Dataset Information

Identification of circRNA-miRNA-mRNA Networks for Exploring the Fundamental Mechanism in Lung Adenocarcinoma.

ABSTRACT: Background:Circular RNAs (circRNAs) were elucidated to act as competing endogenous RNAs (ceRNAs) and to play significant roles in cancer initiation and progression. We aimed to identify the important circRNAs in lung adenocarcinoma and intended to predict the functions of them via the bioinformatics analysis. Methods:We extracted data from three Gene Expression Omnibus (GEO) datasets, GSE101586, GSE101684, and GSE104854, and identified the common differentially expressed circRNAs. Agarose gel electrophoresis and Sanger sequencing were used to verify these significant circRNAs. Then, qRT-PCR was performed to validate the expression through matched tissues and cell lines. Afterwards, a ceRNA network was constructed and functional analysis was performed to predict the potential mechanisms of circRNAs. Results:Five circRNAs (hsa_circ_0072088, hsa_circ_0082564, hsa_circ_0008274, hsa_circ_0000519 and hsa_circ_0003528) were identified differentially expressed in the three datasets. Following the Agarose gel electrophoresis and qRT-PCR validation, hsa_circ_0072088 and hsa_circ_0008274 were chosen for further analysis. A ceRNA network of hsa_circ_0072088 and hsa_circ_0008274 was built based on the CSCD/TargetScan/MiRTarbase/StarBase 3.0. Then, the functional analysis showed that several meaningful terms were identified, such as "epithelial to mesenchymal transition (EMT)", "Cellular response to TGF-? stimulus", "MAPK signaling pathway", and "PI3K-AKT signaling pathway". Finally, several significant circRNA/miRNA/mRNA regulatory axes, which were predicted relating to cancer progress, were noted from the network. Conclusion:We identified significant circRNAs and meaningful circRNA-miRNA-mRNA networks to provide novel insight into pathogenesis and therapy of lung adenocarcinoma.

SUBMITTER: Liang L

PROVIDER: S-EPMC7152915 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Identification of circRNA-miRNA-mRNA Networks for Exploring the Fundamental Mechanism in Lung Adenocarcinoma.

Liang Liming L Zhang Liang L Zhang Jiguang J Bai Shutang S Fu Hongdu H

OncoTargets and therapy 20200408

<h4>Background</h4>Circular RNAs (circRNAs) were elucidated to act as competing endogenous RNAs (ceRNAs) and to play significant roles in cancer initiation and progression. We aimed to identify the important circRNAs in lung adenocarcinoma and intended to predict the functions of them via the bioinformatics analysis.<h4>Methods</h4>We extracted data from three Gene Expression Omnibus (GEO) datasets, GSE101586, GSE101684, and GSE104854, and identified the common differentially expressed circRNAs. ...[more]

