lncRNAs In ceRNA Network Research Articles

Construction of a potentially functional lncRNA-miRNA-mRNA network in sepsis by bioinformatics analysis.

Objective: Sepsis is a common disease in internal medicine, with a high incidence and dangerous condition. Due to the limited understanding of its pathogenesis, the prognosis is poor. The goal of this project is to screen potential biomarkers for the diagnosis of sepsis and to identify competitive endogenous RNA (ceRNA) networks associated with sepsis. Methods: The expression profiles of long non-coding RNAs (lncRNAs), microRNAs (miRNAs) and messenger RNAs (mRNAs) were derived from the Gene Expression Omnibus (GEO) dataset. The differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs) and mRNAs (DEmRNAs) were screened by bioinformatics analysis. DEmRNAs were analyzed by protein-protein interaction (PPI) network analysis, transcription factor enrichment analysis, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Set Enrichment Analysis (GSEA). After the prediction of the relevant database, the competitive ceRNA network is built in Cytoscape. The gene-drug interaction was predicted by DGIgb. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to confirm five lncRNAs from the ceRNA network. Results: Through Venn diagram analysis, we found that 57 DElncRNAs, 6 DEmiRNAs and 317 DEmRNAs expressed abnormally in patients with sepsis. GO analysis and KEGG pathway analysis showed that 789 GO terms and 36 KEGG pathways were enriched. Through intersection analysis and data mining, 5 key KEGG pathways and related core genes were revealed by GSEA. The PPI network consists of 247 nodes and 1,163 edges, and 50 hub genes are screened by the MCODE plug-in. In addition, there are 5 DElncRNAs, 6 DEmiRNAs and 28 DEmRNAs in the ceRNA network. Drug action analysis showed that 7 genes were predicted to be molecular targets of drugs. Five lncRNAs in ceRNA network are verified by qRT-PCR, and the results showed that the relative expression of five lncRNAs was significantly different between sepsis patients and healthy control subjects. Conclusion: A sepsis-specific ceRNA network has been effectively created, which is helpful to understand the interaction between lncRNAs, miRNAs and mRNAs. We discovered prospective sepsis peripheral blood indicators and proposed potential treatment medicines, providing new insights into the progression and development of sepsis.

Integrated Analysis of LncRNA-Mediated ceRNA Network in Calcific Aortic Valve Disease.

Background: The high morbidity and mortality of calcific aortic valve disease (CAVD) represents an unmet clinical need to investigate the molecular mechanisms involved. Evidence suggests that long non-coding RNAs (lncRNAs) can act as competitive endogenous RNAs (ceRNAs) by binding to microRNAs and regulating target genes in cardiovascular diseases. Nevertheless, the role of lncRNAs related ceRNA regulation in CAVD remains unclear. Methods: RNAseq data of human diseased aortic valves were downloaded from GEO data sets (GSE153555, GSE199718), and differentially expressed lncRNAs (DElncRNAs), mRNAs (DEmRNAs) between CAVD and non-calcific aortic valve tissues with limma R package. Gene Ontology (GO) annotation, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Set Enrichment analysis (GSEA) were performed with clusterProfiler and gesaplot2 R package. The pivotal microRNAs were predicted by three databases intersection including TargetScan, MiRwalk, miRDB according to the genes related to the crucial pathways. ENCORI was used to predict targeted lncRNAs of hub microRNAs. We constructed lncRNA-miRNA-mRNA ceRNA network with Cytoscape software. The lncRNAs in ceRNA network were verified by RT-qPCR in human 30 calcific and 20 noncalcified aortic valve tissues. Results: In total, 1739 DEmRNAs and 266 DElncRNAs were identified in CAVD. GO, KEGG pathway, GSEA annotations suggested that most of these genes are enriched in extracellular matrix (ECM)-reporter interaction pathways. The ceRNA networks associated with ECM-reporter interaction are constructed and related lncRNAs including H19, SNHG3 and ZNF436-AS1 were significant upregulated in human calcific aortic valve tissues, which might be potential therapeutic targets for CAVD. Conclusions: In this study, we proposed a novel lncRNA-miRNA-mRNA ceRNA network related to ECM-reporter interaction pathways, which potentially regulates CAVD progression.

