The long noncoding RNA TUNAR modulates Wnt signaling and regulates human β-cell proliferation

Biochemical targets of the micropeptides encoded by lncRNAs

Long non-coding RNAs (lncRNAs) are a group of transcripts longer than 200 nucleotides, which play important roles in regulating various cellular activities by the action of the RNA itself. However, about 40% of lncRNAs in human cells are potentially translated into micropeptides (also referred to as microproteins) usually shorter than 100 amino acids. Thus, these lncRNAs may function by both RNAs directly and their encoded micropeptides. The micropeptides encoded by lncRNAs may regulate transcription, translation, protein phosphorylation or degradation, or subcellular membrane functions. This review attempts to summarize the biochemical targets of the micropeptides-encoded by lncRNAs, which function by both RNAs and micropeptides, and discuss their associations with various diseases and their potentials as drug targets.

T2DB: A Web Database for Long Non-Coding RNA Genes in Type II Diabetes

Type II diabetes (T2D) is a growing health problem worldwide due to increased levels of obesity and can lead to other life-threatening diseases, such as cardiovascular and kidney diseases. As the number of individuals diagnosed with T2D rises, there is an urgent need to understand the pathogenesis of the disease in order to prevent further harm to the body caused by elevated blood glucose levels. Recent advances in long non-coding RNA (lncRNA) research may provide insights into the pathogenesis of T2D. Although lncRNAs can be readily detected in RNA sequencing (RNA-seq) data, most published datasets of T2D patients compared to healthy donors focus only on protein-coding genes, leaving lncRNAs to be undiscovered and understudied. To address this knowledge gap, we performed a secondary analysis of published RNA-seq data of T2D patients and of patients with related health complications to systematically analyze the expression changes of lncRNA genes in relation to the protein-coding genes. Since immune cells play important roles in T2D, we conducted loss-of-function experiments to provide functional data on the T2D-related lncRNA USP30-AS1, using an in vitro model of pro-inflammatory macrophage activation. To facilitate lncRNA research in T2D, we developed a web application, T2DB, to provide a one-stop-shop for expression profiling of protein-coding and lncRNA genes in T2D patients compared to healthy donors or subjects without T2D.

Immune-Related LncRNAs as Prognostic Factors for Pediatric Rhabdoid Tumor of the Kidney

Background

Immune-related long noncoding RNAs (IrlncRNAs) are recognized as important prognostic factors in a variety of cancers, but thus far, their prognostic value in pediatric rhabdoid tumor of the kidney (pRTK) has not been reported. Here, we clarified the associations between IrlncRNAs and overall survival (OS) of pRTK patients and constructed a model to predict their prognosis.

Methods

We accessed RNA sequencing data and corresponding clinical data of pRTK from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. An expression profile of immune-related genes (Irgenes) and lncRNAs of pRTK was extracted from the RNA sequencing data. IrlncRNAs were defined by co-expression analysis of lncRNAs and Irgenes. The limma R package was used to identify differential expression IrlncRNAs. Univariate and multivariate Cox regression analyses were conducted to build a prognostic IrlncRNAs model. The performance of this prognostic model was validated by multimethods, like ROC curve analysis.

Results

A total of 1097 IrlncRNAs were defined. Univariate Cox regression analysis identified 7 IrlncRNAs (AC004791.2, AP003068.23, RP11-54O7.14, RP11-680F8.1, TBC1D3P1-DHX40P1, TUNAR, and XXbac-BPG308K3.5) and were significantly associated with OS. Multivariate regression analysis constructed the best prognostic model based on the expression of AC004791.2, AP003068.23, RP11-54O7.14, TBC1D3P1-DHX40P1, and TUNAR. According to the prognostic model, a risk score of each patient was calculated, and patients were divided into high-risk and low-risk groups accordingly. The survival time of low-risk patients was significantly better than high-risk patients (p < 0.001). Univariate (hazard ratio 1.098, 95% confidence interval 1.048-1.149, p value <0.001) and multivariate (hazard ratio 1.095, 95% confidence interval 1.043-1.150, p value <0.001) analyses confirmed that the prognostic model was reliable and independent in prediction of OS. Time-dependent ROC analysis showed that 1-year survival AUC of prognostic model, stage, age, and sex was 0.824, 0.673, 0.531, and 0.495, respectively, which suggested that the prognostic model was the best predictor of survival in pRTK patients.

