Dataset Information

Identification and Analysis of P53-Mediated Competing Endogenous RNA Network in Human Hepatocellular Carcinoma.

ABSTRACT: Recent studies have indicated that long non-coding RNAs (lncRNAs) and mRNA function as competing endogenous RNAs (ceRNAs) that compete to bind to shared microRNA (miRNA) recognition elements (MREs) to perform specific biological functions during tumorigenesis. The tumor suppressor p53 is a master regulator of cancer-related biological processes by acting as a transcription factor to regulate target genes including miRNA and lncRNA. However, the mechanism in human hepatocellular carcinoma and whether p53-mediated RNA targets could form ceRNA network remain unclear. Here, we identified a series of differential expressed miRNAs, lncRNA and mRNA which were potentially regulated by p53 using RNA sequencing in HepG2. Genomic characteristics comparative analysis showed significant differences between mRNAs and lncRNAs. By integrating experimentally confirmed Ago2 and p53 binding sites, we constructed a highly reliable p53-mediated ceRNA network using hypergeometric test. The KEGG pathway enrichment analysis showed that the ceRNA network highly enriched in the cancer or p53-associated signaling pathways. Finally, using betweenness centrality analysis, we identified five master miRNAs (hsa-miR-3620-5p, hsa-miR-3613-3p, hsa-miR-6881-3p, hsa-miR-6087 and hsa-miR-18a-3p) that regulated most of the target RNAs, suggesting these miRNAs play central roles in the whole p53-mediated ceRNAs network. Taken together, our results provide a new regulatory mechanism of p53 networks for future studies in cancer therapeutics.

SUBMITTER: Zhang Y

PROVIDER: S-EPMC5666336 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Identification and Analysis of P53-Mediated Competing Endogenous RNA Network in Human Hepatocellular Carcinoma.

Zhang Yiming Y Kang Ran R Liu Wenrong W Yang Yalan Y Ding Ruofan R Huang Qingqing Q Meng Junhua J Xiong Lili L Guo Zhiyun Z

International journal of biological sciences 20170905 9

Recent studies have indicated that long non-coding RNAs (lncRNAs) and mRNA function as competing endogenous RNAs (ceRNAs) that compete to bind to shared microRNA (miRNA) recognition elements (MREs) to perform specific biological functions during tumorigenesis. The tumor suppressor p53 is a master regulator of cancer-related biological processes by acting as a transcription factor to regulate target genes including miRNA and lncRNA. However, the mechanism in human hepatocellular carcinoma and whe ...[more]

PMID: 29104512

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Project description:BackgroundHepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide. Recently, competing endogenous RNAs (ceRNA) have revealed a significant role in the progression of HCC. Herein, we aimed to construct a ceRNA network to identify potential biomarkers and illustrate its correlation with immune infiltration in HCC.MethodsRNA sequencing data and clinical traits of HCC patients were downloaded from TCGA. The limma R package was used to identify differentially expressed (DE) RNAs. The predicted prognostic model was established using univariate and multivariate Cox regression. A K-M curve, TISIDB and GEPIA website were utilized for survival analysis. Functional annotation was determined using Enrichr and Reactome. Protein-to-protein network analysis was implemented using SRTNG and Cytoscape. Hub gene expression was validated by quantitative polymerase chain reaction, Oncomine and the Hunan Protein Atlas database. Immune infiltration was analyzed by TIMMER, and Drugbank was exploited to identify bioactive compounds.ResultsThe predicted model that was established revealed significant efficacy with 3- and 5-years of the area under ROC at 0.804 and 0.744, respectively. Eleven DEmiRNAs were screened out by a K-M survival analysis. Then, we constructed a ceRNA network, including 56 DElncRNAs, 6 DEmiRNAs, and 28 DEmRNAs. The 28 DEmRNAs were enriched in cancer-related pathways, for example, the TNF signaling pathway. Moreover, six hub genes, CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1, were all overexpressed in HCC tissues and independently correlated with survival rate. Furthermore, expression of hub genes was related to immune cell infiltration in HCC, including B cells, CD8+ T cells, CD4+ T cells, monocytes, macrophages, neutrophils, and dendritic cells.ConclusionThe findings from this study demonstrate that CEP55, DEPDC1, KIF23, CLSPN, MYBL2, and RACGAP1 are closely associated with prognosis and immune infiltration, representing potential therapeutic targets or prognostic biomarkers in HCC.

Project description:The present study aimed to screen all types of RNAs involved in the development of papillary thyroid carcinoma (PTC). RNA?sequencing data of PTC and normal samples were used for screening differentially expressed (DE) microRNAs (DE?miRNAs), long non?coding RNAs (DE?lncRNAs) and genes (DEGs). Subsequently, lncRNA?miRNA, miRNA?gene (that is, miRNA?mRNA) and gene?gene interaction pairs were extracted and used to construct regulatory networks. Feature genes in the miRNA?mRNA network were identified by topological analysis and recursive feature elimination analysis. A support vector machine (SVM) classifier was built using 15 feature genes, and its classification effect was validated using two microarray data sets that were downloaded from the Gene Expression Omnibus (GEO) database. In addition, Gene Ontology function and Kyoto Encyclopedia Genes and Genomes pathway enrichment analyses were conducted for genes identified in the ceRNA network. A total of 506 samples, including 447 tumor samples and 59 normal samples, were obtained from The Cancer Genome Atlas (TCGA); 16 DE?lncRNAs, 917 DEGs and 30 DE?miRNAs were screened. The miRNA?mRNA regulatory network comprised 353 nodes and 577 interactions. From these data, 15 feature genes with high predictive precision (>95%) were extracted from the network and were used to form an SVM classifier with an accuracy of 96.05% (486/506) for PTC samples downloaded from TCGA, and accuracies of 96.81 and 98.46% for GEO downloaded data sets. The ceRNA regulatory network comprised 596 lines (or interactions) and 365 nodes. Genes in the ceRNA network were significantly enriched in 'neuron development', 'differentiation', 'neuroactive ligand?receptor interaction', 'metabolism of xenobiotics by cytochrome P450', 'drug metabolism' and 'cytokine?cytokine receptor interaction' pathways. Hox transcript antisense RNA, miRNA?206 and kallikrein?related peptidase 10 were nodes in the ceRNA regulatory network of the selected feature gene, and they may serve import roles in the development of PTC.

