Dataset Information

Construction and Comprehensive Analyses of a Competing Endogenous RNA Network in Tumor-Node-Metastasis Stage I Hepatocellular Carcinoma.

ABSTRACT: 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)?

SUBMITTER: Gu X

PROVIDER: S-EPMC7036093 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Construction and Comprehensive Analyses of a Competing Endogenous RNA Network in Tumor-Node-Metastasis Stage I Hepatocellular Carcinoma.

Gu Xuefeng X Li Hongbo H Sha Ling L Zhao Wei W

BioMed research international 20200211

<h4>Background</h4>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 m ...[more]

PMID: 32104698

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Project description:BackgroundHepatocellular carcinoma (HCC) is an extremely common malignant tumor with worldwide prevalence. The aim of this study was to identify potential prognostic genes and construct a competing endogenous RNA (ceRNA) regulatory network to explore the mechanisms underlying the development of HCC.MethodsIntegrated analysis was used to identify potential prognostic genes in HCC with R software based on the GSE14520, GSE17548, GSE19665, GSE29721, GSE60502, and the Cancer Genome Atlas databases. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway-enrichment analyses were performed to explore the molecular mechanisms of potential prognostic genes. Differentially expressed miRNAs (DEMs) and lncRNAs (DELs) were screened based on the Cancer Genome Atlas database. An lncRNA-miRNA-mRNA ceRNA regulatory network was constructed based on information about interactions derived from the miRcode, TargetScan, miRTarBase, and miRDB databases.ResultsA total of 152 potential prognostic genes were screened that were differentially expressed in HCC tissue and significantly associated with overall survival of HCC patients. There were 13 key potential prognostic genes in the ceRNA regulatory network: eleven upregulated genes (CCNB1, CEP55, CHEK1, EZH2, KPNA2, LRRC1, PBK, RRM2, SLC7A11, SUCO, and ZWINT) and two downregulated genes (ACSL1 and CDC37L1) whose expression might be regulated by eight DEMs and 61 DELs. Kaplan-Meier curve analysis showed that nine DELs (AL163952.1, AL359878.1, AP002478.1, C2orf48, C10orf91, CLLU1, CLRN1-AS1, ERVMER61-1, and WARS2-IT1) in the ceRNA regulatory network were significantly associated with HCC-patient prognoses.ConclusionThis study identified potential prognostic genes and constructed an lncRNA- miRNA-mRNA ceRNA regulatory network of HCC, which not only has important clinical significance for early diagnoses but also provides effective targets for HCC treatments and could provide new insights for HCC-interventional strategies.

Project description:BackgroundHepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers.MethodsWe first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively.ResultsWith the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The 'upregulated' ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the 'downregulated' network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients.ConclusionsIn conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

Project description:BackgroundMoyamoya disease (MMD) is a rare cerebrovascular disease characterized by chronic progressive stenosis or occlusion of the bilateral internal carotid artery (ICA), the anterior cerebral artery (ACA), and the middle cerebral artery (MCA). MMD is secondary to the formation of an abnormal vascular network at the base of the skull. However, the etiology and pathogenesis of MMD remain poorly understood.MethodsA competing endogenous RNA (ceRNA) network was constructed by analyzing sample-matched messenger RNA (mRNA), long non-coding RNA (lncRNA), and microRNA (miRNA) expression profiles from MMD patients and control samples. Then, a protein-protein interaction (PPI) network was constructed to identify crucial genes associated with MMD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were employed with the DAVID database to investigate the underlying functions of differentially expressed mRNAs (DEmRNAs) involved in the ceRNA network. CMap was used to identify potential small drug molecules.ResultsA total of 94 miRNAs, 3649 lncRNAs, and 2294 mRNAs were differentially expressed between MMD patients and control samples. A synergistic ceRNA lncRNA-miRNA-mRNA regulatory network was constructed. Core regulatory miRNAs (miR-107 and miR-423-5p) and key mRNAs (STAT5B, FOSL2, CEBPB, and CXCL16) involved in the ceRNA network were identified. GO and KEGG analyses indicated that the DEmRNAs were involved in the regulation of the immune system and inflammation in MMD. Finally, two potential small molecule drugs, CAY-10415 and indirubin, were identified by CMap as candidate drugs for treating MMD.ConclusionsThe present study used bioinformatics analysis of candidate RNAs to identify a series of clearly altered miRNAs, lncRNAs, and mRNAs involved in MMD. Furthermore, a ceRNA lncRNA-miRNA-mRNA regulatory network was constructed, which provides insights into the novel molecular pathogenesis of MMD, thus giving promising clues for clinical therapy.

