bims-lorfki 2020-07-26 papers

Issue of 2020‒07‒26
six papers selected by
Nikita Dewani
Max Delbrück Centre for Molecular Medicine

Cancer Cell Int. 2020 ;20 319

Identification of a three-long noncoding RNA prognostic model involved competitive endogenous RNA in kidney renal clear cell carcinoma.

Di Zhang, Song Zeng, Xiaopeng Hu.

Background: Long noncoding RNA (lncRNA) is generally identified as competing endogenous RNA (ceRNA) that plays a vital role in the pathogenesis of kidney renal clear cell carcinoma (KIRC), the most common subtype of renal cell carcinoma with poor prognosis and unclear pathogenesis. This study established a novel ceRNA network and thus identified a three-lncRNA prognostic model in KIRC patients.Methods: Differentially expressed genes (DEGs) were screened out from The Cancer Genome Atlas (TCGA) database. The lncATLAS was applied to determine the differentially expressed lncRNAs (DElncRNAs) of the cytoplasm. The miRcode, miRDB, miRTarBase, and TargetScan databases were utilized to predict the interactions of DElncRNAs, DEmiRNAs, and DEmRNAs. Cytoscape was used to construct the ceRNA network. Then, a lncRNA prognostic model (LPM) was constructed based on ceRNA-related lncRNA that was significantly related to overall survival (OS), and its predictive ability was evaluated. Moreover, an LPM-based nomogram model was constructed. The significantly different expression of genes in the LPM was validated in an independent clinical cohort (N = 21) by quantitative RT-PCR.
Results: A novel ceRNA regulatory network, including 73 lncRNAs, 8 miRNAs, and 21 mRNAs was constructed. Functional enrichment analysis indicated that integral components of membrane and PI3K-Akt signaling pathway represented the most significant GO terms and pathway, respectively. The LPM established based on three lncRNAs (MIAT, LINC00460, and LINC00443) of great prognostic value from the ceRNA network was proven to be independent of conventional clinical parameters to differentiate patients with low or high risk of poor survival, with the AUC of 1-, 5- and 10-year OS were 0.723, 0.714 and 0.826 respectively. Furthermore, the nomogram showed a better predictive value in KIRC patients than individual prognostic parameters. The expression of MIAT and LINC00460 was significantly upregulated in the KIRC samples, while the expression of LINC00443 was significantly downregulated compared with the adjacent normal samples in the clinical cohort, TCGA, and GTEx.
Conclusion: This LPM based on three-lncRNA could serve as an independent prognostic factor with a tremendous predictive ability for KIRC patients, and the identified novel ceRNA network may provide insight into the prognostic biomarkers and therapeutic targets of KIRC.

Keywords: KIRC; Nomogram; TCGA; ceRNA; lncRNA prognostic model

DOI: https://doi.org/10.1186/s12935-020-01423-4

Eur Rev Med Pharmacol Sci. 2020 Jul;pii: 21867. [Epub ahead of print]24(13): 7216

LncRNA SNHG16 promotes migration and invasion through suppression of CDKN1A in clear cell renal cell carcinoma.

S-B Liu, H-F Wang, Q-P Xie, G Li, L-B Zhou, B Hu.

Since this article has been suspected of research misconduct and the corresponding authors did not respond to our request to prove originality of data and figures, "LncRNA SNHG16 promotes migration and invasion through suppression of CDKN1A in clear cell renal cell carcinoma, by S.-B. Liu, H.-F. Wang, Q.-P. Xie, G. Li, L.-B. Zhou, B. Hu, published in Eur Rev Med Pharmacol Sci 2020; 24 (7): 3572-3578-DOI: 10.26355/eurrev_202004_20818-PMID: 32329831" has been withdrawn. The Publisher apologizes for any inconvenience this may cause. https://www.europeanreview.org/article/20818.