Conclusions

The prognostic model based on 5 IrlncRNAs was robust and could better predict the survival of pRTK than other clinical factors. Additionally, the mechanism of regulation and action of prognosis-associated lncRNAs could provide new avenues for basic research to explore the mechanism of tumor initiation and development in order to prevent and treat pRTK.

Is type 2 diabetes mellitus another intercellular junction-related disorder?

Type 2 diabetes mellitus (T2D) is nowadays a worldwide epidemic and has become a major challenge for health systems around the world. It is a multifactorial disorder, characterized by a chronic state of hyperglycemia caused by defects in the production as well as in the peripheral action of insulin. This minireview highlights the experimental and clinical evidence that supports the novel idea that intercellular junctions (IJs)-mediated cell-cell contacts play a role in the pathogenesis of T2D. It focuses on IJs repercussion for endocrine pancreas, intestinal barrier, and kidney dysfunctions that contribute to the onset and evolution of this metabolic disorder.

The possible role of long non-coding RNAs in recurrent miscarriage

Recurrent miscarriage (RM) is a complicated disease in reproductive medicine that impacts many families. Currently, the etiology of RM is thought to include chromosome abnormalities, reproductive tract malformations, autoimmune dysfunction, infection, and environmental factors. However, the underlying mechanisms of RM remain unknown. At present, research on long non-coding RNAs (lncRNAs) is rapidly emerging and becoming a hot research topic in epigenetic studies. Recent studies revealed that lncRNAs are strongly linked to RM and play a crucial role in epigenetic, cell cycle, cell differentiation regulation, and other life activities. This article mainly reviews the difference in lncRNA expression in patients with RM and regulation of susceptibility, endometrial receptivity, and the maternal-fetal interface. Meanwhile, the correlation between lncRNAs and RM is expounded, which provides new insights for the early diagnosis and treatment of RM.

Insights from Dysregulated mRNA Expression Profile of β-Cells in Response to Proinflammatory Cytokines

Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease that is characterized by autoimmunity and its mediated β-cell damage. Chronic exposure of β-cells to proinflammatory cytokines is known to regulate the expression of many genes, subsequently resulting in the impairment of some signaling pathways involved with insulin production and secretion and/or β-cell apoptosis. In our study, RNA sequencing technology was applied to identify differentially expressed mRNAs in MIN6 cells treated with a mix of cytokines, including IL-1β, TNF-α, and IFN-γ. The results showed 809 upregulated and 946 downregulated protein-coding mRNAs in MIN6 cells upon the stimulation of cytokines. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) biological pathway analyses were performed to predict the functions of dysregulated genes. The networks of circRNA-mRNA were constructed between differentially mRNAs and dysregulated expressed circRNAs in our previous study. In addition, we selected 8 dysregulated mRNAs for further validation by quantitative real-time PCR. The RNA sequencing data showed 809 upregulated and 946 downregulated protein-coding mRNAs. GO analysis showed that the top 10 significant “biological processes,” “cellular components,” and “molecular functions” for upregulated mRNAs include “immune system process,” “inflammatory response,” and “innate immune response” and the top 10 for downregulated mRNAs include “cell cycle,” “mitotic cytokinesis,” and “cytoplasm.” KEGG analysis showed that these differentially expressed genes were involved with “antigen processing and presentation,” “TNF signaling pathway” and “type 1 diabetes,” “cell cycle,” “necroptosis,” and “Rap1 signaling pathway.” We also constructed the networks of differentially expressed circRNAs and mRNAs. We observed that upregulated circRNA 006029 and downregulated circRNA 000286 and 017277 were associated with the vast majority of selected dysregulated mRNAs, while circRNA 013053 was only related to the protein-coding gene, Slc7a2. To the summary, these data indicated that differentially expressed mRNAs may play key or partial roles in cytokine-mediated β-cell dysfunction and gave us the hint that circRNAs might regulate mRNAs, thereby contributing to the development of T1DM. The current study provided a systematic perspective on the potential functions and possible regulatory mechanisms of mRNAs in proinflammatory cytokine-induced β-cell destruction.