Project description:BackgroundChronic lymphocytic leukemia (CLL) is a heterogeneous B-cell malignancy that lacks specific biomarkers and drug targets. Competing endogenous RNAs (ceRNAs) play vital roles in oncogenesis and tumor progression by sponging microRNAs (miRNAs). Nevertheless, the regulatory mechanisms of survival-related ceRNA networks in CLL remain to be uncovered.MethodsWe included 865 de novo CLL patients to investigate RNA expression profiles and Illumina sequencing was performed on four CLL patients, two CLL cell lines and six healthy donors in our center. According to univariate Cox regression, LASSO regression as well as multivariate Cox regression analyses, we established a novel risk score model in CLL patients. Immune signatures were compared between the low- and high-risk groups with CIBERSORT and ESTIMATE program. Afterwards, we analyzed the relationship between differentially expressed miRNAs (DEmiRNAs) and IGHV mutational status, p53 mutation status and del17p. Based on the survival analyses and differentially expressed RNAs with targeting relationships, the lncRNA/circRNA-miRNA-mRNA ceRNA networks were constructed. In addition, the circRNA circ_0002078/miR-185-3p/TCF7L1 axis was verified and their interrelations were delineated by dual-luciferase reporter gene assay.ResultsTotally, 57 differentially expressed mRNAs (DEmRNAs) and 335 DEmiRNAs were identified between CLL patient specimens and normal B cells. A novel risk score model consisting of HTN3, IL3RA and NCK1 was established and validated. The concordance indexes of the model were 0.825, 0.719 and 0.773 in the training, test and total sets, respectively. The high-risk group was related to del(13q14) as well as shorter overall survival (OS). Moreover, we identified DEmiRNAs that related to cytogenetic abnormality of CLL patients, which revealed that miR-324-3p was associated with IGHV mutation, p53 mutation and del17p. The survival-related lncRNA/circRNA-miRNA-mRNA ceRNA networks were constructed to further facilitate the development of potential predictive biomarkers. Besides, the expression of circ_0002078 and TCF7L1 were significantly elevated and miR-185-3p was obviously decreased in CLL patients. Circ_0002078 regulated TCF7L1 expression by competing with TCF7L1 for miR-185-3p.ConclusionsThe comprehensive analyses of RNA expression profiles provide pioneering insights into the molecular mechanisms of CLL. The novel risk score model and survival-related ceRNA networks promote the development of prognostic biomarkers and potential therapeutic vulnerabilities for CLL.

Project description:Malignant melanoma (MM) is a malignant tumor originating from melanocytes, with high aggressiveness, high metastasis and extremely poor prognosis. MM accounts for 4% of skin cancers and 80% of mortality, and the median survival of patients with metastatic melanoma is only about 6 months, with a five-year survival rate of less than 10%. In recent years, the incidence of melanoma has gradually increased and has become one of the serious diseases that endanger human health. Competitive endogenous RNA (ceRNA) is the main model of the mechanism by which long chain non-coding RNAs (lncRNAs) play a regulatory role in the disease. LncRNAs can act as a "sponge", competitively attracting small RNAs (micoRNAs; miRNAs), thus interfering with miRNA function, and affect the expression of target gene messenger RNAs (mRNAs), ultimately promoting tumorigenesis and progression. Bioinformatics analysis can identify potentially prognostic and therapeutically relevant differentially expressed genes in MM, finding lncRNAs, miRNAs and mRNAs that are interconnected through the ceRNA network, providing further insight into gene regulation and prognosis of metastatic melanoma. Weighted co-expression networks were used to identify lncRNA and mRNA modules associated with the metastatic phenotype, as well as the co-expression genes contained in the modules. A total of 17 lncRNAs, six miRNAs, and 11 mRNAs were used to construct a ceRNA interaction network that plays a regulatory role in metastatic melanoma patients. The prognostic risk model was used as a sorter to classify the survival prognosis of melanoma patients. Four groups of ceRNA interaction triplets were finally obtained, which miR-3662 might has potential implication for the treatment of metaststic melanoma patients, and futher experiments confirmed the regulating relationship and phenotype of this assumption. This study provides new targets to regulate metastatic process, predict metastatic potential and indicates that the miR-3662 can be used in the treatment of melanoma.

Dataset Information

Construction and Comprehensive Analyses of a Competing Endogenous RNA Network in Tumor-Node-Metastasis Stage I Hepatocellular Carcinoma.

Publications

Construction and Comprehensive Analyses of a Competing Endogenous RNA Network in Tumor-Node-Metastasis Stage I Hepatocellular Carcinoma.

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