VECTOR: An Integrated Correlation Network Database for the Identification of CeRNA Axes in Uveal Melanoma

Uveal melanoma (UM) is the most common primary intraocular malignant tumor in adults and, although its genetic background has been extensively studied, little is known about the contribution of non-coding RNAs (ncRNAs) to its pathogenesis. Indeed, its competitive endogenous RNA (ceRNA) regulatory network comprising microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and mRNAs has been insufficiently explored. Thanks to UM findings from The Cancer Genome Atlas (TCGA), it is now possible to statistically elaborate these data to identify the expression relationships among RNAs and correlative interaction data. In the present work, we propose the VECTOR (uVeal mElanoma Correlation NeTwORk) database, an interactive tool that identifies and visualizes the relationships among RNA molecules, based on the ceRNA model. The VECTOR database contains: i) the TCGA-derived expression correlation values of miRNA-mRNA, miRNA-lncRNA and lncRNA-mRNA pairs combined with predicted or validated RNA-RNA interactions; ii) data of sense-antisense sequence overlapping; iii) correlation values of Transcription Factor (TF)-miRNA, TF-lncRNA, and TF-mRNA pairs associated with ChiPseq data; iv) expression data of miRNAs, lncRNAs and mRNAs both in UM and physiological tissues. The VECTOR web interface can be queried, by inputting the gene name, to retrieve all the information about RNA signaling and visualize this as a graph. Finally, VECTOR provides a very detailed picture of ceRNA networks in UM and could be a very useful tool for researchers studying RNA signaling in UM. The web version of Vector is freely available at the URL reported at the end of the Introduction.

RNA Signaling in Pulmonary Arterial Hypertension—A Double-Stranded Sword

Recognition of and response to pathogens and tissue injury is driven by the innate immune system via activation of pattern recognition receptors. One of the many patterns recognized is RNA and, while several receptors bind RNA, Toll-like receptor 3 (TLR3) is well placed for initial recognition of RNA molecules due to its localization within the endosome. There is a growing body of work describing a role for TLR3 in maintenance of vascular homeostasis. For example, TLR3 deficiency has been shown to play repair and remodeling roles in the systemic vasculature and in lung parenchyma. A hallmark of pulmonary arterial hypertension (PAH) is pulmonary vascular remodeling, yet drivers and triggers of this remodeling remain incompletely understood. Based on its role in the systemic vasculature, our group discovered reduced endothelial TLR3 expression in PAH and revealed a protective role for a TLR3 agonist in rodent models of pulmonary hypertension. This review will provide an overview of RNA signaling in the vasculature and how it relates to PAH pathobiology, including whether targeting double-stranded RNA signaling is a potential treatment option for PAH.

miR-140 Promotes Expression of long non-coding RNA NEAT1 in Adipogenesis

More than 40% of the US population are clinically obese, and suffer from the metabolic syndrome and increased risk of post-menopausal estrogen-receptor-positive breast cancer. Adipocytes are the primary component of adipose tissue, and are formed through adipogenesis from precursor mesenchymal stem cells. While the major molecular pathways of adipogenesis are understood, little is known about the non-coding RNA signaling networks involved in adipogenesis. Using adipocyte-derived stem cells (ADSCs) isolated from wild-type and miR-140 knock-out mice, we identify a novel miR-140/long non-coding RNA (lncRNA) NEAT1 signaling network necessary for adipogenesis. miR-140 knock-out ADSCs have dramatically decreased adipogenic capabilities associated with down-regulation of NEAT1 expression. We identified a miR-140 binding site in NEAT1 and found that mature miR-140 in the nucleus can physically interact with NEAT1 leading to increased NEAT1 expression. We demonstrated that re-expression of NEAT1 in miR-140 knock-out ADSCs is sufficient to restore their ability to undergo differentiation. Our results reveal an exciting new non-coding RNA signaling network that regulates adipogenesis, and is a potential new target in prevention or treatment of obesity.