DOI: https://doi.org/10.26355/eurrev_202007_21867

Biosci Biotechnol Biochem. 2020 Jul 22. 1-13

LncRNA NEAT1 regulated inflammation and apoptosis in a rat model of sepsis-induced acute kidney injury via MiR-27a-3p/TAB3 axis.

Jiasheng Wang, Yong Chen, Ze Tang, Dabi Hu, Caoyuan Yao, Lei Yang.

This study explored the mechanism of NEAT1 in sepsis-induced AKI rats. Cecal ligation punctures (CLP)-induced AKI rats were injected with siRNA-NEAT1 lentivirus. Kidney histopathology and apoptosis were evaluated via hematoxylin-eosin and TUNEL staining, respectively. ELISA determined the levels of Blood urea nitrogen (BUN), serum creatinine (SCr), neutrophil gelatinase-associated lipocalin (NGAL), kidney injury molecule-1 (KIM-1), TNF-α, Interleukin (IL)-1β, and IL-6. Colorimetry measured malondialdehyde (MDA), superoxide dismutase (SOD) activities. qPCR analyzed NEAT1, miR-27a-3p, TAB3, Bcl-2, and Bax expressions. siNEAT1 reversed the promotive effect of CLP on kidney histopathological injury, and BUN, SCr, NGAL, KIM-1, TNF-α, IL-1β, IL-6, MDA, and Bax levels and apoptosis, but raised CLP-downregulated SOD and Bcl-2 levels. NEAT1 sponged miR-27a-3p which targeted TAB3. siNEAT1 upregulated miR-27a-3p and downregulated TAB3 expression. TAB3 overexpression reversed the inhibitory effect of siNEAT1 on the LPS-induced apoptosis of HK-2 cells. siNEAT1 alleviated sepsis-induced AKI in rats and LPS-induced sepsis of cells via miR-27a-3p/TAB3 axis.

Keywords: NEAT1; TAB3; acute kidney injury; inflammatory response; miR-27a-3p

DOI: https://doi.org/10.1080/09168451.2020.1792760

Biomed Res Int. 2020 ;2020 4830847

The ceRNA Network Has Potential Prognostic Value in Clear Cell Renal Cell Carcinoma: A Study Based on TCGA Database.

Haosheng Liu, Zhaowen Zhu, Jianxiong Fang, Tianqi Liu, Zhenhui Zhang, Chao Zhao, Xiaoyong Pu, Jiumin Liu.

Clear cell renal cell carcinoma (ccRCC) is a very common cancer in urology. Many evidences suggest that complex changed pathways take a nonnegligible part in the occurrence and development of ccRCC. Nevertheless, the underlying mechanism is not clear. In this study, the expression data between ccRCC and normal tissue samples in TCGA database were compared to distinguish differentially expressed genes (DEGs: mRNAs, miRNAs, and lncRNAs). Afterwards, we used GO enrichment and KEGG pathway enrichment analyses to explore the functions of these DEGs. We also found the correlation between three RNAs and created a competing endogenous RNA (ceRNA) network. Moreover, we used univariate Cox regression analysis to select DEGs that are connected with overall survival (OS) of ccRCC patients. We found 1652 mRNAs, 1534 lncRNAs, and 173 miRNAs that were distinguished in ccRCC compared with normal tissues. According to GO analysis, the maladjusted mRNAs are mainly concentrated in immune cell activation and kidney development, while according to KEGG, they are mainly concentrated in pathways related to cancer. A total of 5 mRNAs, 1 miRNA, and 4 lncRNAs were connected with patients' OS. In this article, a network of lncRNA-miRNA-mRNA was established; it is expected to be able to indicate possible molecular mechanisms for initial of ccRCC and provide a new viewpoint for diagnosis of ccRCC.

DOI: https://doi.org/10.1155/2020/4830847

Methods Mol Biol. 2020 ;2166 195-214

A Protocol for Non-biased Identification of RNAs Transferred Between Heterologous Mammalian Cell Types Using RNA Tagging, Cell Sorting, and Sequencing.

