Dataset Information

Integrated Analysis of lncRNA-miRNA-mRNA ceRNA Network Identified lncRNA EPB41L4A-AS1 as a Potential Biomarker in Non-small Cell Lung Cancer.

ABSTRACT: Background:Recent evidence has indicated that long non-coding RNAs (lncRNAs) can function as competing endogenous RNAs (ceRNAs) to modulate mRNAs expression by sponging microRNAs (miRNAs). However, the specific mechanism and function of lncRNA-miRNA-mRNA regulatory network in non-small cell lung cancer (NSCLC) remains unclear. Materials and Methods:We constructed a lung cancer related lncRNA-mRNA network (LCLMN) by integrating differentially expressed genes (DEGs) with miRNA-target interactions. We further performed topological feature analysis and random walk with restart (RWR) analysis of LCLMN. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed to investigate the target DEGs in LCLMN. The expression levels of significant lncRNAs in NSCLC were validated by quantitative real-time PCR (RT-qPCR). The prognostic value of the potential lncRNA was evaluated by Kaplan-Meier analysis. Results:A total of 33 lncRNA nodes, 580 mRNA nodes and 2105 edges were identified from LCLMN. Based on functional enrichment analysis and co-expression analysis, lncRNA EPB41L4A-AS1 was demonstrated to be correlated with the tumorigenesis of NSCLC. RT-qPCR results confirmed that the expression levels of lncRNA EPB41L4A-AS1 in NSCLC tissues were downregulated compared with adjacent non-cancerous tissues. Kaplan-Meier analysis showed that high expression of lncRNA EPB41L4A-AS1 was associated with better overall survival (OS) in NSCLC patients. Further investigation identified that high expression levels of COL4A3BP, CDS2, PURA, PDCD6IP, and TMEM245 were also correlated with better OS in NSCLC patients. Conclusion:In this study, we constructed a lncRNA-miRNA-mRNA ceRNA network to investigate potential prognostic biomarkers for NSCLC. We found that lncRNA EPB41L4A-AS1 could function as a regulator in the pathogenesis of NSCLC.

SUBMITTER: Wang M

PROVIDER: S-EPMC7530329 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Integrated Analysis of lncRNA-miRNA-mRNA ceRNA Network Identified lncRNA EPB41L4A-AS1 as a Potential Biomarker in Non-small Cell Lung Cancer.

Wang Meiqi M Zheng Sihan S Li Xi X Ding Yu Y Zhang Mingyan M Lin Lin L Xu Hao H Cheng Yue Y Zhang Xiaonan X Xu Hui H Li Shijun S

Frontiers in genetics 20200918

<h4>Background</h4>Recent evidence has indicated that long non-coding RNAs (lncRNAs) can function as competing endogenous RNAs (ceRNAs) to modulate mRNAs expression by sponging microRNAs (miRNAs). However, the specific mechanism and function of lncRNA-miRNA-mRNA regulatory network in non-small cell lung cancer (NSCLC) remains unclear.<h4>Materials and methods</h4>We constructed a lung cancer related lncRNA-mRNA network (LCLMN) by integrating differentially expressed genes (DEGs) with miRNA-targe ...[more]

PMID: 33193600

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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.

Dataset Information

Integrated Analysis of lncRNA-miRNA-mRNA ceRNA Network Identified lncRNA EPB41L4A-AS1 as a Potential Biomarker in Non-small Cell Lung Cancer.

Publications

Integrated Analysis of lncRNA-miRNA-mRNA ceRNA Network Identified lncRNA EPB41L4A-AS1 as a Potential Biomarker in Non-small Cell Lung Cancer.

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