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An lncRNA?miRNA?mRNA ceRNA network for adipocyte differentiation from human adipose?derived stem cells.

ABSTRACT: Human adipose tissue?derived stromal stem cells (HASCs) represent a promising regenerative resource for breast reconstruction and augmentation. However, the mechanisms involved in inducing its adipogenic differentiation remain to be fully elucidated. The present study aimed to comprehensively investigate the expression changes in mRNAs, microRNAs (miRNAs) and long non?coding (lnc)RNAs during the adipogenic differentiation of HASCs, and screen crucial lncRNA?miRNA?mRNA interaction axes using microarray datasets GSE57593, GSE25715 and GSE61302 collected from the Gene Expression Omnibus database. Following pretreatment, differentially expressed genes (DEGs), miRNAs (DE?miRNAs) or lncRNAs (DE?lncRNAs) between undifferentiated and differentiated HASCs were identified using the Linear Models for Microarray data method. A protein?protein interaction (PPI) network was constructed for the DEGs based on protein databases, followed by module analysis. The 'lncRNA?miRNA?mRNA' competing endogenous RNA (ceRNA) network was constructed based on the interactions between miRNAs and mRNAs, lncRNAs and miRNAs predicted by the miRWalk and lnCeDB databases. The underlying functions of mRNAs were predicted using the clusterProfiler package. In the present study, 905 DEGs, 36 DE?miRNAs and 577 DE?lncRNAs were screened between undifferentiated HASCs and differentiated adipocyte cells. PPI network analysis demonstrated that LEP may be a hub gene, which was also enriched in significant module 5. LEP was predicted to be involved in the Janus kinase?signal transducer and activator of transcription signaling pathway, and the regulation of inflammatory response. The upregulation of LEP was regulated by downregulated hsa?miRNA (miR)?130b?5p and hsa?miR?23a?5p (or hsa?miR?302d?3p). These miRNAs also respectively interacted with RP11?552F3.9 (or RP11?15A1.7), ultimately forming the ceRNA axes. In conclusion, the present study revealed that the RP11?552F3.9 (RP11?15A1.7)?hsa?miR?130b?5p/hsa?miR?23a?5p (hsa?miR?302d?3p)?LEP interaction axes may be crucial for inducing the adipogenic differentiation of HASCs via involvement in inflammation.

SUBMITTER: Guo Z

PROVIDER: S-EPMC6471198 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature

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An lncRNA‑miRNA‑mRNA ceRNA network for adipocyte differentiation from human adipose‑derived stem cells.

Guo Zhen Z Cao Yali Y

Molecular medicine reports 20190321 5

Human adipose tissue‑derived stromal stem cells (HASCs) represent a promising regenerative resource for breast reconstruction and augmentation. However, the mechanisms involved in inducing its adipogenic differentiation remain to be fully elucidated. The present study aimed to comprehensively investigate the expression changes in mRNAs, microRNAs (miRNAs) and long non‑coding (lnc)RNAs during the adipogenic differentiation of HASCs, and screen crucial lncRNA‑miRNA‑mRNA interaction axes using micr ...[more]

