130b-expressed prostate cancer cells displayed significant reduction in tumor metastasis. Furthermore, we identified and validated matrix metalloproteinase-2 (MMP2) as a direct target of miR-130b. Ectopic expression of MMP2 rescued miR-130b-suppressed cell migration and invasion, and knock-down of MMP2 antagonized the effect of silencing miR-130b.Taken together, our data reveal for the first time that miR-130b exerts a suppressive effect in prostate cancer metastasis through down-regulation of MMP2.

The identified miRNAs appear to be novel biomarkers for the detection of LPS, and may contribute to an understanding of the mechanisms of LPS tumorigenesis and its development, and further elucidate the characteristics of LPS subtypes.

Background: Identifying bladder cancer-specific miRNA expression signatures by large scale miRNA profiling Methods：30 bladder cancer (BC) tissue samples and matched adjacent normal bladder tissue samples from patients with BC were collected and were divided into two groups； a training group and a blind testing group. Expressions of 1900 miRNAs and controls were detected in a BC miRNA pool and in a normal miRNAs pool, respectively. 380 differential expressed miRNAs between the BC miRNA pool and the normal miRNA pool were selected. The primers for detecting the 380 selected miRNAs and controls were used to generate one 384-well panel. This panel was used to profile miRNA expression of each individual sample in the training group and in the blind testing group. Data analysis was performed using a machine learning approach of a support vector machine classifier with a Student's t-test feature selection procedure. Results： We identified signatures consisting of three or four miRNAs that could distinguish BC from normal controls with an accuracy of 100% in the training model and an accuracy of over 95% in the blind test. All identified signatures contain hsa-miR-133a. We also revealed that the miRNA183-96 cluster and the miR200 cluster are both significantly up-regulated in BC. Conclusions：The identified signatures containing hsa-miR-133a could be used as biomarkers in the diagnosis and prognosis of BC.