Dataset Information

Integrated analysis of circular RNA-associated ceRNA network in pancreatic ductal adenocarcinoma.

ABSTRACT: Circular RNAs (circRNAs) have displayed dysregulated expression in several types of cancer. However, the functions of the majority of circRNAs in pancreatic ductal adenocarcinoma (PDAC) remain unknown. The present study aimed to investigate the expression, functions and molecular mechanisms of circRNAs in PDAC. The circRNAs, mRNAs and the microRNA (miRNAs) expression profiles were obtained from three Gene Expression Omnibus microarray datasets, and a circRNA-miRNA-mRNA and circRNA-miRNA-hubgene network was established. The interactions between proteins were analyzed using the Search Tool for the Retrieval of Interacting Genes/Proteins database, and hubgenes were identified using the MCODE plugin. A total of eight differentially expressed circRNAs (DEcircRNAs), 44 differentially expressed miRNAs (DEmiRNAs), and 2,052 differentially expressed mRNAs (DEmRNAs) were identified. The present study successfully constructed a circRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network based on four circRNAs, six miRNAs and 111 mRNAs in PDAC. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathways analyses indicated that DEmRNAs may participate in the pathogenesis and progression of PDAC. The protein-protein interaction network and module analysis identified six hubgenes (THBS1, FN1, TIMP3, TGFB2, ITGA1 and ITGA3). Furthermore, the circRNA-miRNA-hubgene regulatory modules were constructed based on the three DEcircRNAs, one DEmiRNAs and five DEmRNAs. In conclusion, the results of the present study improve the current understanding of the pathogenesis of PDAC.

SUBMITTER: Song W

PROVIDER: S-EPMC7039142 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Integrated analysis of circular RNA-associated ceRNA network in pancreatic ductal adenocarcinoma.

Song Wei W Wang Wen-Jie WJ Fu Tao T Chen Lei L Miao Dong-Liu DL

Oncology letters 20200116 3

Circular RNAs (circRNAs) have displayed dysregulated expression in several types of cancer. However, the functions of the majority of circRNAs in pancreatic ductal adenocarcinoma (PDAC) remain unknown. The present study aimed to investigate the expression, functions and molecular mechanisms of circRNAs in PDAC. The circRNAs, mRNAs and the microRNA (miRNAs) expression profiles were obtained from three Gene Expression Omnibus microarray datasets, and a circRNA-miRNA-mRNA and circRNA-miRNA-hubgene ...[more]

PMID: 32194715

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Project description:Circular RNA (circRNA) is closely related to tumorigenesis and cancer progression. Yet, the roles of cancer-specific circRNAs in the circRNA-related ceRNA network of breast cancer (BRCA) remain unclear. The aim of this study was to construct a ceRNA network associated with circRNA and to explore new therapeutic and prognostic targets and biomarkers for breast cancer. We downloaded the circRNA expression profile of BRCA from Gene Expression Omnibus (GEO) microarray datasets and downloaded the miRNA and mRNA expression profiles of BRCA from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed circRNAs (DEcircRNAs) were identified, and a competitive endogenous RNA (ceRNA) regulatory network was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs. Gene ontology and pathway enrichment analyses were performed on mRNAs regulated by circRNAs in ceRNA networks. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network were performed. A total of 72 DEcircRNAs, 158 DEmiRNAs, and 2762 DE mRNAs were identified. The constructed ceRNA network contains 60 circRNA-miRNA pairs and 140 miRNA-mRNA pairs, including 40 circRNAs, 30 miRNAs, and 100 mRNAs. Functional enrichment indicated that DEmRNAs regulated by DEcircRNAs in ceRNA networks were significantly enriched in the PI3K-Akt signaling pathway, microRNAs in cancer, and proteoglycans in cancer. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network showed that 13 mRNAs and 6 miRNAs were significantly associated with overall survival, and 48 miRNA-mRNA interaction pairs had a significant negative correlation. A PPI network was established, and 21 hub genes were determined from the network. This study provides an effective bioinformatics basis for further understanding of the molecular mechanisms and predictions of breast cancer. A better understanding of the circRNA-related ceRNA network in BRCA will help identify potential biomarkers for diagnosis and prognosis.

