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Construction of a long non?coding RNA-mediated competitive endogenous RNA network reveals global patterns and regulatory markers in gestational diabetes.

ABSTRACT: Gestational diabetes mellitus (GDM) is a common disease affecting pregnant women. Recent studies have suggested that competing endogenous RNAs (ceRNAs), which compete with long non?coding RNAs (lncRNAs) for microRNA (miRNA or miR) binding and indirectly regulate miRNA targets through competing interactions, play a critical role in disease. In this study, we present a computationally integrated approach with which to construct a lncRNA?mediated ceRNA network (LCEN) in GDM by integrating RNA interactions and expression data. lncRNAs exhibited specific features and played critical roles in GDM?associated LCEN. The construction of a global functional score profile revealed that ceRNAs had a high activity in GDM. We extracted several ceRNA modules and demonstrated that these modules had increased close interactions. We further discovered that these ceRNA modules may be utilized as specific and effective circulating biomarkers for GDM. Finally, functional analyses demonstrated that the GDM?associated ceRNAs participated in the regulation of irisin and the thyroid hormone signaling pathway. It was suggested that there were close associations between the thyroid hormone and GDM. Collectively, ceRNAs may accelerate biomarker discovery and therapeutic development in GDM.

SUBMITTER: Leng L

PROVIDER: S-EPMC6317690 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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Construction of a long non‑coding RNA-mediated competitive endogenous RNA network reveals global patterns and regulatory markers in gestational diabetes.

Leng Lei L Zhang Chengwei C Ren Lihong L Li Qiang Q

International journal of molecular medicine 20181212 2

Gestational diabetes mellitus (GDM) is a common disease affecting pregnant women. Recent studies have suggested that competing endogenous RNAs (ceRNAs), which compete with long non‑coding RNAs (lncRNAs) for microRNA (miRNA or miR) binding and indirectly regulate miRNA targets through competing interactions, play a critical role in disease. In this study, we present a computationally integrated approach with which to construct a lncRNA‑mediated ceRNA network (LCEN) in GDM by integrating RNA inter ...[more]

PMID: 30569156

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Project description:BackgroundGlioblastoma is the most common primary malignant brain tumor. Because of the limited understanding of its pathogenesis, the prognosis of glioblastoma remains poor. This study was conducted to explore potential competing endogenous RNA (ceRNA) network chains and biomarkers in glioblastoma by performing integrated bioinformatics analysis.MethodsTranscriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma and normal tissues. Biological pathways potentially associated with the differentially expressed genes were explored by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan-Meier curve method. A ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by quantitative reverse-transcription polymerase chain reaction analysis and by determining the Pearson correlation coefficient. Additionally, an MTS assay and the wound-healing and transwell assays were performed to evaluate the effects of complement C1s (C1S) on the viability and migration and invasion abilities of glioblastoma cells, respectively.ResultsWe detected 2842 differentially expressed (DE) mRNAs, 2577 DE long non-coding RNAs (lncRNAs), and 309 DE microRNAs (miRNAs) that were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DE mRNAs and one DE lncRNA were correlated with overall survival (p < 0.05). C1S was significantly correlated with overall survival (p= 0.015). In functional assays, knockdown of C1S inhibited the proliferation and invasion of glioblastoma cell lines.ConclusionsWe established four ceRNA networks that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis is a potential marker and therapeutic target for glioblastoma. Knockdown of C1S inhibited the proliferation, migration, and invasion of glioblastoma cells. These findings clarify the role of the ceRNA regulatory network in glioblastoma and provide a foundation for further research.

Project description:Osteoporosis (OP) is a common bone disease of old age resulting from the imbalance between bone resorption and bone formation. CircRNAs are a class of endogenous non-coding RNAs (ncRNAs) involved in gene regulation and may play important roles in the development of OP. Here, we aimed to discover the OP‑related circRNA-miRNA-mRNA (ceRNA) network and the potential mechanisms. Six microarray datasets were obtained from the GEO database and the OP‑related differentially expressed genes (DEGs), circRNAs (DECs), and miRNAs (DEMs) were screened out from these datasets. Then, combined with the prediction of the relationships between DEGs, DEMs, and DECs, a ceRNA network containing 7 target circRNAs, 5 target miRNAs, and 38 target genes was constructed. Then the RNA-seq verification by using total RNAs isolated from the femurs of normal and ovariectomized Wistar rats indicated that MFAP5, CAMK2A, and RGS4 in the ceRNA network were closely associated with osteoporosis. Function enrichment analysis indicated that the target circRNAs, miRNAs, and genes were involved in the process of MAPK cascade, hormone stimulus, cadherin binding, rRNA methyltransferase, PI3K-Akt signaling pathway, and Vitamin digestion and absorption, etc. Then a circRNA-miRNA-hub gene subnetwork was constructed and the qRT-PCR analysis of human bone tissues from the femoral head was used to confirm that the transcription of hsa_circR_0028877, hsa_circR_0082916, DIRAS2, CAMK2A, and MAPK4 showed a significant correlation with osteogenic genes. Besides, the two axes of hsa_circR_0028877/hsa-miR-1273f/CAMK2A and hsa_circR_0028877/hsa-miR-1273f/DIRAS2 conformed to be closely associated with OP. Additionally, by constructing a drug-target gene network, RKI-1447, FRAX486, Hyaluronic, and Fostamatinib were identified as therapeutic options for OP. Our study revealed the potential links between circRNAs, miRNAs, and mRNAs in OP, suggesting that the ceRNA mechanism might contribute to the occurrence of OP.

Dataset Information

Construction of a long non?coding RNA-mediated competitive endogenous RNA network reveals global patterns and regulatory markers in gestational diabetes.

Publications

Construction of a long non‑coding RNA-mediated competitive endogenous RNA network reveals global patterns and regulatory markers in gestational diabetes.

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