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Integrated bioinformatics analysis of chromatin regulator EZH2 in regulating mRNA and lncRNA expression by ChIP sequencing and RNA sequencing.

ABSTRACT: Enhancer of zeste homolog 2 (EZH2), a dynamic chromatin regulator in cancer, represents a potential therapeutic target showing early signs of promise in clinical trials. EZH2 ChIP sequencing data in 19 cell lines and RNA sequencing data in ten cancer types were downloaded from GEO and TCGA, respectively. Integrated ChIP sequencing analysis and co-expressing analysis were conducted and both mRNA and long noncoding RNA (lncRNA) targets were detected. We detected a median of 4,672 mRNA targets and 4,024 lncRNA targets regulated by EZH2 in 19 cell lines. 20 mRNA targets and 27 lncRNA targets were found in all 19 cell lines. These mRNA targets were enriched in pathways in cancer, Hippo, Wnt, MAPK and PI3K-Akt pathways. Co-expression analysis confirmed numerous targets, mRNA genes (RRAS, TGFBR2, NUF2 and PRC1) and lncRNA genes (lncRNA LINC00261, DIO3OS, RP11-307C12.11 and RP11-98D18.9) were potential targets and were significantly correlated with EZH2. We predicted genome-wide potential targets and the role of EZH2 in regulating as a transcriptional suppressor or activator which could pave the way for mechanism studies and the targeted therapy of EZH2 in cancer.

SUBMITTER: Li Y

PROVIDER: S-EPMC5348424 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature

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Integrated bioinformatics analysis of chromatin regulator EZH2 in regulating mRNA and lncRNA expression by ChIP sequencing and RNA sequencing.

Li Yuan Y Luo Mei M Shi Xuejiao X Lu Zhiliang Z Sun Shouguo S Huang Jianbing J Chen Zhaoli Z He Jie J

Oncotarget 20161201 49

Enhancer of zeste homolog 2 (EZH2), a dynamic chromatin regulator in cancer, represents a potential therapeutic target showing early signs of promise in clinical trials. EZH2 ChIP sequencing data in 19 cell lines and RNA sequencing data in ten cancer types were downloaded from GEO and TCGA, respectively. Integrated ChIP sequencing analysis and co-expressing analysis were conducted and both mRNA and long noncoding RNA (lncRNA) targets were detected. We detected a median of 4,672 mRNA targets and ...[more]

PMID: 27835578

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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:BackgroundAccumulating evidence has highlighted the significance of chromatin regulator (CR) in pathogenesis and progression of cancer. However, the prognostic role of CRs in LUAD remains obscure. We aim to detect the prognostic value of CRs in LUAD and create favorable signature for assessing prognosis and clinical value of LUAD patients.MethodsThe mRNA sequencing data and clinical information were obtained from TCGA and GEO databases. Gene consensus clustering analysis was utilized to determine the molecular subtype of LUAD. Cox regression methods were employed to set up the CRs-based signature (CRBS) for evaluating survival rate in LUAD. Biological function and signaling pathways were identified by KEGG and GSEA analyses. In addition, we calculated the infiltration level of immunocyte by CIBERSORT algorithm. The expressions of model hub genes were detected in LUAD cell lines by real-time polymerase chain reaction (PCR).ResultsKEGG analysis suggested the CRs were mainly involved in histone modification, nuclear division and DNA modification. Consensus clustering analysis identified a novel CRs-associated subtype which divided the combined LUAD cohort into two clusters (C1 = 217 and C2 = 296). We noticed that a remarkable discrepancy in survival rate among two clusters. Then, a total of 120 differentially expressed CRs were enrolled into stepwise Cox analyses. Four hub CRs (CBX7, HMGA2, NPAS2 and PRC1) were selected to create a risk signature which could accurately forecast patient outcomes and differentiate patient risk. GSEA unearthed that mTORC1 pathway, PI3K/Akt/mTOR and p53 pathway were greatly enriched in CRBS-high cohort. Moreover, the infiltration percentages of macrophage M0, macrophage M2, resting NK cells, memory B cells, dendritic cells and mast cells were statistically significantly different in the two groups. PCR assay confirmed the differential expression of four model biomarkers.ConclusionsAltogether, our project developed a robust risk signature based on CRs and offered novel insights into individualized treatment for LUAD cases.

Dataset Information

Integrated bioinformatics analysis of chromatin regulator EZH2 in regulating mRNA and lncRNA expression by ChIP sequencing and RNA sequencing.

Publications

Integrated bioinformatics analysis of chromatin regulator EZH2 in regulating mRNA and lncRNA expression by ChIP sequencing and RNA sequencing.

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