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      MicroRNA-466 inhibits tumor growth and bone metastasis in prostate cancer by direct regulation of osteogenic transcription factor RUNX2

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          Abstract

          MicroRNAs (miRNAs) have emerged as key players in cancer progression and metastatic initiation yet their importance in regulating prostate cancer (PCa) metastasis to bone has begun to be appreciated. We employed multimodal strategy based on in-house PCa clinical samples, publicly available TCGA cohorts, a panel of cell lines, in silico analyses, and a series of in vitro and in vivo assays to investigate the role of miR-466 in PCa. Expression analyses revealed that miR-466 is under-expressed in PCa compared to normal tissues. Reconstitution of miR-466 in metastatic PCa cell lines impaired their oncogenic functions such as cell proliferation, migration/invasion and induced cell cycle arrest, and apoptosis compared to control miRNA. Conversely, attenuation of miR-466 in normal prostate cells induced tumorigenic characteristics. miR-466 suppressed PCa growth and metastasis through direct targeting of bone-related transcription factor RUNX2. Overexpression of miR-466 caused a marked downregulation of integrated network of RUNX2 target genes such as osteopontin, osteocalcin, ANGPTs, MMP11 including Fyn, pAkt, FAK and vimentin that are known to be involved in migration, invasion, angiogenesis, EMT and metastasis. Xenograft models indicate that miR-466 inhibits primary orthotopic tumor growth and spontaneous metastasis to bone. Receiver operating curve and Kaplan–Meier analyses show that miR-466 expression can discriminate between malignant and normal prostate tissues; and can predict biochemical relapse. In conclusion, our data strongly suggests miR-466-mediated attenuation of RUNX2 as a novel therapeutic approach to regulate PCa growth, particularly metastasis to bone. This study is the first report documenting the anti-bone metastatic role and clinical significance of miR-466 in prostate cancer.

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          Most cited references18

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          MicroRNA expression patterns to differentiate pancreatic adenocarcinoma from normal pancreas and chronic pancreatitis.

          While global microRNA (miRNA) expression patterns of many embryologic, physiologic, and oncogenic processes have been described, description of the role of miRNAs in ductal adenocarcinoma of the pancreas is lacking. To define the expression pattern of miRNAs in pancreatic cancer and compare it with those of normal pancreas and chronic pancreatitis. Specimens were obtained at a National Cancer Institute-designated comprehensive cancer center from patients with ductal adenocarcinoma of the pancreas (n = 65) or chronic pancreatitis (n = 42) (January 2000-December 2005). All patients underwent curative pancreatectomy; those with pancreatic cancer were chemotherapy-naive. RNA harvested from resected pancreatic cancers and matched benign adjacent pancreatic tissue as well as from chronic pancreatitis specimens was hybridized to miRNA microarrays. Identification of differentially expressed miRNAs that could differentiate pancreatic cancer from normal pancreas, chronic pancreatitis, or both, as well as a pattern of miRNA expression predictive of long-term (>24 months) survival. Significance of Analysis of Microarrays and Prediction of Analysis of Microarrays were undertaken to identify miRNAs predictive of tissue type and prognosis. P values were calculated by t test, adjusted for multiple testing. Kaplan-Meier survival curves were constructed using mean miRNA expression (high vs low) as threshold and compared by log-rank analysis. Twenty-one miRNAs with increased expression and 4 with decreased expression were identified that correctly differentiated pancreatic cancer from benign pancreatic tissue in 90% of samples by cross validation. Fifteen overexpressed and 8 underexpressed miRNAs differentiated pancreatic cancer from chronic pancreatitis with 93% accuracy. A subgroup of 6 miRNAs was able to distinguish long-term survivors with node-positive disease from those dying within 24 months. Finally, high expression of miR-196a-2 was found to predict poor survival (median, 14.3 months [95% confidence interval, 12.4-16.2] vs 26.5 months [95% confidence interval, 23.4-29.6]; P = .009). Pancreatic cancer may have a distinct miRNA expression pattern that may differentiate it from normal pancreas and chronic pancreatitis. miRNA expression patterns may be able to distinguish between long- and short-term survivors, but these findings need to be validated in other study populations.
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            MicroRNAs accurately identify cancer tissue origin.

            MicroRNAs (miRNAs) belong to a class of noncoding, regulatory RNAs that is involved in oncogenesis and shows remarkable tissue specificity. Their potential for tumor classification suggests they may be used in identifying the tissue in which cancers of unknown primary origin arose, a major clinical problem. We measured miRNA expression levels in 400 paraffin-embedded and fresh-frozen samples from 22 different tumor tissues and metastases. We used miRNA microarray data of 253 samples to construct a transparent classifier based on 48 miRNAs. Two-thirds of samples were classified with high confidence, with accuracy >90%. In an independent blinded test-set of 83 samples, overall high-confidence accuracy reached 89%. Classification accuracy reached 100% for most tissue classes, including 131 metastatic samples. We further validated the utility of the miRNA biomarkers by quantitative RT-PCR using 65 additional blinded test samples. Our findings demonstrate the effectiveness of miRNAs as biomarkers for tracing the tissue of origin of cancers of unknown primary origin.
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              MicroRNA signature predicts survival and relapse in lung cancer.

              We investigated whether microRNA expression profiles can predict clinical outcome of NSCLC patients. Using real-time RT-PCR, we obtained microRNA expressions in 112 NSCLC patients, which were divided into the training and testing sets. Using Cox regression and risk-score analysis, we identified a five-microRNA signature for the prediction of treatment outcome of NSCLC in the training set. This microRNA signature was validated by the testing set and an independent cohort. Patients with high-risk scores in their microRNA signatures had poor overall and disease-free survivals compared to the low-risk-score patients. This microRNA signature is an independent predictor of the cancer relapse and survival of NSCLC patients.
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                Author and article information

                Journal
                Cell Death Dis
                Cell Death Dis
                Cell Death & Disease
                Nature Publishing Group
                2041-4889
                January 2017
                26 January 2017
                1 January 2017
                : 8
                : 1
                : e2572
                Affiliations
                [1 ]Department of Urology, VA Medical Center and UCSF , San Francisco, CA, USA
                [2 ]CPMC Research Institute , San Francisco, CA, USA
                [3 ]Department of Biochemistry and Surgery, University of Vermont College of Medicine , 148 Beaumont Avenue, Burlington, VT, USA
                Author notes
                [* ]Department of Urology (112F), VA Medical Center and UCSF , 4150 Clement Street, San Francisco, CA 94121, USA. Tel: +415 221 4810 × 22578; Fax: +415-750-6639; E-mail: Shahana.Majid@ 123456ucsf.edu
                Article
                cddis201715
                10.1038/cddis.2017.15
                5386393
                28125091
                35b220e7-1342-411a-9283-6bbb989287b7
                Copyright © 2017 The Author(s)

                Cell Death and Disease is an open-access journal published by Nature Publishing Group. This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 09 November 2016
                : 20 December 2016
                : 03 January 2017
                Categories
                Original Article

                Cell biology
                Cell biology

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