Dataset Information

Construction of circRNA-Based ceRNA Network to Reveal the Role of circRNAs in the Progression and Prognosis of Hepatocellular Carcinoma.

ABSTRACT:

Background

Circular RNAs (circRNAs) are now under hot discussion as novel promising biomarkers for patients with hepatocellular carcinoma (HCC). The purpose of our study is to identify several competing endogenous RNA (ceRNA) networks related to the prognosis and progression of HCC and to further investigate the mechanism of their influence on tumor progression.

Methods

First, we obtained gene expression data related to liver cancer from The Cancer Genome Atlas (TCGA) database (http://www.portal.gdc.cancer.gov/), including microRNA (miRNA) sequence, RNA sequence, and clinical information. A co-expression network was constructed through the Weighted Correlation Network Analysis (WGCNA) software package in R software. The differentially expressed messenger RNAs (DEmRNAs) in the key module were analyzed with the Database for Annotation Visualization and Integrated Discovery (DAVID) (https://david.ncifcrf.gov/summary.jsp) to perform functional enrichment analysis including Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO). The data of miRNA expression and clinical information downloaded from TCGA were utilized for survival analysis to detach the prognostic value of the DEmiRNAs of the key module.

Results

The 201 differentially expressed miRNAs (DEmiRNAs) and 3,783 DEmRNAs were preliminarily identified through differential expression analysis. The co-expression networks of DEmiRNAs and DEmRNAs were constructed with WGCNA. Further analysis confirmed four miRNAs in the most significant module (blue module) were associated with the overall survival (OS) of patients with liver cancer, including hsa-miR-92b-3p, hsa-miR-122-3p, hsa-miR-139-5p, and hsa-miR-7850-5p. DAVID was used for functional enrichment analysis of 286 co-expressed mRNAs. The GO analysis results showed that the top enriched GO terms were oxidation-reduction process, extracellular exosome, and iron ion binding. In KEGG pathway analysis, the top three enriched terms included metabolic pathways, fatty acid degradation, and valine, leucine, and isoleucine degradation. In addition, we intersected the miRNA-mRNA interaction prediction results with the differentially expressed and prognostic mRNAs. We found that hsa-miR-92b-3p can be related to CPEB3 and ACADL. By overlapping the data of predicted circRNAs by circBank and differentially expressed circRNAs of GSE94508, we screened has_circ_0077210 as the upstream regulatory molecule of hsa-miR-92b-3p. Hsa_circ_0077210/hsa-miR-92b-3p/cytoplasmic polyadenylation element binding protein-3 (CPEB3) and acyl-Coenzyme A dehydrogenase, long chain (ACADL) were validated in HCC tissue.

Conclusion

Our research provides a mechanistic elucidation of the unknown ceRNA regulatory network in HCC. Hsa_circ_0077210 might serve a momentous therapeutic role to restrain the occurrence and development of HCC.

SUBMITTER: Deng R

PROVIDER: S-EPMC7953168 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Publications

Construction of circRNA-Based ceRNA Network to Reveal the Role of circRNAs in the Progression and Prognosis of Hepatocellular Carcinoma.

Deng Rong R Cui Xiaohan X Dong Yuxiang Y Tang Yanqiu Y Tao Xuewen X Wang Shuyu S Wang Jincheng J Chen Lin L

Frontiers in genetics 20210226

<h4>Background</h4>Circular RNAs (circRNAs) are now under hot discussion as novel promising biomarkers for patients with hepatocellular carcinoma (HCC). The purpose of our study is to identify several competing endogenous RNA (ceRNA) networks related to the prognosis and progression of HCC and to further investigate the mechanism of their influence on tumor progression.<h4>Methods</h4>First, we obtained gene expression data related to liver cancer from The Cancer Genome Atlas (TCGA) database (ht ...[more]

