Dataset Information

Comprehensive analysis of lncRNA-associated competing endogenous RNA network in tongue squamous cell carcinoma.

ABSTRACT: Background:Increasing evidence has demonstrated that long non-coding RNAs (lncRNAs) play an important role in the competitive endogenous RNA (ceRNA) networks in that they regulate protein-coding gene expression by sponging microRNAs (miRNAs). However, the understanding of the ceRNA network in tongue squamous cell carcinoma (TSCC) remains limited. Methods:Expression profile data regarding mRNAs, miRNAs and lncRNAs as well as clinical information on 122 TSCC tissues and 15 normal controls from The Cancer Genome Atlas (TCGA) database were collected. We used the edgR package to identify differentially expressed mRNAs (DEmRNAs), lncRNAs (DElncRNAs) and miRNAs (DEmiRNAs) between TSCC samples and normal samples. In order to explore the functions of DEmRNAs, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis was performed. Subsequently, a ceRNA network was established based on the identified DElncRNAs-DEmiRNAs and DEmiRNAs-DEmRNAs interactions. The RNAs within the ceRNA network were analyzed for their correlation with overall disease survival. Finally, lncRNAs were specifically analyzed for their correlation with clinical features in the included TSCC patient samples. Results:A total of 1867 mRNAs, 828 lncRNAs and 81 miRNAs were identified as differentially expressed in TSCC tissues (-log 2fold change- ? 2; adjusted P value <0.01). The resulting ceRNA network included 16 mRNAs, 56 lncRNAs and 6 miRNAs. Ten out of the 56 lncRNAs were found to be associated with the overall survival in TSCC patients (P < 0.05); 10 lncRNAs were correlated with TSCC progression (P < 0.05). Conclusion:Our study deepens the understanding of ceRNA network regulatory mechanisms in TSCC. Furthermore, we identified ten lncRNAs (PART1, LINC00261, AL163952.1, C2orf48, FAM87A, LINC00052, LINC00472, STEAP3-AS1, TSPEAR-AS1 and ERVH48-1) as novel, potential prognostic biomarkers and therapeutic targets for TSCC.

SUBMITTER: Zhang S

PROVIDER: S-EPMC6368841 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Comprehensive analysis of lncRNA-associated competing endogenous RNA network in tongue squamous cell carcinoma.

Zhang Shusen S Cao Ruoyan R Li Qiulan Q Yao Mianfeng M Chen Yu Y Zhou Hongbo H

PeerJ 20190206

<h4>Background</h4>Increasing evidence has demonstrated that long non-coding RNAs (lncRNAs) play an important role in the competitive endogenous RNA (ceRNA) networks in that they regulate protein-coding gene expression by sponging microRNAs (miRNAs). However, the understanding of the ceRNA network in tongue squamous cell carcinoma (TSCC) remains limited.<h4>Methods</h4>Expression profile data regarding mRNAs, miRNAs and lncRNAs as well as clinical information on 122 TSCC tissues and 15 normal co ...[more]

PMID: 30755833

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Project description:BackgroundPulpitis is a common inflammatory disease that affects dental pulp. It is important to understand the molecular signals of inflammation and repair associated with this process. Increasing evidence has revealed that long noncoding RNAs (lncRNAs), via competitively sponging microRNAs (miRNAs), can act as competing endogenous RNAs (ceRNAs) to regulate inflammation and reparative responses. The aim of this study was to elucidate the potential roles of lncRNA, miRNA and messenger RNA (mRNA) ceRNA networks in pulpitis tissues compared to normal control tissues.MethodsThe oligo and limma packages were used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs, respectively) based on expression profiles in two datasets, GSE92681 and GSE77459, from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were further analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein-protein interaction (PPI) networks and modules were established to screen hub genes using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the Molecular Complex Detection (MCODE) plugin for Cytoscape, respectively. Furthermore, an lncRNA-miRNA-mRNA-hub genes regulatory network was constructed to investigate mechanisms related to the progression and prognosis of pulpitis. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was applied to verify critical lncRNAs that may significantly affect the pathogenesis in inflamed and normal human dental pulp.ResultsA total of 644 upregulated and 264 downregulated differentially expressed genes (DEGs) in pulpitis samples were identified from the GSE77459 dataset, while 8 up- and 19 downregulated probes associated with lncRNA were identified from the GSE92681 dataset. Protein-protein interaction (PPI) based on STRING analysis revealed a network of DEGs containing 4,929 edges and 623 nodes. Upon combined analysis of the constructed PPI network and the MCODE results, 10 hub genes, including IL6, IL8, PTPRC, IL1B, TLR2, ITGAM, CCL2, PIK3CG, ICAM1, and PIK3CD, were detected in the network. Next, a ceRNA regulatory relationship consisting of one lncRNA (PVT1), one miRNA (hsa-miR-455-5p) and two mRNAs (SOCS3 and PLXNC1) was established. Then, we constructed the network in which the regulatory relationship between ceRNA and hub genes was summarized. Finally, our qRT-PCR results confirmed significantly higher levels of PVT1 transcript in inflamed pulp than in normal pulp tissues (p = 0.03).ConclusionOur study identified a novel lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of pulpitis.