Bioinformatics Analysis and Functional Verification of ADAMTS9-AS1/AS2 in Lung Adenocarcinoma.

Long non-coding RNAs (lncRNAs), as competitive endogenous RNAs (ceRNAs), play a critical role in biological processes of cancer. However, the roles of specific lncRNAs in ceRNA network of lung adenocarcinoma (LUAD) remains largely unclear. Herein, we identified the roles of lncRNA ADAMTS9-AS1/AS2 (ADAMTS-AS1/AS2) in lung adenocarcinoma by bioinformatics analyses and functional verification. First, differentially expressed genes ADAMTS9-AS1, ADAMTS9-AS2 and ADAMTS9 were screened out from GSE130779. Then the expression correlation of these three genes was analyzed. The results showed that ADAMTS9-AS1, ADAMTS9-AS2 and ADAMTS9 were down-regulated in LUAD, and were positively correlated with each other. After that, miRcode was used to find miR-150 which binds to ADAMTS9-AS1/ADAMTS9-AS2/ADAMTS9. Next, co-expression analysis and functional enrichment analyses were performed to further analyze differentially expressed genes. The results showed that the differentially expressed genes were mainly enriched in Beta3 integrin cell surface interactions and epithelial-to-mesenchymal transition. Finally, the cell functions of ADAMTS9-AS1 and ADAMTS9-AS2 in A549 and NCI-H1299 cell lines were verified. In vitro cell studies confirmed that ADAMTS9-AS1 and ADAMTS9-AS2 play an inhibitory role in LUAD cells.

Integrated analysis of lymphocyte infiltration-associated lncRNA for ovarian cancer via TCGA, GTEx and GEO datasets.

BackgroundAbnormal expression of long non-coding RNAs (lncRNA) play a significant role in the incidence and progression of high-grade serous ovarian cancer (HGSOC), which is a leading cause of mortality among gynecologic malignant tumor patients. In this study, our aim is to identify lncRNA-associated competing endogenous RNA (ceRNA ) axes that could define more reliable prognostic parameters of HGSOC, and to investigate the lncRNAs’ potential mechanism of in lymphocyte infiltration.MethodsThe RNA-seq and miRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) database; while for obtaining the differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs), we used edgeR, limma and DESeq2. After validating the RNA, miRNA and gene expressions, using integrated three RNA expression profiles (GSE18520, GSE27651, GSE54388) and miRNA profile (GSE47841) from the Gene Expression Omnibus (GEO) database, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analyses through ClusterProfiler. The prognostic value of these genes was determined with Kaplan–Meier survival analysis and Cox regression analysis. The ceRNA network was constructed using Cytoscape. The correlation between lncRNAs in ceRNA network and immune infiltrating cells was analyzed by using Tumor IMmune Estimation Resource (TIMER), and gene markers of tumor-infiltrating immune cells were identified using Spearman’s correlation after removing the influence of tumor purity.ResultsA total of 33 DELs (25 upregulated and eight downregulated), 134 DEMs (76 upregulated and 58 downregulated), and 1,612 DEGs (949 upregulated and 663 downregulated) were detected that could be positively correlated with overall survival (OS) of HGSOC. With the 1,612 analyzed genes, we constructed a ceRNA network, which indicated a pre-dominant involvement of the immune-related pathways. Furthermore, our data revealed that LINC00665 influenced the infiltration level of macrophages and dendritic cells (DCs). On the other hand, FTX and LINC00665, which may play their possible roles through the ceRNA axis, demonstrated a potential to inhibit Tregs and prevent T-cell exhaustion.ConclusionWe defined several prognostic biomarkers for the incidence and progression of HGSOC and constructed a network for ceRNA axes; among which three were indicated to have a positive correlation with lymphocyte infiltration, namely: FTX-hsa-miR-150-5p-STK11, LINC00665-hsa-miR449b-5p-VAV3 and LINC00665-hsa-miR449b-5p-RRAGD.