PMID: 32308427

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Project description:Objectives: Epidermal growth factor receptor-tyrosine kinase inhibitors are widely used for lung epidermal growth factor receptor-positive lung adenocarcinomas, but acquired resistance is inevitable. Although non-coding RNAs, such as circular RNA and microRNA, are known to play vital roles in epidermal growth factor receptor-tyrosine kinase inhibitor resistance, comprehensive analysis is lacking. Thus, this study aimed to explore the circular RNA-microRNA-messenger RNA regulatory network involved in epidermal growth factor receptor-tyrosine kinase inhibitor resistance. Methods: To identify differentially expressed genes between the epidermal growth factor receptor-tyrosine kinase inhibitor sensitive cell line PC9 and resistant cell line PC9/ epidermal growth factor receptor-tyrosine kinase inhibitor resistance(PC9/ER), circular RNA, microRNA and messenger RNA microarrays were performed. Candidates were then identified to construct a circular RNA-microRNA-messenger RNA network using bioinformatics. Additionally, Gene Oncology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted to evaluate the network messenger RNA, setting up a protein-protein interaction network for hub-gene identification. Afterwards, RNA immunoprecipitation was performed to enrich microRNA, and quantitative real-time PCR was used to estimated gene expression levels. Results: In total, 603, 377, and 1863 differentially expressed circular RNA, microRNA, messenger RNAs, respectively, were identified using microarray analysis, constructing a circular RNA-microRNA-messenger RNA network containing 18 circular RNAs, 17 microRNAs and 175 messenger RNAs. Moreover, Gene Oncology and Kyoto Encyclopedia of Genes and Genomes pathway analyses showed that the most enriched biological process terms and pathways were related to epidermal growth factor receptor-tyrosine kinase inhibitor resistance, including Wnt and Hippo signaling pathways. Based on the competing endogenous RNA and protein-protein interaction network, circ-0007312 was showed to interact with miR-764 and both circ-0003748 and circ-0001398 were shown to interact with miR-628; both these microRNAs targeted MAPK1. Furthermore, circ-0007312, circ-0003748, circ-0001398, and MAPK1 were up-regulated, whereas miR-764 and miR-628 were downregulated in PC9/ER cells as compared to parental PC9 cells. We also found that circ-0007312 and miR-764 were positively expressed in plasma. Conclusions: Our original study associated with mechanism of target therapy in lung cancer provided a systematic and comprehensive regulation of circular RNA, microRNA and messenger RNA in epidermal growth factor receptor-tyrosine kinase inhibitor resistance. It was found that circ-0007312- miR-764-MAPK1, circ-0003748-miR-628-MAPK1, and circ-0001398-miR-628-MAPK1 axis may play key roles in epidermal growth factor receptor-tyrosine kinase inhibitor resistance.

Project description:BackgroundCircular RNAs (circRNAs) have received increasing attention in human tumor research. However, there are still a large number of unknown circRNAs that need to be deciphered. The aim of this study is to unearth novel circRNAs as well as their action mechanisms in hepatocellular carcinoma (HCC).MethodsA combinative strategy of big data mining, reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and computational biology was employed to dig HCC-related circRNAs and to explore their potential action mechanisms. A connectivity map (CMap) analysis was conducted to identify potential therapeutic agents for HCC.ResultsSix differently expressed circRNAs were obtained from three Gene Expression Omnibus microarray datasets (GSE78520, GSE94508 and GSE97332) using the RobustRankAggreg method. Following the RT-qPCR corroboration, three circRNAs (hsa_circRNA_102166, hsa_circRNA_100291 and hsa_circRNA_104515) were selected for further analysis. miRNA response elements of the three circRNAs were predicted. Five circRNA-miRNA interactions including two circRNAs (hsa_circRNA_104515 and hsa_circRNA_100291) and five miRNAs (hsa-miR-1303, hsa-miR-142-5p, hsa-miR-877-5p, hsa-miR-583 and hsa-miR-1276) were identified. Then, 1424 target genes of the above five miRNAs and 3278 differently expressed genes (DEGs) on HCC were collected. By intersecting the miRNA target genes and the DEGs, we acquired 172 overlapped genes. A protein-protein interaction network based on the 172 genes was established, with seven hubgenes (JUN, MYCN, AR, ESR1, FOXO1, IGF1 and CD34) determined from the network. The Gene Oncology, Kyoto Encyclopedia of Genes and Genomes and Reactome enrichment analyses revealed that the seven hubgenes were linked with some cancer-related biological functions and pathways. Additionally, three bioactive chemicals (decitabine, BW-B70C and gefitinib) based on the seven hubgenes were identified as therapeutic options for HCC by the CMap analysis.ConclusionsOur study provides a novel insight into the pathogenesis and therapy of HCC from the circRNA-miRNA-mRNA network view.

Dataset Information

Identification of circRNA-miRNA-mRNA Networks for Exploring the Fundamental Mechanism in Lung Adenocarcinoma.

Publications

Identification of circRNA-miRNA-mRNA Networks for Exploring the Fundamental Mechanism in Lung Adenocarcinoma.

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