Project description:BackgroundThis study aimed to develop multi-RNA-based models using a competing endogenous RNA (ceRNA) regulatory network to provide survival risk prediction in head and neck squamous cell carcinoma (HNSCC).MethodsAll long non-coding RNA (lncRNA), microRNA (miRNA), and mRNA expression data and clinicopathological features related to HNSCC were derived from The Cancer Genome Atlas. Differentially expressed RNAs were calculated using R. Prognostic factors were identified using univariate Cox regression analysis. Functional analysis was performed using GO, KEGG pathways, and PPI network. Based on the results, we derived a risk signature and compared high- and low-risk subgroups using LASSO regression analysis. Survival analysis and the relationship between risk signature and clinicopathological features were performed using log-rank tests and Cox regression analysis. A ceRNA regulatory network was constructed, and prognostic lncRNAs and miRNA expression levels were validated in vitro and in vivo.ResultsA list of 207 lncRNAs, 18 miRNAs and 362 mRNAs related to overall survival was established. Five lncRNAs (HOTTIP, LINC00460, RMST, SFTA1P, and TM4SF19-AS1), one miRNA (hsa-miR-206), and one mRNA (STC2) were used to construct the ceRNA network. Three prognostic models contained 13 lncRNAs, eight miRNAs, and 17 mRNAs, which correlated with the patient status, disease-free survival (DFS), stage, grade, T stage, N stage, TP53 mutation status, angiolymphatic invasion, HPV status, and extracapsular spread. KEGG pathway analysis revealed significant enrichment of "Transcriptional misregulation in cancer" and "Neuroactive ligand-receptor interaction." In addition, HOTTIP, LINC00460, miR-206 and STC2 were validated in GTEx data, GEO microarrays and six HNSCC cell lines.ConclusionsOur findings clarify the interaction of ceRNA regulatory networks and crucial clinicopathological features. These results show that prognostic biomarkers can be identified by constructing multi-RNA-based prognostic models, which can be used for survival risk prediction in patients with HNSCC.

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Project description:Phospholipase C epsilon 1 (PLCE1) and the competing endogenous RNA (ceRNA) network are crucial for tumorigenesis and the progression of esophageal squamous cell carcinoma (ESCC). However, whether PLCE1 can regulate the ceRNA network in ESCC has not been clarified. In the present study, we aimed to identify the PLCE1‑regulated ceRNA network and further elucidate the regulatory mechanisms by which ESCC is promoted. Microarray analysis was used to identify differentially expressed lncRNAs (DELs) and differentially expressed genes (DEGs) from three pairs of samples of PLCE‑silenced Eca109 and control Eca109 cells. Next, the ceRNA regulatory network was established and visualized in Cytoscape, and functional enrichment analysis was performed to analyze DEGs from ceRNAs. Protein‑protein interaction (PPI) networks among the DEGs were established by the STRING database to screen hub genes. Kaplan‑Meier survival analysis was used to validate hub genes. Finally, PLCE1‑related hub gene/lncRNA/miRNA axes were also constructed based on the ceRNA network. A total of 105 DELs and 346 DEGs were found to be dysregulated in the microarray data (|log2FC| >1.5, adjusted P<0.05). We constructed a PLCE1‑regulated ceRNA network that incorporated 12 lncRNAs, 43 miRNAs, and 169 mRNAs. Functional enrichment analysis indicated that the DEGs might be associated with ESCC onset and development. A PPI network was established, and 9 hub genes [WD and tetratricopeptide repeats 1 (WDTC1), heat shock protein family A (Hsp70) member 5 (HSPA5), N‑ethylmaleimide sensitive factor, vesicle fusing ATPase (NSF), fibroblast growth factor 2 (FGF2), cyclin dependent kinase inhibitor 1A (CDKN1A or P21), bone morphogenetic protein 2 (BMP2), complement C3 (C3), GM2 ganglioside activator (GM2A) and discs large MAGUK scaffold protein 4 (DLG4)] were determined from the network. Kaplan‑Meier survival analysis validated four hub genes (BMP2, CDKN1A, GM2A, and DLG4) that were treated as prognostic factors. Ultimately, hub gene/lncRNA/miRNA subnetworks were obtained based on the 4 hub genes, 13 DEmiRNAs, and 10 DELs. In conclusion, the PLCE1‑regulated ceRNA contributes to the onset and progression of ESCC and the underlying molecular mechanisms may provide insights into personalized prognosis and new therapies for ESCC patients.

Dataset Information

Comprehensive analysis of lncRNA-associated competing endogenous RNA network in tongue squamous cell carcinoma.

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Comprehensive analysis of lncRNA-associated competing endogenous RNA network in tongue squamous cell carcinoma.

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