Project description:Hepatocellular carcinoma (HCC) is a common type of liver cancer and one of the highly lethal diseases worldwide. Hypoxia plays an important role in the development and prognosis of HCC. This study aimed to construct a new hypoxia-related prognosis signature and investigate its potential ceRNA axes in HCC. RNA profiles and hypoxia genes were downloaded, respectively, from the Cancer Genome Atlas hepatocellular carcinoma database and Gene Set Enrichment Analysis website. Cox regression analyses were performed to select the prognostic genes and construct the risk model. The ENCORI database was applied to build the lncRNA-miRNA-mRNA prognosis-related network. The TIMER and CellMiner databases were employed to analyze the association of gene expression in ceRNA with immune infiltration and drug sensitivity, respectively. Finally, the co-expression analysis was carried out to construct the potential lncRNA/miRNA/mRNA regulatory axes. We obtained a prognostic signature including eight hypoxia genes (ENO2, KDELR3, PFKP, SLC2A1, PGF, PPFIA4, SAP30, and TKTL1) and further established a hypoxia-related prognostic ceRNA network including 17 lncRNAs, six miRNAs, and seven mRNAs for hepatocellular carcinoma. Then, the analysis of immune infiltration and drug sensitivity showed that gene expression in the ceRNA network was significantly correlated with the infiltration abundance of multiple immune cells, the expression level of immune checkpoints, and drug sensitivity. Finally, we identified three ceRNA regulatory axes (SNHG1/miR-101-3p/PPFIA4, SNHG1/miR-101-3p/SAP30, and SNHG1/miR-101-3p/TKTL1) associated with the progression of HCC under hypoxia. Here, we constructed a prognosis gene signature and a ceRNA network related to hypoxia for hepatocellular carcinoma. Among the ceRNA network, six highly expressed lncRNAs (AC005540.1, AC012146.1, AC073529.1, AC090772.3, AC138150.2, AL390728.6) and one highly expressed mRNA (PPFIA4) were the potential biomarkers of hepatocellular carcinoma which we firstly reported. The three predicted hypoxia-related regulatory axes may play a vital role in the progression of hepatocellular carcinoma.

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.

Project description:Background:Long noncoding RNAs (lncRNAs) can function as competing endogenous RNAs (ceRNAs) and interact with microRNAs (miRNAs) to regulate target gene expression, which can greatly influence tumor development and progression. Different tumor-node-metastasis (TNM) stages of hepatocellular carcinoma (HCC) defined by the American Joint Committee on Cancer (AJCC) have different clinical results. Our purpose was to comprehensively analyze differentially expressed (DE) lncRNAs, miRNAs, and mRNAs in stage I HCC and identify prognosis-associated RNAs. Methods:RNA-seq data were obtained from The Cancer Genome Atlas (TCGA) database. A stage I HCC-associated miRNA-lncRNA-mRNA network was constructed. Next, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment pathway analyses of ceRNA-associated DEmRNAs were performed using Database for Annotation, Visualization, and Integrated Discovery (DAVID) 6.8 and Clusterprofile in the R package. The protein-protein interaction (PPI) network of the above mRNAs was then constructed using STRING. Finally, the association between lncRNAs and mRNAs in the ceRNA network and prognosis of patients was further analyzed. Linear regression analysis of the above lncRNAs and mRNAs associated with overall survival was performed. Results:After a comparison between HCC and adjacent nontumor tissues, 778 lncRNAs, 1608 mRNAs, and 102 miRNAs that were abnormally expressed were identified. The ceRNA network was composed of 56 DElncRNAs, 14 DEmiRNAs, and 30 DEmRNAs. Functional analysis results showed that 30 DEmRNAs were enriched in 14 GO biological process categories and 6 KEGG categories (false discovery rate (FDR)?<?0.05). A PPI network was composed of 22 nodes and 58 edges. We detected 4 DElncRNAs (BPESC1, AC061975.6, AC079341.1, and CLLU1) and 6 DEmRNAs (CEP55, E2F1, E2F7, EZH2, G6PD, and SLC7A11) that had significant influences on the overall survival (OS) of stage I HCC patients (P < 0.05). lncRNA BPESC1 was positively correlated with mRNA CEP55 via miR-424, and lncRNA AC061975.6 was positively correlated with mRNA E2F1 via miR-519d. Conclusion:Our study identified novel lncRNAs and mRNAs that were associated with the progression and prognosis of stage I HCC and further investigated the regulatory mechanism of lncRNA-mediated ceRNAs in the development of stage I HCC.

Dataset Information

Identification and Analysis of P53-Mediated Competing Endogenous RNA Network in Human Hepatocellular Carcinoma.

Publications

Identification and Analysis of P53-Mediated Competing Endogenous RNA Network in Human Hepatocellular Carcinoma.

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