bims-lorfki Biomed News
on Long non-coding RNA functions in the kidney
Issue of 2021‒06‒13
two papers selected by
Nikita Dewani
Max Delbrück Centre for Molecular Medicine

  1. PLoS One. 2021 ;16(6): e0252761
      Long non-coding RNAs (lncRNAs) are important regulators in diabetic nephropathy. In this study, we investigated the potential role of lncRNA TUG1 in regulating endoplasmic reticulum stress (ERS)-mediated apoptosis in high glucose induced renal tubular epithelial cells. Human renal tubular epithelial cell line HK-2 was challenged with high glucose following transfection with lncRNA TUG1, miR-29c-3p mimics or inhibitor expression plasmid, either alone or in combination, for different experimental purposes. Potential binding effects between TUG1 and miR-29c-3p, as well as between miR-29c-3p and SIRT1 were verified. High glucose induced apoptosis and ERS in HK-2 cells, and significantly decreased TUG1 expression. Overexpressed TUG1 could prevent high glucose-induced apoptosis and alleviated ERS via negatively regulating miR-29c-3p. In contrast, miR-29c-3p increased HK-2 cells apoptosis and ERS upon high glucose-challenge. SIRT1 was a direct target gene of miR-29c-3p in HK-2 cells, which participated in the effects of miR-29c-3p on HK-2 cells. Mechanistically, TUG1 suppressed the expression of miR-29c-3p, thus counteracting its function in downregulating the level of SIRT1. TUG1 regulates miR-29c-3p/SIRT1 and subsequent ERS to relieve high glucose induced renal epithelial cells injury, and suggests a potential role for TUG1 as a promising diagnostic marker of diabetic nephropathy.
  2. PLoS One. 2021 ;16(6): e0252452
      INTRODUCTION: Kidney renal clear cell carcinoma (KIRC) has a high incidence globally, and its pathogenesis remains unclear. Long non-coding RNA (lncRNA), as a molecular sponge, participates in the regulation of competitive endogenous RNA (ceRNA). We aimed to construct a ceRNA network and screened out possible lncRNAs to predict KIRC prognosis.MATERIAL AND METHODS: All KIRC data were downloaded from the TCGA database and screened to find the possible target lncRNA; a ceRNA network was designed. Next, GO functional enrichment and KEGG pathway of differentially expressed mRNA related to lncRNA were performed. We used Kaplan-Meier curve analysis to predict the survival of these RNAs. We used Cox regression analysis to construct a model to predict KIRC prognosis.
    RESULTS: In the KIRC datasets, 1457 lncRNA, 54 miRNA and 2307 mRNA were screened out. The constructed ceRNA network contained 81 lncRNAs, nine miRNAs, and 17 mRNAs differentially expressed in KIRC. Survival analysis of all differentially expressed RNAs showed that 21 lncRNAs, four miRNAs, and two mRNAs were related to the overall survival rate. Cox regression analysis was performed again, and we found that eight lncRNAs were related to prognosis and used to construct predictive models. Three lnRNAs from independent samples were meaningful.
    CONCLUSION: The construction of ceRNA network was involved in the process and transfer of KIRC, and three lncRNAs may be potential targets for predicting KIRC prognosis.