Predicting functional circular RNA-based competitive endogenous RNA network in gastric carcinoma using novel bioinformatics analysis.
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ABSTRACT:
SUBMITTER: Zhu Z
PROVIDER: S-EPMC8777479 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Keratoconus (KC) is the most common corneal ectatic disease, with its pathological mechanisms unclear. We mainly performed bioinformatics approaches to reveal core RNA targets and hub competitive endogenous RNA (ceRNA) network and explored the potential regulatory mechanisms of ceRNA in KC. The high-throughput sequencing datasets GSE77938 and GSE151631 were downloaded from the Gene Expression Omnibus (GEO) database. The differential expression of mRNAs and lncRNAs was identified using the DESeq2 package. Functional enrichment analyses and protein-protein interaction (PPI) were executed. Then, the hub genes were filtered and molecular docking analysis was performed. Moreover, we predicted miRNAs through a website database and validated them using quantitative PCR (qPCR). Eventually, the lncRNA-miRNA-mRNA regulatory network was constructed by Cytoscape. We revealed that 428 intersected differentially expressed mRNA (DEGs) and 68 intersected differentially expressed lncRNA (DELs) were shared between the two datasets. Functional enrichment results innovatively showed that the ubiquitin-dependent protein catabolic process was upregulated in KC. The pathway enrichment showed that DEGs were mainly involved in NF-kB signaling and neurodegenerative diseases. In addition, we uncovered the top 20 hub genes in which FBXW11, FBXO9, RCHY1, and CD36 were validated by qPCR. Particularly, a small-molecule drug triptolide was predicted by molecular docking to be a candidate drug for treating KC. Moreover, we innovatively predicted and validated four core miRNAs (miR-4257, miR-4494, miR-4263, and miR-4298) and constructed a ceRNA network that contained 165 mRNA, eight lncRNAs, and four core miRNAs. Finally, we proposed a potential regulatory mechanism for KC. Overall, we uncovered a hub ceRNA network that might underlie a critical posttranslational regulatory mechanism in KC, in which miR-4257, miR-4494, miR-4263, and miR-4298 could be valuable biomarkers and provided core RNAs therapeutic targets for KC.
| S-EPMC9209702 | biostudies-literature
Project description:BackgroundType 1 diabetes mellitus (T1DM), an autoimmune disease with a genetic tendency, has an increasing prevalence. Long non-coding RNA (lncRNA) and circular RNA (circRNA) are receiving increasing attention in disease pathogenesis. However, their roles in T1DM are poorly understood. The present study aimed at identifying signature lncRNAs and circRNAs and investigating their roles in T1DM using the competing endogenous RNA (ceRNA) network analysis.MethodsThe T1DM expression profile was downloaded from Gene Expression Omnibus (GEO) database to identify the differentially expressed circRNAs, lncRNAs, and mRNAs. The biological functions of these differentially expressed circRNAs, lncRNAs, and mRNAs were analyzed by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Targeting relationships of circRNA-miRNA, lncRNA-miRNA, and miRNA-mRNA were predicted, and the circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network was established. Finally, qRT-PCR was applied to identify the effect of hsa_circ_0002202 inhibition on the IFN-I induced macrophage inflammation.ResultsA total of 178 circRNAs, 404 lncRNAs, and 73 mRNAs were identified to be abnormally expressed in T1DM samples. Functional enrichment analysis results indicated that the differentially expressed genes were mainly enriched in extracellular matrix components and macrophage activation. CeRNA regulatory network showed that circRNAs and lncRNAs regulate mRNAs through integrate multiple miRNAs. In addition, in vitro experiments showed that hsa_circ_0002202 inhibition suppressed the type I interferon (IFN-I)-induced macrophage inflammation.ConclusionIn the present study, the circRNA-lncRNA-miRNA-mRNA ceRNA regulatory network in T1DM was established for the first time. We also found that hsa_circ_0002202 inhibition suppressed the IFN-I-induced macrophage inflammation. Our study may lay a foundation for future studies on the ceRNA regulatory network in T1DM.