PMID: 30896814

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Project description:BackgroundInjection of adipose-derived stem cells (ASCs) is a promising treatment for facial contour deformities. However, its treatment mechanisms remain largely unknown. The study aimed to explain the molecular mechanisms of adipogenic differentiation from ASCs based on the roles of long noncoding RNAs (lncRNAs).MethodsDatasets of mRNA-lncRNA (GSE113253) and miRNA (GSE72429) expression profiling were collected from Gene Expression Omnibus database. The differentially expressed genes (DEGs), lncRNAs (DELs) and miRNAs (DEMs) between undifferentiated and adipocyte differentiated human ASCs were identified using the Linear Models for Microarray Data method. DELs related co-expression and competing endogenous RNA (ceRNA) networks were constructed. Protein-protein interaction (PPI) analysis was performed to screen crucial target genes.ResultsA total of 748 DEGs, 17 DELs and 51 DEMs were identified. A total of 13 DELs and 279 DEGs with Pearson correlation coefficients > 0.9 and p-value < 0.01 were selected to construct the co-expression network. A total of 151 interaction pairs among 112 nodes (10 DEMs; eight DELs; 94 DEGs) were obtained to construct the ceRNA network. By comparing the lncRNAs and mRNAs in two networks, five lncRNAs (SNHG9, LINC02202, UBAC2-AS1, PTCSC3 and myocardial infarction associated transcript (MIAT)) and 32 genes (i.e., such as phosphoinositide-3-kinase regulatory subunit 1 (PIK3R1), protein tyrosine phosphatase receptor type B (PTPRB)) were found to be shared. PPI analysis demonstrated PIK3R1 , forkhead box O1 (FOXO1; a transcription factor) and estrogen receptor 1 (ESR1) were hub genes, which could be regulated by the miRNAs that interacted with the above five lncRNAs, such as LINC02202-miR-136-5p-PIK3R1, LINC02202-miR-381-3p-FOXO1 and MIAT-miR-18a-5p-ESR1. LINC02202 also could directly co-express with PIK3R1. Furthermore, PTPRB was predicted to be modulated by co-expression with LINC01119.ConclusionMIAT, LINC02202 and LINC01119 may be potentially important, new lncRNAs associated with adipogenic differentiation of ASCs. They may be involved in adipogenesis by acting as a ceRNA or co-expressing with their targets.

Project description:Long non-coding RNAs (lncRNAs) are ncRNA transcripts >200 nucleotides that are important genetic regulators. LncRNAs can directly regulate mRNA through a lncRNA-mRNA regulatory mode and can also regulate mRNA through competitive binding to micro (mi)RNA, which is generally known as the competitive endogenous RNA (ceRNA) network. The present study evaluated the functional roles and regulatory networks of lncRNAs in chronic glomerulonephritis (CGN). The proliferative ability of mouse glomerular mesangial cells (GMCs) induced by different concentrations of lipopolysaccharide (LPS) was assessed using the Cell Counting Kit-8 assay, and RNA sequencing (RNA-seq) was performed to identify differentially expressed lncRNAs in LPS-induced GMCs. Based on the sequencing results, six lncRNAs were selected for validation using reverse transcription-quantitative PCR (RT-qPCR). Furthermore, the lncRNA-mRNA regulatory network and the lncRNA-miRNA-mRNA ceRNA network were constructed to assess the role and mechanism of CGN-related lncRNAs. To elucidate the biological functions of lncRNAs, Gene Ontology (GO) biological process term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on all mRNAs involved in the lncRNA-mRNA regulatory network and in the ceRNA network. A total of 1,532 differentially expressed lncRNAs, including 594 upregulated lncRNAs and 938 downregulated lncRNAs, were identified using RNA-seq. The results of RT-qPCR validation were consistent with RNA-seq results. An lncRNA-mRNA regulatory network, including 236 lncRNAs and 556 mRNAs, and a ceRNA network, including 6 lncRNAs, 18 miRNAs and 419 mRNAs, were successfully constructed. The GO biological process term enrichment and KEGG pathway enrichment analyses demonstrated that those lncRNAs were often related to inflammatory response and substance metabolism. The present study identified key CGN-related lncRNAs in LPS-induced GMCs, and further demonstrated a global view of the lncRNA-mRNA regulatory network and ceRNA network involved in CGN. These results offered novel insights into the roles of lncRNAs in the pathogenesis of CGN and identified potential diagnostic biomarkers.

