Dataset Information

Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer.

ABSTRACT:

Background

Increasing evidence has underscored the role of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in the development and progression of tumors. Nevertheless, lncRNA biomarkers in lncRNA-related ceRNA network that can predict the prognosis of breast cancer (BC) are still lacking. The aim of our study was to identify potential lncRNA signatures capable of predicting overall survival (OS) of BC patients.

Methods

The RNA sequencing data and clinical characteristics of BC patients were obtained from the Cancer Genome Atlas database, and differentially expressed lncRNA (DElncRNAs), DEmRNAs, and DEmiRNAs were then identified between BC and normal breast tissue samples. Subsequently, the lncRNA-miRNA-mRNA ceRNA network of BC was established, and the gene oncology enrichment analyses for the DEmRNAs interacting with lncRNAs in the ceRNA network was implemented. Using univariate and multivariate Cox regression analyses, a four-lncRNA signature was developed and used for predicting the survival in BC patients. We applied receiver operating characteristic analysis to assess the performance of our model.

Results

A total of 1061 DElncRNAs, 2150 DEmRNAs, and 82 DEmiRNAs were identified between BC and normal breast tissue samples. A lncRNA-miRNA-mRNA ceRNA network of BC was established, which comprised of 8 DEmiRNAs, 48 DElncRNAs, and 10 DEmRNAs. Further gene oncology enrichment analyses revealed that the DEmRNAs interacting with lncRNAs in the ceRNA network participated in cell leading edge, protease binding, alpha-catenin binding, gamma-catenin binding, and adenylate cyclase binding. A univariate regression analysis of the DElncRNAs revealed 7 lncRNAs (ADAMTS9-AS1, AC061992.1, LINC00536, HOTAIR, AL391421.1, TLR8-AS1 and LINC00491) that were associated with OS of BC patients. A multivariate Cox regression analysis demonstrated that 4 of those lncRNAs (ADAMTS9-AS1, LINC00536, AL391421.1 and LINC00491) had significant prognostic value, and their cumulative risk score indicated that this 4-lncRNA signature independently predicted OS in BC patients. Furthermore, the area under the curve of the 4-lncRNA signature associated with 3-year survival was 0.696.

Conclusions

The current study provides novel insights into the lncRNA-related ceRNA network in BC and the 4 lncRNA biomarkers may be independent prognostic signatures in predicting the survival of BC patients.

SUBMITTER: Fan CN

PROVIDER: S-EPMC6161429 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Publications

Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer.

Fan Chun-Ni CN Ma Lei L Liu Ning N

Journal of translational medicine 20180927 1

<h4>Background</h4>Increasing evidence has underscored the role of long non-coding RNAs (lncRNAs) acting as competing endogenous RNAs (ceRNAs) in the development and progression of tumors. Nevertheless, lncRNA biomarkers in lncRNA-related ceRNA network that can predict the prognosis of breast cancer (BC) are still lacking. The aim of our study was to identify potential lncRNA signatures capable of predicting overall survival (OS) of BC patients.<h4>Methods</h4>The RNA sequencing data and clinica ...[more]

PMID: 30261893

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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 aims to reveal early breast cancer (BC) specific competing endogenous RNA (ceRNA) network through the expression profiles of microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and mRNAs.MethodsBased on The Cancer Genome Atlas (TCGA), we obtained the differentially expressed mRNAs, miRNAs, and lncRNAs (DEmRNAs, DEmiRNAs and DElncRNAs) between early BC and normal samples. The lncRNA-miRNA-mRNA interaction network was constructed using Cytoscape. Functional enrichment were performed using GeneCoDis3. The expression of selected genes were validated by qRT-PCR. Based on the published dataset, we validated the result of TCGA integration analysis. The diagnostic and prognostic value of candidate genes was evaluated by ROC curve analysis and survival analysis, respectively.ResultsTotally, 1207 DEmRNAs, 194 DElncRNAs and 37 DEmiRNAs were obtained. Functional enrichment analysis results showed that all of DEmRNAs were enriched in pathway of cytokine-cytokine receptor interaction, PPAR signaling pathway and pathways in cancer. The DEmRNA-DEmiRNA-DElncRNA interaction network in early BC was consisted of 23 DEmiRNAs, 95 DElncRNAs and 309 DEmRNAs. Among ceRNA network, IL-6-hsa-miR-182-5p-ADAMTS9-AS1 interactions, LIFR-hsa-miR-21-5p-ADAMTS9-AS1 interactions and MMP1/MMP11-hsa-miR-145-5p-CDKN2B-AS1 interactions were speculated to involve in the development of early BC. The qRT-PCR results were consistent with our integrated analysis. Except for ADAMTS9-AS1 and CDKN2B-AS1, expression of the others results in the Gene Expression Omnibus (GEO) dataset were generally consistent with TCGA integrated analysis. The area under curve (AUC) of the ADAMTS9-AS1, CDKN2B-AS1, IL-6, MMP11, hsa-miR-145-5p and hsa-miR-182-5p were 0.947, 0.862, 0.842, 0.993, 0.960 and 0.944, and the specificity and sensitivity of the 6 biomarkers were 83.4% and 95.6%, 72.2% and 90.3%, 80.1% and 74.3%, 96.2% and 96.5%, 90.1% and 92.3%, and 88.7% and 90.4%, respectively. In addition, IL-6 had potential prognostic value for early BC.ConclusionThese findings may provide novel insights into the lncRNA-miRNA-mRNA network and uncover potential therapeutic targets in early BC.

Dataset Information

Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer.

Background

Methods

Results

Conclusions

Publications

Systematic analysis of lncRNA-miRNA-mRNA competing endogenous RNA network identifies four-lncRNA signature as a prognostic biomarker for breast cancer.

Similar Datasets

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