| S-EPMC8436179 | biostudies-literature
Project description:Background: Increasing studies has found that long non-coding RNAs (lncRNAs) play critical roles in carcinogenesis, but the underlying mechanisms remain unclear. The aim of this study is to construct a competitive endogenous RNA (ceRNA) network and to identify potential regulatory axis in gastric cancer (GC). Methods: Differentially expressed (DE) mRNAs, miRNAs, and lncRNAs were obtained by analyzing the RNA expression profiles of stomach adenocarcinoma (STAD) retrieved from The Cancer Genome Atlas (TCGA) database. The lncRNA-miRNA-mRNA regulatory networks of GC were constructed by comprehensive bioinformatics methods including functional annotation, RNA-RNA interactomes prediction, correlation analysis, and survival analysis. The interactions and correlations among ceRNAs were validated by experiments on cancer tissues and cell lines. Results: A total of 41 lncRNAs, 9 miRNAs, and 10 mRNAs were identified and selected to establish the ceRNA regulatory network of GC. Several ceRNA regulatory axes, which consist of 18 lncRNAs, 4 miRNAs, and 6 mRNAs, were obtained from the network. A potential ADAMTS9-AS2/miR-372/CADM2 axis which perfectly conformed to the ceRNA theory was further analyzed. qRT-PCR showed that ADAMTS9-AS2 knockdown remarkably increased miR-372 expression but reduced CADM2 expression, whereas ADAMTS9-AS2 overexpression had the opposite effects. Dual luciferase reporter assay indicated that miR-372 could bound to the ADAMTS9-AS2 and the 3'UTR of CADM2. Conclusion: The constructed novel ceRNA network and the potential regulatory axes might provide a novel approach of the exploring the potential mechanisms of development in GC. The ADAMTS9-AS2/miR-372/CADM2 could act as a promising target for GC treatment.
| S-EPMC6787165 | biostudies-literature
Project description:BackroundTongue squamous cell carcinoma (TSCC) is the most common malignant tumor in the oral cavity. An increasing number of studies have suggested that long noncoding RNA (lncRNA) plays an important role in the biological process of disease and is closely related to the occurrence and development of disease, including TSCC. Although many lncRNAs have been discovered, there remains a lack of research on the function and mechanism of lncRNAs. To better understand the clinical role and biological function of lncRNAs in TSCC, we conducted this study.MethodsIn this study, 162 tongue samples, including 147 TSCC samples and 15 normal control samples, were investigated and downloaded from The Cancer Genome Atlas (TCGA). We constructed a competitive endogenous RNA (ceRNA) regulatory network. Then, we investigated two lncRNAs as key lncRNAs using Kaplan-Meier curve analysis and constructed a key lncRNA-miRNA-mRNA subnetwork. Furthermore, gene set enrichment analysis (GSEA) was carried out on mRNAs in the subnetwork after multivariate survival analysis of the Cox proportional hazards regression model.ResultsThe ceRNA regulatory network consists of six differentially expressed miRNAs (DEmiRNAs), 29 differentially expressed lncRNAs (DElncRNAs) and six differentially expressed mRNAs (DEmRNAs). Kaplan-Meier curve analysis of lncRNAs in the TSCC ceRNA regulatory network showed that only two lncRNAs, including LINC00261 and PART1, are correlated with the total survival time of TSCC patients. After we constructed the key lncRNA-miRNA -RNA sub network, the GSEA results showed that key lncRNA are mainly related to cytokines and the immune system. High expression levels of LINC00261 indicate a poor prognosis, while a high expression level of PART1 indicates a better prognosis.
| S-EPMC6544013 | biostudies-literature
Project description:Background: The mortality and disability rates of acute coronary syndrome (ACS) are quite high. Circular RNA (circRNA) is a competitive endogenous RNA (ceRNA) that plays an important role in the pathophysiology of ACS. Our goal is to screen circRNA-associated ceRNA networks for biomarker genes that are conducive to the diagnosis or exclusion of ACS, and better understand the pathology of the disease through the analysis of immune cells. Materials and methods: RNA expression profiles for circRNAs (GSE197137), miRNAs (GSE31568), and mRNAs (GSE95368) were obtained from the GEO database, and differentially expressed RNAs (DEcircRNAs, DEmiRNAs, and DEmRNAs) were identified. The circRNA-miRNA and miRNA-mRNA regulatory links were retrieved from the CircInteractome database and TargetScan databases, respectively. As a final step, a regulatory network has been designed for ceRNA. On the basis of the ceRNA network, hub mRNAs were verified by quantitative RT-PCR. Hub genes were validated using a third independent mRNA database GSE60993, and ROC curves were used to evaluate their diagnostic values. The correlation between hub genes and immune cells associated with ACS was then analyzed using single sample gene set enrichment analysis (ssGSEA). Results: A total of 17 DEcircRNAs, 229 DEmiRNAs, and 27 DEmRNAs were found, as well as 52 circRNA-miRNA pairings and 10 miRNA-mRNA pairings predicted. The ceRNA regulatory network (circRNA-miRNA-mRNA) was constructed, which included 2 circRNA (hsa_circ_0082319 and hsa_circ_0005654), 4 miRNA (hsa-miR-583, hsa-miR-661, hsa-miR-671-5p, hsa-miR-578), and 5 mRNA (XPNPEP1, UCHL1, DBNL, GPC6, and RAD51). The qRT-PCR analysis result showed that the XPNPEP1, UCHL1, GPC6 and RAD51 genes had a significantly decreased expression in ACS patients. Based on ROC curve analysis, we found that XPNPEP1 has important significance in preventing ACS occurrence and excluding ACS diagnosis. ACS immune infiltration analysis revealed significant correlations between the other 3 hub genes (UCHL1, GPC6, RAD51) and the immune cells (Eosinophils, T folliculars, Type 2 T helper cells, and Imumature dendritic cells). Conclusion: Our study constructed a circRNA-related ceRNA network in ACS. The XPNPEP1 gene could be a protective gene biomarker for ACS. The UCHL1, GPC6 and RAD51 genes were significantly correlated with immune cells in ACS.
