Dataset Information

Construction and investigation of lncRNA-associated ceRNA regulatory network in papillary thyroid cancer.

ABSTRACT: Increasing evidence has experimentally proved the competitive endogenous RNA (ceRNA) hypothesis that long non-coding RNA (lncRNA) can affect the expression of RNA targets by competitively combining microRNA (miRNA) via miRNA response elements. However, an extensive ceRNA network of thyroid carcinoma in a large cohort has not been evaluated. We analyzed the RNAseq and miRNAseq data of 348 cases of primary papillary thyroid cancer (PTC) patients with clinical information downloaded from The Cancer Genome Atlas (TCGA) project to search for potential biomarkers or therapeutic targets. A computational approach was applied to build an lncRNA-miRNA-mRNA regulatory network of PTC. In total, 780 lncRNAs were detected as collectively dysregulated lncRNAs in all 3 PTC variants compared with normal tissues (fold change >2 and false discovery rate <0.05). The interactions among 45 lncRNAs, 13 miRNAs and 86 mRNAs constituted a ceRNA network of PTC. Nine out of the 45 aberrantly expressed lncRNAs were related to the clinical features of PTC patients. However, the expression levels of 3 lncRNAs (LINC00284, RBMS3-AS1 and ZFX-AS1) were identified to be tightly correlated with the patients overall survival (log-rank, P<0.05). The present study identified a list of specific lncRNAs associated with PTC progression and prognosis. This complex ceRNA interaction network in PTC may provide guidance for better understanding the molecular mechanisms underlying PTC.

SUBMITTER: Zhao Y

PROVIDER: S-EPMC5802034 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Construction and investigation of lncRNA-associated ceRNA regulatory network in papillary thyroid cancer.

Zhao Yangjing Y Wang Hui H Wu Chengjiang C Yan Meina M Wu Haojie H Wang Jingzhe J Yang Xinxin X Shao Qixiang Q

Oncology reports 20180110 3

Increasing evidence has experimentally proved the competitive endogenous RNA (ceRNA) hypothesis that long non-coding RNA (lncRNA) can affect the expression of RNA targets by competitively combining microRNA (miRNA) via miRNA response elements. However, an extensive ceRNA network of thyroid carcinoma in a large cohort has not been evaluated. We analyzed the RNAseq and miRNAseq data of 348 cases of primary papillary thyroid cancer (PTC) patients with clinical information downloaded from The Cancer ...[more]

PMID: 29328463

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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:Purpose:Accumulating evidence has indicated that circRNAs are closely involved in tumorigenesis and progression of human cancers. However, the molecular mechanism underlying function of circRNAs in breast cancer has not been thoroughly elucidated. Currently, we aimed to characterize the circRNA-related competing endogenous RNA (ceRNA) regulatory network in breast cancer and to construct prognostic model. Materials and Methods:First, we constructed circRNA expression profiles for paired breast cancer in a Chinese population using a human circRNA microarray. Expression profiles of circRNAs, miRNAs, and mRNAs were retrieved from our circRNA dataset, the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. We applied the limma and edgeR packages to identify differentially expressed RNAs. Weighted gene correlation network analysis (WGCNA) was used to identify critical modules of mRNAs. Next, a ceRNA network was established based on circRNA-miRNA and miRNA-mRNA intersections. Both Cox regression analysis and ROC curve analysis were performed to generate prognostic model. Additionally, we performed Gene Set Enrichment Analysis (GSEA) on prognostic signatures. Results:Total of 59 circRNAs, 98 miRNAs and 3966 mRNAs were identified as differentially expressed RNAs. We first identified 38 miRNA-mRNA pairs and 38 circRNA-miRNA pairs to construct the circRNA-miRNA-mRNA regulatory network and then generated a prognostic model based on 7 signatures (MMD, SLC29A4, CREB5, FOS, ANKRD29, MYOCD, and PIGR), and patients with high-risk scores presented poor prognosis. Several cancer-related pathways were enriched, including the TGF-? pathway, the focal adhesion pathway, and the JAK-STAT signaling pathway, and 20 prognostic ceRNA regulatory networks were subsequently identified. Conclusion:In all, we screened a series of dysregulated circRNAs, miRNAs, and mRNAs, and constructed circRNA-related ceRNA network in breast cancer. Our findings may help to deepen the understanding of circRNA-related regulatory mechanisms. Moreover, we generated a prognostic model that provided new insight into postoperative management for breast cancer.

Dataset Information

Construction and investigation of lncRNA-associated ceRNA regulatory network in papillary thyroid cancer.

Publications

Construction and investigation of lncRNA-associated ceRNA regulatory network in papillary thyroid cancer.

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