PMID: 33719338

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Project description:Background: Hepatocellular carcinoma (HCC) accounts for the majority of liver cancer, with the incidence and mortality rates increasing every year. Despite the improvement of clinical management, substantial challenges remain due to its high recurrence rates and short survival period. This study aimed to identify potential diagnostic and prognostic biomarkers in HCC through bioinformatic analysis. Methods: Datasets from GEO and TCGA databases were used for the bioinformatic analysis. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were carried out by WebGestalt website and clusterProfiler package of R. The STRING database and Cytoscape software were used to establish the protein-protein interaction (PPI) network. The GEPIA website was used to perform expression analyses of the genes. The miRDB, miRWalk, and TargetScan were employed to predict miRNAs and the expression levels of the predicted miRNAs were explored via OncomiR database. LncRNAs were predicted in the StarBase and LncBase while circRNA prediction was performed by the circBank. ROC curve analysis and Kaplan-Meier (KM) survival analysis were performed to evaluate the diagnostic and prognostic value of the gene expression, respectively. Results: A total of 327 upregulated and 422 downregulated overlapping DEGs were identified between HCC tissues and noncancerous liver tissues. The PPI network was constructed with 89 nodes and 178 edges and eight hub genes were selected to predict upstream miRNAs and ceRNAs. A lncRNA/circRNA-miRNA-mRNA network was successfully constructed based on the ceRNA hypothesis, including five lncRNAs (DLGAP1-AS1, GAS5, LINC00665, TYMSOS, and ZFAS1), six circRNAs (hsa_circ_0003209, hsa_circ_0008128, hsa_circ_0020396, hsa_circ_0030051, hsa_circ_0034049, and hsa_circ_0082333), eight miRNAs (hsa-miR-150-5p, hsa-miR-19b-3p, hsa-miR-23b-3p, hsa-miR-26a-5p, hsa-miR-651-5p, hsa-miR-10a-5p, hsa-miR-214-5p and hsa-miR-486-5p), and five mRNAs (CDC6, GINS1, MCM4, MCM6, and MCM7). The ceRNA network can promote HCC progression via cell cycle, DNA replication, and other pathways. Clinical diagnostic and survival analyses demonstrated that the ZFAS1/hsa-miR-150-5p/GINS1 ceRNA regulatory axis had a high diagnostic and prognostic value. Conclusion: These results revealed that cell cycle and DNA replication pathway could be potential pathways to participate in HCC development. The ceRNA network is expected to provide potential biomarkers and therapeutic targets for HCC management, especially the ZFAS1/hsa-miR-150-5p/GINS1 regulatory axis.

Project description:Background and purposeAccumulating evidence suggests that circular RNAs (circRNAs) are involved in immune and inflammatory processes after acute ischemic stroke (AIS). However, the roles of circRNA-mediated competing endogenous RNA (ceRNA) in modulating immune inflammation of AIS have not yet been determined. This study aimed to construct a circRNA-mediated immune-related ceRNA network and identify novel circRNAs in AIS.MethodsMicroarray data were downloaded from the GEO database and further analysed by R software. Then, we constructed a circRNA-mediated ceRNA network based on interaction information from the bioinformatics database. A topological property analysis of the ceRNA network was conducted to screen novel circRNAs. Finally, we further applied quantitative real-time polymerase chain reaction (qRT-PCR) to two independent sets.ResultsWe constructed an AIS immune-related ceRNA (AISIRC) network containing immune-related genes (IRGs), miRNAs, and circRNAs. Additionally, we extracted the subnetwork from the AISIRC network and screened six immune-related circRNAs. After identification and validation, we finally confirmed that plasma levels of circPTP4A2 and circTLK2 were significantly increased in AIS patients compared with both healthy control subjects (HCs) and transient ischemic attack (TIA) patients. Logistic regression and receiver-operating characteristic (ROC) curve analyses demonstrated that these two circRNAs may function as predictive and discriminative biomarkers for AIS. We also confirmed that plasma levels of circPTP4A2 were elevated in TIA patients compared with HCs and might be an independent risk factor for predicting TIA. Longitudinal analysis of circRNA expression up to 90 days after AIS indicated that the ability of circPTP4A2 and circTLK2 to monitor AIS dynamics was highly desirable.ConclusionIn summary, the circRNA-mediated immune-related ceRNA network was successfully constructed, and two circulating circRNAs (circPTP4A2 and circTLK2) improved sensitivity for the diagnosis of AIS and could be considered diagnostic biomarkers.

Dataset Information

Construction of circRNA-Based ceRNA Network to Reveal the Role of circRNAs in the Progression and Prognosis of Hepatocellular Carcinoma.

Background

Methods

Results

Conclusion

Publications

Construction of circRNA-Based ceRNA Network to Reveal the Role of circRNAs in the Progression and Prognosis of Hepatocellular Carcinoma.

Similar Datasets

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