| S-EPMC9627163 | biostudies-literature
Project description:BackgroundCircular RNA is emerging functional molecule for glioblastoma. However, the function and regulatory of circular RNA (circRNA) remains unclear. In this study, the circRNA sequencing and array data of glioblastoma were analyzed by multiple bioinformatics methods to establish a potential molecular sponge mechanism regulation network.MethodsGene Expression Omnibus datasets were used to extract circRNAs. CircInteractome was used to predict microRNAs binding to circRNAs. Chinese Glioma Gene Atlas database was used to screen the microRNAs with expression and survival trends. MiRabel database was used to predict potential gene targets of microRNAs. The Cancer Genome Atlas database was used to screen the gene targets of sponge network. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis were to explain the gene targets functions. R software, Cytoscape software and Bioinformatics website were used to establish the network and visualize the results.ResultsHsa_circ_0000219, hsa_circ_0001073 and hsa_circ_0070700 were selected from more than 2000 differentially expressed circRNAs of Gene Expression Omnibus Series (GSE) GSE146463, GSE92322 and GSE86202 datasets. Hsa-miR-1248 and hsa-miR-1290 were up regulated and related to glioblastoma poor prognosis. Targets of these microRNAs including ARHGEF7, CELA2b, RNF11, YPEL1 and ZNF37a were also screened via expression and survival data. Gene targets function were mainly enriched in signal transduction, cell plasma membrane, ATP binding and calcium signaling pathway.ConclusionsA circRNA molecular sponge regulatory network including hsa-miR-1248 and hsa-miR-1290 has been established. In this network, hsa_circ_0001073, hsa_circ_0070700, hsa_circ_0000219, hsa-miR-1248, hsa-miR-1290, and RNF11 may have the potential being emerging glioblastoma therapeutic targets. However, their function and significance for glioblastoma need further experiments to verify.
| S-EPMC9189202 | biostudies-literature
Project description:The competing endogenous RNA (ceRNA) activity of circular RNAs (circRNAs) has been implicated in the development of gastric cancer. Here, we sought to explore the ceRNA function of circRNA Jupiter microtubule associated homolog 1 (circ_HN1) in gastric tumorigenesis. Circ_HN1, microRNA (miR)-628-5p, and NT5E expression levels were quantified by qRT-PCR and western blot. Dual-luciferase reporter assays were used to assess the direct relationship between miR-628-5p and circ_HN1 or NT5E. Our data showed that circ_HN1 expression was enhanced in human gastric cancer. Depletion of circ_HN1 impeded cell proliferation, spheroid formation, invasion, and migration and promoted apoptosis in vitro, as well as diminished tumor growth in vivo. NT5E was a downstream effector of circ_HN1 function. NT5E was targeted and inhibited by miR-628-5p through the perfect complementary site in NT5E 3'UTR, and circ_HN1 affected NT5E expression through miR-628-5p competition. Moreover, depletion of miR-628-5p reversed the effects of circ_HN1 silencing on regulating cell functional behaviors. Our findings identify a novel ceRNA network, the circ_HN1/miR-628-5p/NT5E axis, for the oncogenic activity of circ_HN1 in gastric cancer, highlighting circ_HN1 inhibition as a promising targeted treatment against gastric cancer.
