Identification a lncRNA/circRNA-miRNA-mRNA ceRNA network in Nasopharyngeal Carcinoma by deep sequencing and bioinformatics analysis
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE227541 | GEO | 2023/12/31
REPOSITORIES: GEO
Similar Datasets
Project description:Identification a lncRNA/circRNA-miRNA-mRNA ceRNA network in Nasopharyngeal Carcinoma by deep sequencing and bioinformatics analysis
| PRJNA945480 | ENA
Project description:Background: Accumulating evidence indicates that non-coding RNAs (ncRNA), including long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs), can function as competitive endogenous RNAs (ceRNAs) by binding to microRNAs (miRNAs) and regulating host gene expression at the transcriptional or post-transcriptional level. Dysregulation in ceRNA network regulation has been implicated in the occurrence and development of cancer. However, the lncRNA/circRNA-miRNA-mRNA regulatory network is still lacking in nasopharyngeal carcinoma (NPC). Methods: Differentially expressed genes (DEGs) were obtained from our previous sequencing data and Gene Expression Omnibus (GEO). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) were used to explore the biological functions of these common DEGs. Through a series of bioinformatic analyses, the lncRNA/circRNA-miRNA-mRNA network was established. In additional, the external data GSE102349 was used to test the prognostic value of the hub mRNAs through the Kaplan-Meier method. Results: We successfully constructed a lncRNA/circRNA-miRNA-mRNA network in NPC, consisting of 16 lncRNAs, 6 miRNAs, 3 circRNAs and 10 mRNAs and found that three genes (TOP2A, ZWINT, TTK) were significantly associated with overall survival time (OS) in patients. Conclusion: The regulatory network revealed in this study may help comprehensively elucidate the ceRNA mechanisms driving NPC, and provide novel candidate biomarkers for evaluating the prognosis of NPC.
| S-EPMC10905391 | biostudies-literature
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.
| S-EPMC6755180 | biostudies-literature
Project description:Melanoma is an extremely malignant tumor with early metastasis and high mortality. Little is known about the process of by which melanoma occurs, as its mechanism is very complex and only limited data are available on its long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs). The purpose of this study was to screen out potential prognostic molecules and identify a ceRNA network related to the occurrence of melanoma. We screened 169 differentially expressed mRNAs (DEmRNAs) from E-MTAB-1862 and GSE3189; gene ontology (GO) enrichment analysis showed that these genes were closely related to the development of skin. In the protein-protein interaction network, we screened out a total of 19 hub genes. Furthermore, we predicted the microRNAs (miRNAs) that regulate hub genes using the miRWalk database and then intersected these with GSE35579, resulting in nine DEmiRNAs. We also predicted the lncRNAs that regulate the miRNAs using the LncBasev.2 database. According to the ceRNA hypothesis, and based on the intersection of the DElncRNAs with merged GTEx and TCGA data, we obtained 20 DElncRNAs. A total of four DEmRNAs, nine DEmiRNAs, and 20 DElncRNAs were included in the ceRNA network. Based on Cox stepwise regression and survival analysis, we identified five biomarkers, ZSCAN16-AS1, LINC00520, XIST, DTL, and let-7a-5p, and obtained risk scores. The results showed that most of the differentially expressed genes were related to epithelial-mesenchymal transition (EMT) in melanoma. Finally, we obtained a LINC00520/let-7a-5p/DTL molecular regulatory network. These results suggest that ceRNA networks have an important role in evaluating the prognosis of patients with melanoma and provide a new experimental basis for exploring the EMT process in the development of melanoma.
| S-EPMC8040875 | biostudies-literature
Project description:To determine ceRNA transcribed during the PBMCs, we have employed whole genome microarray expression profiling as a discovery platform to identify ceRNA expression in PBMCs donated by T1DM (type 1 diabetes mellitus) patients and healthy volunteers.
2020-06-25 | GSE133225 | GEO
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.
| S-EPMC8977626 | biostudies-literature
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.
| S-EPMC10375445 | biostudies-literature
Project description:We explored the whole expression profiles of transcriptome included miRNA, circRNA, lncRNA and mRNA in 5 pairs of LSCC and matched non-LSCC tissues by microarray The LSCC-related competing endogenous RNA (ceRNA) networks were constructed based on these microarray data.
2020-07-10 | GSE117001 | GEO
Project description:This study constructed a ceRNA network consisting of lncRNA–miRNA–mRNA based on lncRNA-mRNA and miRNA-mRNA interactions. Our objective was to investigate functional modules and hub differentially expressed genes, miRNAs and lncRNAs on different traits.
2022-05-18 | GSE159902 | GEO
Project description:We explored the whole expression profiles of transcriptome included miRNA, circRNA, lncRNA and mRNA in 5 pairs of LSCC and matched non-LSCC tissues by microarray The LSCC-related competing endogenous RNA (ceRNA) networks were constructed based on these microarray data.
2020-07-10 | GSE117005 | GEO