bims-lorfki Biomed News
on Long non-coding RNA functions in the kidney
Issue of 2020‒09‒13
two papers selected by
Nikita Dewani
Max Delbrück Centre for Molecular Medicine

  1. Med Sci Monit. 2020 Sep 08. 26 e925361
      BACKGROUND Long non-coding RNAs (lncRNAs) play vital roles in development of diabetic nephropathy (DN). The goal of our study was to investigate the functional roles of long intergenic noncoding RNA (lincRNA) 4930556M19Rik in DN. MATERIAL AND METHODS A DN cell model was constructed by exposing podocytes to high glucose (HG). A subcellular fraction assay was used to determine the level of 4930556M19Rik in the nucleus and cytoplasm of podocytes. Quantitative real-time polymerase chain reaction was used to evaluate expression of 4930556M19Rik and miR-27a-3p. Western blot assay was used to assessed levels of fibrosis-related proteins, podocin, and tissue inhibitor of metalloproteinase 3 (TIMP3). Flow cytometry analysis was performed to analyze cell apoptosis. Enzyme linked immunosorbent assay was used to examine secretion of inflammatory cytokines. Dual-luciferase reporter, RIP, and RNA pull-down assays were used to verify the relationship between miR-27a-3p and 4930556M19Rik or TIMP3. RESULTS 4930556M19Rik was significantly decreased in HG-stimulated podocytes and mainly enriched in the cytoplasm of podocytes. Elevation of 4930556M19Rik hampered HG-induced cell apoptosis, fibrosis, and inflammatory in podocytes. 4930556M19Rik sponged miR-27a-3p to negatively modulate miR-27a-3p expression. MiR-27a-3p overexpression reversed the impact of 4930556M19Rik mediated cell progression in HG-induced podocytes. Moreover, TIMP3 was the target for miR-27a-3p and miR-27a-3p inhibition slowed podocyte injury by targeting TIMP3. CONCLUSIONS 4930556M19Rik overexpression slowed HG-induced podocyte injury by downregulating miR-27a-3p and upregulating TIMP3.
  2. Biomed Res Int. 2020 ;2020 5843874
      Rhabdoid tumor of the kidney (RTK) is a rare and severely malignant tumor occurring in infancy and early childhood, with the overall outcomes remain poor. Neither gene regulatory networks nor biomarkers to predict the prognostic outcomes have been elucidated in RTK. In this study, RNA sequencing data were obtained to identify differentially expressed messenger RNAs (mRNAs), long noncoding RNAs (lncRNAs), and microRNAs (miRNAs) between RTK samples and normal samples. A total of 4217 mRNAs, 284 lncRNAs, and 286 miRNAs were screened out. Of those, 103 mRNAs, 80 lncRNAs, and 45 miRNAs were identified for a competing endogenous RNA (ceRNA) regulatory network, in which three significant modules were identified. A protein-protein interaction (PPI) network was constructed, and the hub-gene cluster consisted of four core genes (EXOSC2, PAK1IP1, WDR43, and POLR1D) was selected. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were also performed to analyze the functional characteristics of differentially expressed mRNAs. Subsequently, among 211 mRNAs, 8 lncRNAs, and 12 miRNAs associated with overall survival (OS) obtained by univariate Cox analysis, 5 mRNAs, 7 lncRNAs, and 7 miRNAs were identified and the risk score formulas were constructed correspondingly using the least absolute shrinkage and selection operator (LASSO) Cox regression model analysis. The log-rank tests and Kaplan-Meier analyses were performed to confirm the predictive value of the risk scores for OS in RTK patients. A genomic-clinicopathologic nomogram integrating the stage and risk scores based on RNAs was established and demonstrated high predictive accuracy and clinical value, which was validated through calibration curves, time-dependent receiver operating characteristic (ROC) curve analyses, and decision curve analysis (DCA). In conclusion, this study not only provided potential insights into the mechanisms underlying RTK, but also presented a practicable tool for predicting the prognosis in children with RTK.