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      Distinct microRNA expression profile and targeted biological pathways in functional myeloid-derived suppressor cells induced by Δ9-tetrahydrocannabinol in vivo: regulation of CCAAT/enhancer-binding protein α by microRNA-690.

      The Journal of Biological Chemistry
      Analgesics, Non-Narcotic, pharmacology, Animals, Antigens, Differentiation, biosynthesis, genetics, immunology, Bone Marrow Cells, cytology, metabolism, CCAAT-Enhancer-Binding Proteins, Cells, Cultured, Dronabinol, Female, Gene Expression Regulation, drug effects, Immune Tolerance, Mice, Myeloid Cells

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          Abstract

          Δ(9)-Tetrahydrocannabinol (THC), the major bioactive component of marijuana, has been shown to induce functional myeloid-derived suppressor cells (MDSCs) in vivo. Here, we studied the involvement of microRNA (miRNA) in this process. CD11b(+)Gr-1(+) MDSCs were purified from peritoneal exudates of mice administered with THC and used for genome-wide miRNA profiling. Expression of CD31 and Ki-67 confirmed that the THC-MDSCs were immature and proliferating. THC-induced MDSCs exhibited distinct miRNA expression signature relative to various myeloid cells and BM precursors. We identified 13 differentially expressed (>2-fold) miRNA in THC-MDSCs relative to control BM precursors. In silico target prediction for these miRNA and pathway analysis using multiple bioinformatics tools revealed significant overrepresentation of Gene Ontology clusters within hematopoiesis, myeloid cell differentiation, and regulation categories. Insulin-like growth factor 1 signaling involved in cell growth and proliferation, and myeloid differentiation pathways were among the most significantly enriched canonical pathways. Among the differentially expressed, miRNA-690 was highly overexpressed in THC-MDSCs (∼16-fold). Transcription factor CCAAT/enhancer-binding protein α (C/EBPα) was identified as a potential functional target of miR-690. Supporting this, C/EBPα expression was attenuated in THC-MDSCs as compared with BM precursors and exhibited an inverse relation with miR-690. miR-690 knockdown using peptide nucleic acid-antagomiR was able to unblock and significantly increase C/EBPα expression establishing the functional link. Further, CD11b(+)Ly6G(+)Ly6C(+) and CD11b(+)Ly6G(-)Ly6C(+) purified subtypes showed high levels of miR-690 with attenuated C/EBPα expression. Moreover, EL-4 tumor-elicited MDSCs showed increased miR-690 expression. In conclusion, miRNA are significantly altered during the generation of functional MDSC from BM. Select miRNA such as miR-690 targeting genes involved in myeloid expansion and differentiation likely play crucial roles in this process and therefore in cannabinoid-induced immunosuppression.

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          Integration of biological networks and gene expression data using Cytoscape.

          Cytoscape is a free software package for visualizing, modeling and analyzing molecular and genetic interaction networks. This protocol explains how to use Cytoscape to analyze the results of mRNA expression profiling, and other functional genomics and proteomics experiments, in the context of an interaction network obtained for genes of interest. Five major steps are described: (i) obtaining a gene or protein network, (ii) displaying the network using layout algorithms, (iii) integrating with gene expression and other functional attributes, (iv) identifying putative complexes and functional modules and (v) identifying enriched Gene Ontology annotations in the network. These steps provide a broad sample of the types of analyses performed by Cytoscape.
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            Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites

            mirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.
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              miRecords: an integrated resource for microRNA–target interactions

              MicroRNAs (miRNAs) are an important class of small noncoding RNAs capable of regulating other genes’ expression. Much progress has been made in computational target prediction of miRNAs in recent years. More than 10 miRNA target prediction programs have been established, yet, the prediction of animal miRNA targets remains a challenging task. We have developed miRecords, an integrated resource for animal miRNA–target interactions. The Validated Targets component of this resource hosts a large, high-quality manually curated database of experimentally validated miRNA–target interactions with systematic documentation of experimental support for each interaction. The current release of this database includes 1135 records of validated miRNA–target interactions between 301 miRNAs and 902 target genes in seven animal species. The Predicted Targets component of miRecords stores predicted miRNA targets produced by 11 established miRNA target prediction programs. miRecords is expected to serve as a useful resource not only for experimental miRNA researchers, but also for informatics scientists developing the next-generation miRNA target prediction programs. The miRecords is available at http://miRecords.umn.edu/miRecords.
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