Project description:BackgroundA growing body of evidence indicates that long non-coding RNAs (lncRNAs) can act as competitive endogenous RNAs (ceRNAs) to bind to microRNAs (miRNAs), thereby affecting and regulating the expression of target genes. The lncRNA-miRNA-mRNA ceRNA network has been theorized to play an indispensable role in many types of tumors. However, the role of the lncRNA-related ceRNA regulatory network in lung adenocarcinoma (LUAD) remains unclear.MethodsWe downloaded the RNAseq and miRNAseq data of LUAD from The Cancer Genome Atlas (TCGA) data portal and identified differentially expressed lncRNAs (DElncRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) between LUAD and corresponding paracancerous tissues by using the edgeR package of R software. We constructed the lncRNA-miRNA-mRNA ceRNA network by using Cytoscape (version 3.7.2) on the basis of the interaction generated from the miRcode, miRTarBase, miRDB, and TargetScan databases. Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed with DAVID 6.8 bioinformatics resources and plotted by using the ggplot2 package in R. The effect of genes on LUAD prognosis was assessed by applying the survival package in R in accordance with the Kaplan-Meier curve.ResultsIn total, 1645 DElncRNAs, 117 DEmiRNAs, and 2729 DEmRNAs were identified in LUAD. The LUAD-specific ceRNA network was composed of 157 nodes and 378 edges (329 DElncRNA-DEmiRNA interactions and 49 DEmiRNA-DEmRNA interactions). GO and KEGG pathway annotations suggested that the LUAD-specific ceRNA network was related to tumor-related molecular functions and pathways. Seven lncRNAs (DISC1-IT1, SYNPR-AS1, H19, LINC00460, LINC00518, DSCR10, and STEAP2-AS1), one miRNA (hsa-mir-31), and 16 mRNAs (ATAD2, OSCAR, KIF23, E2F7, PFKP, MCM4, CEP55, CBX2, CCNE1, CLSPN, CCNB1, CDC25A, EZH2, CHEK1, SLC7A11, and PBK) were revealed to be significantly correlated with overall survival.ConclusionIn this study, we described the potential regulatory mechanism of the progression of LUAD. We proposed a new lncRNA-miRNA-mRNA ceRNA network that could help further explore the molecular mechanisms of LUAD.

Project description:A comprehensive meta-analysis of publicly available gene expression microarray data obtained from human-derived pancreatic ductal adenocarcinoma (PDAC) tissues and their histologically matched adjacent tissue samples was performed to provide diagnostic and prognostic biomarkers, and molecular targets for PDAC. An integrative meta-analysis of four submissions (GSE62452, GSE15471, GSE62165, and GSE56560) containing 105 eligible tumor-adjacent tissue pairs revealed 344 differentially over-expressed and 168 repressed genes in PDAC compared to the adjacent-to-tumor samples. The validation analysis using TCGA combined GTEx data confirmed 98.24% of the identified up-regulated and 73.88% of the down-regulated protein-coding genes in PDAC. Pathway enrichment analysis showed that "ECM-receptor interaction", "PI3K-Akt signaling pathway", and "focal adhesion" are the most enriched KEGG pathways in PDAC. Protein-protein interaction analysis identified FN1, TIMP1, and MSLN as the most highly ranked hub genes among the DEGs. Transcription factor enrichment analysis revealed that TCF7, CTNNB1, SMAD3, and JUN are significantly activated in PDAC, while SMAD7 is inhibited. The prognostic significance of the identified and validated differentially expressed genes in PDAC was evaluated via survival analysis of TCGA Pan-Cancer pancreatic ductal adenocarcinoma data. The identified candidate prognostic biomarkers were then validated in four external validation datasets (GSE21501, GSE50827, GSE57495, and GSE71729) to further improve reliability. A total of 28 up-regulated genes were found to be significantly correlated with worse overall survival in patients with PDAC. Twenty-one of the identified prognostic genes (ITGB6, LAMC2, KRT7, SERPINB5, IGF2BP3, IL1RN, MPZL2, SFTA2, MET, LAMA3, ARNTL2, SLC2A1, LAMB3, COL17A1, EPSTI1, IL1RAP, AK4, ANXA2, S100A16, KRT19, and GPRC5A) were also found to be significantly correlated with the pathological stages of the disease. The results of this study provided promising prognostic biomarkers that have the potential to differentiate PDAC from both healthy and adjacent-to-tumor pancreatic tissues. Several novel dysregulated genes merit further study as potentially promising candidates for the development of more effective treatment strategies for PDAC.

Dataset Information

Integrated analysis of circular RNA-associated ceRNA network in pancreatic ductal adenocarcinoma.

Publications

Integrated analysis of circular RNA-associated ceRNA network in pancreatic ductal adenocarcinoma.

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