| S-EPMC8810003 | biostudies-literature
Project description:Background:Lung squamous cell carcinoma (LUSC) is a subtype of highly malignant lung cancer with poor prognosis, for which smoking is the main risk factor. However, the underlying genetic and molecular mechanisms of smoking-related LUSC remain largely unknown. Methods:We mined existing LUSC-related mRNA, miRNA, and lncRNA transcriptome data and corresponding clinical data from The Cancer Genome Atlas (TCGA) database and divided them into smoking and nonsmoking groups, followed by differential expression analysis. Functional enrichment analysis of the unique differentially expressed mRNAs of the two groups was performed using the DAVID database. Subsequently, the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network of LUSC in smoking and nonsmoking groups was constructed. Finally, survival analyses were performed to determine the effects of differentially expressed lncRNAs/mRNAs/miRNAs that were involved in the ceRNA network on overall survival and to discover the hub genes. Results:A total of 1696 lncRNAs, 125 miRNAs, and 3246 mRNAs and 1784 lncRNAs, 96 miRNAs, and 3229 mRNAs with differentially expressed profiles were identified in the smoking and nonsmoking groups, respectively. The ceRNA network and survival analysis revealed four lncRNAs (LINC00466, DLX6-AS1, LINC00261, and AGBL1), one miRNA (hsa-mir-210), and two mRNAs (CITED2 and ENPP4), with the potential as biomarkers for smoking-related LUSC diagnosis and prognosis. Conclusion:Taken together, our research has identified the differences in the ceRNA regulatory networks between smoking and nonsmoking LUSC, which could lay the foundation for future clinical research.
| S-EPMC6914966 | biostudies-literature
Project description:The aim of the present study is to construct a competitive endogenous RNA (ceRNA) regulatory network by using differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in patients with hepatocellular carcinoma (HCC), and to construct a prognostic model for predicting overall survival (OS) of HCC patients. Differentially expressed lncRNAs, miRNAs, and mRNAs were explored between HCC tissues and normal liver tissues. A prognostic model was built for predicting OS of HCC patients and receiver operating characteristic curves were used to evaluate the performance of the prognostic model. There were 455 differentially expressed lncRNAs, 181 differentially expressed miRNAs, and 5035 differentially expressed mRNAs. A ceRNA regulatory network was constructed based on 43 lncRNAs, 37 miRNAs, and 105 mRNAs. Eight mRNA biomarkers (H2AFX, SQSTM1, ITM2A, PFKP, TPD52L1, ACSL4, STRN3, and CPEB3) were identified as independent risk factors by multivariate Cox regression and were used to develop a prognostic model for OS. The C-indexes in the model group were 0.776 (95% confidence interval [CI], 0.730-0.822), 0.745 (95% CI, 0.699-0.791), and 0.789 (95% CI, 0.743-0.835) for 1-, 3-, and 5-year OS, respectively. The current study revealed potential molecular biological regulation pathways and prognostic biomarkers by the ceRNA regulatory network. A prognostic model based on prognostic mRNAs in the ceRNA network might be helpful to predict the individual mortality risk for HCC patients. The individual mortality risk calculator can be used by visiting the following URL: https://zhangzhiqiao.shinyapps.io/Smart_cancer_predictive_system_HCC/.
| S-EPMC6726690 | biostudies-literature
Project description:BackgroundLong noncoding RNAs (lncRNAs) play a role in the formation, development, and prognosis of various cancers. Our study aimed to identify prognostic-related lncRNAs in lung squamous cell carcinoma (LUSC), which may provide new perspectives for individualized treatment of patients.Materials and methodsThe RNA sequencing (lncRNA, microRNA (miRNA), mRNA) data and clinical information related to LUSC were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed RNA sequences were used to construct the competitive endogenous RNA (ceRNA) network. In present study, we mainly used two prognostic verification methods, Cox analysis and survival analysis, to identify the prognostic relevance of specific lncRNAs and construct prognostic model of lncRNA.ResultsDatasets on 551 samples of lncRNA and mRNA and 523 miRNA samples were retrieved from the TCGA database. Analysis of the normal and LUSC samples identified 170 DElncRNAs, 331 DEmiRNAs, and 417 DEmRNAs differentially expressed RNAs. The ceRNA network contained 27 lncRNAs, 43 miRNAs, and 11 mRNAs. Furthermore, we identified seven specific lncRNAs (ERVH48-1, HCG9, SEC62-AS1, AC022148.1, LINC00460, C5orf17, LINC00261) as potential prognostic factors after correlation analysis, and five of the seven lncRNAs (AC022148.1, HCG9, LINC00460, C5orf17, LINC00261) constructed a prognostic model of LUSC.ConclusionIn present study, we identified seven lncRNAs in the ceRNA network that are associated with potential prognosis in LUSC patients, and constructed a prognostic model of LUSC which can be used to assess the prognosis risk of clinical patients. Further biological experiments are needed to elucidate the specific molecular mechanisms underlying them.
| S-EPMC6753923 | biostudies-literature