Sandipan Dasgupta, Jeffrey E Gerst.

Intercellular communication is a major hallmark of multicellular organisms and is responsible for coordinating cell and tissue differentiation, immune responses, synaptic transmission, and both paracrine and endocrine signaling, for example. Small molecules, peptides, and proteins have all been studied extensively as mediators of intercellular communication; however, RNAs have also been shown recently to transfer between cells. In mammalian cells, microRNAs, tRNAs, short noncoding RNAs, mRNA fragments, as well as full-length mRNAs have all been shown to transfer between cells either by exosomes or by membrane nanotubes. We have previously described nanotube-mediated cell-cell transfer of specific mRNAs between heterologous mammalian cell types cultured in vitro. Here, we describe a simple method for the unbiased and quantitative identification of the complete range of transferred mRNAs (i.e., the mRNA transferome) in one population of mammalian cells following co-culture with another population. After co-culture, the individual cell populations are sorted by magnetic bead-mediated cell sorting and the transferred RNAs are then identified by downstream analysis methods, such as RNA sequencing. Application of this technique not only allows for determination of the mRNA transferome, but can also reveal changes in the native transcriptome of a cell population after co-culture. This can indicate the effect that co-culture and intercellular transfer of mRNA have upon cell physiology.

Keywords: Co-culture; MACS; MS2; MS2-binding sequence; Magnetic sorting; Membrane nanotubes; RNA sequencing; RNA transfer; lncRNA; mRNA; miRNA; β-Actin

DOI: https://doi.org/10.1007/978-1-0716-0712-1_11

Cell Tissue Res. 2020 Jul 24.

LncRNA NEAT1 accelerates renal mesangial cell injury via modulating the miR-146b/TRAF6/NF-κB axis in lupus nephritis.

Li-Hua Zhang, Bin Xiao, Miao Zhong, Qiao Li, Jian-Ying Chen, Jie-Rou Huang, Hui Rao.

Although growing advances have been made in the regulation of lupus nephritis recently, lupus nephritis is still one of the major causes of death in SLE patients and the pathogenesis remains largely unknown. Therefore, exploring the pathological mechanisms is urgently needed for designing and developing novel therapeutic strategies for lupus nephritis. Human renal mesangial cells (HRMCs) were transfected with sh-NEAT1, miR-146b mimic, pcDNA-NEAT1, miR-146b inhibitor, or sh-TRAF6 to modify their expression. Lipopolysaccharide (LPS) was used to induce inflammatory injury. Cell viability was examined with CCK8. Apoptosis was determined by flow cytometry and Hoechst staining. qRT-PCR and western blot were used to analyze gene expression. The secretion of inflammatory cytokines was examined with ELISA. The bindings of NEAT1 with miR-146b and miR-146b with TRAF6 were tested by dual-luciferase reporter assay. NEAT1 was upregulated in LPS-treated HRMCs. Both the knockdown of NEAT1 and TRAF6 suppressed the LPS-induced inflammatory injury in HRMCs. NEAT1 directly targeted miR-146b to control miR-146b-mediated regulation of TRAF6 expression in HRMCs. NEAT1 promoted the expression of TRAF6 via targeting miR-146b to accelerate the LPS-mediated renal mesangial cell injury in HRMCs. Moreover, TRAF6 activated the NF-κB signaling in HRMCs. NEAT1 accelerated renal mesangial cell injury via directly targeting miR-146b, promoting the expression of TRAF6, and activating the NF-κB signaling in lupus nephritis. Our investigation elucidated novel pathological mechanisms and provided potential therapeutic targets for lupus nephritis.

Keywords: Inflammatory injury; LncRNA NEAT1; Lupus nephritis; miR-146b/TRAF6/NF-κB axis

DOI: https://doi.org/10.1007/s00441-020-03248-z