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      SNHG16/miR-140-5p axis promotes esophagus cancer cell proliferation, migration and EMT formation through regulating ZEB1

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          Abstract

          Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignancies. Long noncoding RNAs (lncRNAs) have been identified to be associated with many diseases including tumors, and involved in the regulation of a wide array of pathophysiological processes. Small nucleolar RNA host gene 16 (SNHG16), also known as noncoding RNA expressed in aggressive neuroblastoma, was newly identified as a potential oncogene in many cancers. However, its role in ESCC has not been investigated. In the current study, the level of SNHG16 in the ESCC tissues and cell lines was measured by quantitative real-time PCR (qRT-PCR). Then loss-of-function assays were performed to explore the biological effects of SNHG16 in ESCC cell. Based on the online database analysis tools, we uncovered that miR-140-5p could interact with SNHG16 and the level of miR-140-5p was inverse correlated with SNHG16 in ESCC specimens. Moreover, RIP, RNA pulldown system and dual luciferase reporter assay further provided evidence that SNHG16 directly targets miR-140-5p by binding with microRNA binding site harboring in the SNHG16 sequence. Furthermore, bioinformatics analysis revealed that ZEB1 is a target of miR-140-5p in ESCC. Collectively, our findings suggested that SNHG16 could act as an oncogenic lncRNA that promotes tumor progression through acting as an endogenous ‘sponge’ by competing with miR-140-5p, thereby regulating target ZEB1.

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          A coding-independent function of gene and pseudogene mRNAs regulates tumour biology

          The canonical role of messenger RNA (mRNA) is to deliver protein-coding information to sites of protein synthesis. However, given that microRNAs bind to RNAs, we hypothesized that RNAs possess a biological role in cancer cells that relies upon their ability to compete for microRNA binding and is independent of their protein-coding function. As a paradigm for the protein-coding-independent role of RNAs, we describe the functional relationship between the mRNAs produced by the PTEN tumour suppressor gene and its pseudogene (PTENP1) and the critical consequences of this interaction. We find that PTENP1 is biologically active as determined by its ability to regulate cellular levels of PTEN, and that it can exert a growth-suppressive role. We also show that PTENP1 locus is selectively lost in human cancer. We extend our analysis to other cancer-related genes that possess pseudogenes, such as oncogenic KRAS. Further, we demonstrate that the transcripts of protein coding genes such as PTEN are also biologically active. Together, these findings attribute a novel biological role to expressed pseudogenes, as they can regulate coding gene expression, and reveal a non-coding function for mRNAs.
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            Long noncoding RNA associated-competing endogenous RNAs in gastric cancer

            Some long noncoding RNAs (lncRNAs) play important roles in the regulation of gene expression by acting as competing endogenous RNAs (ceRNAs). However, the roles of lncRNA associated-ceRNAs in oncogenesis are not fully understood. Here, based on lncRNA microarray data of gastric cancer, bioinformatic algorithm miRcode and microRNA (miRNA) targets database TarBase, we first constructed an lncRNA-miRNA-mRNA network. Then, we confirmed it by data of six types of other cancer including head and neck squamous cell carcinoma, prostate cancer, papillary thyroid carcinoma, pituitary gonadotrope tumors, ovarian cancer, and chronic lymphocytic leukemia. The results showed a clear cancer-associated ceRNA network. Eight lncRNAs (AC009499.1, GACAT1, GACAT3, H19, LINC00152, AP000288.2, FER1L4, and RP4-620F22.3) and nine miRNAs (miR-18a-5p, miR-18b-5p, miR-19a-3p, miR-20b-5p, miR-106a-5p, miR-106b-5p, miR-31-5p, miR-139-5p, and miR-195-5p) were involved. For instance, through its miRNA response elements (MREs) to compete for miR-106a-5p, lncRNA-FER1L4 regulates the expression of PTEN, RB1, RUNX1, VEGFA, CDKN1A, E2F1, HIPK3, IL-10, and PAK7. Furthermore, cellular experimental results indicated that FER1L4-small interfering RNA (siRNA) simultaneously suppressed FER1L4 and RB1 mRNA level. These results suggest that lncRNAs harbor MREs and play important roles in post-transcriptional regulation in cancer.
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              PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction

              In the recent few years, an increasing number of studies have shown that microRNAs (miRNAs) play critical roles in many fundamental and important biological processes. As one of pathogenetic factors, the molecular mechanisms underlying human complex diseases still have not been completely understood from the perspective of miRNA. Predicting potential miRNA-disease associations makes important contributions to understanding the pathogenesis of diseases, developing new drugs, and formulating individualized diagnosis and treatment for diverse human complex diseases. Instead of only depending on expensive and time-consuming biological experiments, computational prediction models are effective by predicting potential miRNA-disease associations, prioritizing candidate miRNAs for the investigated diseases, and selecting those miRNAs with higher association probabilities for further experimental validation. In this study, Path-Based MiRNA-Disease Association (PBMDA) prediction model was proposed by integrating known human miRNA-disease associations, miRNA functional similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity for miRNAs and diseases. This model constructed a heterogeneous graph consisting of three interlinked sub-graphs and further adopted depth-first search algorithm to infer potential miRNA-disease associations. As a result, PBMDA achieved reliable performance in the frameworks of both local and global LOOCV (AUCs of 0.8341 and 0.9169, respectively) and 5-fold cross validation (average AUC of 0.9172). In the cases studies of three important human diseases, 88% (Esophageal Neoplasms), 88% (Kidney Neoplasms) and 90% (Colon Neoplasms) of top-50 predicted miRNAs have been manually confirmed by previous experimental reports from literatures. Through the comparison performance between PBMDA and other previous models in case studies, the reliable performance also demonstrates that PBMDA could serve as a powerful computational tool to accelerate the identification of disease-miRNA associations.
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                Author and article information

                Journal
                Oncotarget
                Oncotarget
                Oncotarget
                ImpactJ
                Oncotarget
                Impact Journals LLC
                1949-2553
                2 January 2018
                11 December 2017
                : 9
                : 1
                : 1028-1040
                Affiliations
                1 Department of Medical Oncology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing, Jiangsu, China
                Author notes
                Correspondence to: Long-Bang Chen, chenlongbang@ 123456yeah.net
                [*]

                These authors have contributed equally to this work

                Article
                23178
                10.18632/oncotarget.23178
                5787416
                29416674
                6c508889-fbc6-40c5-9596-c9c09ca6a03f
                Copyright: © 2018 Zhang et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License 3.0 (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 25 July 2017
                : 26 November 2017
                Categories
                Research Paper

                Oncology & Radiotherapy
                esophagus cancer,long non-coding rna,snhg16,proliferation,emt
                Oncology & Radiotherapy
                esophagus cancer, long non-coding rna, snhg16, proliferation, emt

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