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Transforming growth factor-β1 (TGFβ1)-induced differentiation into and the activation of myofibroblasts have been regarded as critical events in benign prostatic hyperplasia (BPH); however, the underlying mechanisms of BPH pathogenesis remain unclear. Microarray profiling, STRING analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation, and Gene Ontology (GO) enrichment analysis were performed to confirm the candidate genes and long non-coding RNA (lncRNAs) related to BPH. Collagen Type III (COL3A1) was significantly upregulated by TGFβ1 in prostate stromal cells (PrSCs) and might be involved in DNM3OS function in myofibroblasts upon TGFβ1 stimulation. Upon TGFβ1 stimulation, COL3A1 protein was decreased by DNM3OS silencing. miR-29a and miR-29b could directly bind to the DNM3OS and COL3A1 3' untranslated region (UTR)s to negatively regulate their expression, and by serving as a competing endogenous RNAs (ceRNA), DNM3OS competed with COL3A1 for miR-29a/29b binding, therefore counteracting miR-29a/29b-mediated COL3A1 suppression. The effect of DNM3OS silencing on ECM components and TGFβ1 downstream signaling was similar to that of the TGFβ1 inhibitor SB431542. miR-361 could target DNM3OS and TGFβ1; DNM3OS competed for miR-361 binding to counteract miR-361-mediated TGFβ1 suppression. In conclusion, we identified DNM3OS as a specifically-upregulated lncRNA upon TGFβ1 stimulation in PrSCs; by serving as a ceRNA for the miR-29a/29b cluster and miR-361, DNM3OS eliminated miRNA-mediated suppression of COL3A1 and TGFβ1, thereby promoting TGFβ1-induced PrSC transformation into myofibroblasts.
Pubmed ID: 31694982
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Software platform for complex network analysis and visualization. Used for visualization of molecular interaction networks and biological pathways and integrating these networks with annotations, gene expression profiles and other state data.
View all literature mentionsDatabase of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations and are derived from four sources: Genomic Context, High-throughput experiments, (Conserved) Coexpression, and previous knowledge. STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable. The database currently covers 5''214''234 proteins from 1133 organisms. (2013)
View all literature mentionsIntegrated database resource consisting of 16 main databases, broadly categorized into systems information, genomic information, and chemical information. In particular, gene catalogs in completely sequenced genomes are linked to higher-level systemic functions of cell, organism, and ecosystem. Analysis tools are also available. KEGG may be used as reference knowledge base for biological interpretation of large-scale datasets generated by sequencing and other high-throughput experimental technologies.
View all literature mentionsA commercial antibody supplier which supplies primary and secondary antibodies, biochemicals, proteins, peptides, lysates, immunoassays and other kits.
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