Project description:Accumulating evidence has indicated that noncoding RNAs are involved in intervertebral disc degeneration (IDD); however, the competing endogenous RNA (ceRNA)‑mediated regulatory mechanisms in IDD remain rarely reported. The present study aimed to comprehensively investigate the alterations in expression levels of circular RNA (circRNA), long noncoding RNA (lncRNA), microRNA (miRNA/miR) and mRNA in the nucleus pulposus (NP) of patients with IDD. In addition, crucial lncRNA/circRNA‑miRNA‑mRNA ceRNA interaction axes were screened using the GSE67567 microarray dataset obtained from the Gene Expression Omnibus database. After data preprocessing, differentially expressed circRNAs (DECs), lncRNAs (DELs), miRNAs (DEMs) or genes (DEGs) between IDD and normal controls were identified using the Linear Models for Microarray data method. A protein‑protein interaction (PPI) network was constructed for DEGs based on protein databases, followed by module analysis. The ceRNA network was constructed based on the interaction between miRNAs and mRNAs, and lncRNAs/circRNAs and miRNAs. The underlying functions of mRNAs were predicted using the Database for Annotation, Visualization and Integrated Discovery database. The present study identified 636 DECs, 115 DELs, 84 DEMs and 1,040 DEGs between patients with IDD and control individuals. PPI network analysis demonstrated that Fos proto‑oncogene, AP‑1 transcription factor subunit (FOS), mitogen‑activated protein kinase 1 (MAPK1), hypoxia inducible factor 1 subunit α (HIF1A) and transforming growth factor β1 (TGFB1) were hub genes and enriched in modules. Metastasis‑associated lung adenocarcinoma transcript 1 (MALAT1)/hsa_circRNA_102348‑hsa‑miR‑185‑5p‑TGFB1/FOS, MALAT1‑hsa‑miR‑155‑5p‑HIF1A, hsa_circRNA_102399‑hsa‑miR‑302a‑3p‑HIF1A, MALAT1‑hsa‑miR‑519d‑3p‑MAPK1 and hsa_circRNA_100086‑hsa‑miR‑509‑3p‑MAPK1 ceRNA axes were obtained by constructing the ceRNA networks. In conclusion, these identified ceRNA interaction axes may be crucial targets for the treatment of IDD.

Project description:Background: Hepatocellular carcinoma (HCC) accounts for the majority of liver cancer, with the incidence and mortality rates increasing every year. Despite the improvement of clinical management, substantial challenges remain due to its high recurrence rates and short survival period. This study aimed to identify potential diagnostic and prognostic biomarkers in HCC through bioinformatic analysis. Methods: Datasets from GEO and TCGA databases were used for the bioinformatic analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were carried out by WebGestalt website and clusterProfiler package of R. The STRING database and Cytoscape software were used to establish the protein-protein interaction (PPI) network. The GEPIA website was used to perform expression analyses of the genes. The miRDB, miRWalk, and TargetScan were employed to predict miRNAs and the expression levels of the predicted miRNAs were explored via OncomiR database. LncRNAs were predicted in the StarBase and LncBase while circRNA prediction was performed by the circBank. ROC curve analysis and Kaplan-Meier (KM) survival analysis were performed to evaluate the diagnostic and prognostic value of the gene expression, respectively. Results: A total of 327 upregulated and 422 downregulated overlapping DEGs were identified between HCC tissues and noncancerous liver tissues. The PPI network was constructed with 89 nodes and 178 edges and eight hub genes were selected to predict upstream miRNAs and ceRNAs. A lncRNA/circRNA-miRNA-mRNA network was successfully constructed based on the ceRNA hypothesis, including five lncRNAs (DLGAP1-AS1, GAS5, LINC00665, TYMSOS, and ZFAS1), six circRNAs (hsa_circ_0003209, hsa_circ_0008128, hsa_circ_0020396, hsa_circ_0030051, hsa_circ_0034049, and hsa_circ_0082333), eight miRNAs (hsa-miR-150-5p, hsa-miR-19b-3p, hsa-miR-23b-3p, hsa-miR-26a-5p, hsa-miR-651-5p, hsa-miR-10a-5p, hsa-miR-214-5p and hsa-miR-486-5p), and five mRNAs (CDC6, GINS1, MCM4, MCM6, and MCM7). The ceRNA network can promote HCC progression via cell cycle, DNA replication, and other pathways. Clinical diagnostic and survival analyses demonstrated that the ZFAS1/hsa-miR-150-5p/GINS1 ceRNA regulatory axis had a high diagnostic and prognostic value. Conclusion: These results revealed that cell cycle and DNA replication pathway could be potential pathways to participate in HCC development. The ceRNA network is expected to provide potential biomarkers and therapeutic targets for HCC management, especially the ZFAS1/hsa-miR-150-5p/GINS1 regulatory axis.

Dataset Information

An lncRNA?miRNA?mRNA ceRNA network for adipocyte differentiation from human adipose?derived stem cells.

Publications

An lncRNA‑miRNA‑mRNA ceRNA network for adipocyte differentiation from human adipose‑derived stem cells.

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