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Identification of circRNA–miRNA–mRNA regulatory network in gastric cancer by analysis of microarray data

BACKGROUND: Evidence is increasingly indicating that circular RNAs (circRNAs) are closely involved in tumorigenesis and cancer progression. However, the function of circRNAs in gastric cancer (GC) are still unknown. Here, we aimed to determine the regulatory mechanism of circRNAs in GC. METHODS: Exp...

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Autores principales: Guan, Yong-jun, Ma, Jian-ying, Song, Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636116/
https://www.ncbi.nlm.nih.gov/pubmed/31346318
http://dx.doi.org/10.1186/s12935-019-0905-z
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author Guan, Yong-jun
Ma, Jian-ying
Song, Wei
author_facet Guan, Yong-jun
Ma, Jian-ying
Song, Wei
author_sort Guan, Yong-jun
collection PubMed
description BACKGROUND: Evidence is increasingly indicating that circular RNAs (circRNAs) are closely involved in tumorigenesis and cancer progression. However, the function of circRNAs in gastric cancer (GC) are still unknown. Here, we aimed to determine the regulatory mechanism of circRNAs in GC. METHODS: Expression profiles of circRNAs were downloaded from four Gene Expression Omnibus (GEO) microarray datasets. Expression profiles of miRNAs and mRNAs were collected from The Cancer Genome Atlas (TCGA) database. We used the robust rank aggregation method to identify differentially expressed circRNAs (DEcircRNAs) and a ceRNA network was constructed based on circRNA–miRNA pairs and miRNA–mRNA pairs. Functional and pathway enrichment analyses were performed and interactions between proteins were predicted using Cytoscape. Aa subnetwork regulatory module was built using the MCODE plugin. RESULTS: A total of eight DEcircRNAs, 240 DEmiRNAs, and 4578 DEmRNAs were identified. The circRNA–miRNA–mRNA network was constructed based on seven circRNAs, 33 miRNAs, 69 mRNAs in GC. GO and KEGG pathway analysis indicated DEmRNAs might be associated with GC onset and progression. A PPI network was established and four hub genes (MCM4, KIF23, MCM8, and NCAPD2) were determined from the network. Then a circRNA–miRNA-hub gene subnetwork was constructed based on the four DEcircRNAs, three DEmiRNAs, and four DEmRNAs. CONCLUSIONS: Our findings provide a deeper understanding the circRNA-related competing endogenous RNA regulatory mechanism in GC pathogenesis.
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spelling pubmed-66361162019-07-25 Identification of circRNA–miRNA–mRNA regulatory network in gastric cancer by analysis of microarray data Guan, Yong-jun Ma, Jian-ying Song, Wei Cancer Cell Int Primary Research BACKGROUND: Evidence is increasingly indicating that circular RNAs (circRNAs) are closely involved in tumorigenesis and cancer progression. However, the function of circRNAs in gastric cancer (GC) are still unknown. Here, we aimed to determine the regulatory mechanism of circRNAs in GC. METHODS: Expression profiles of circRNAs were downloaded from four Gene Expression Omnibus (GEO) microarray datasets. Expression profiles of miRNAs and mRNAs were collected from The Cancer Genome Atlas (TCGA) database. We used the robust rank aggregation method to identify differentially expressed circRNAs (DEcircRNAs) and a ceRNA network was constructed based on circRNA–miRNA pairs and miRNA–mRNA pairs. Functional and pathway enrichment analyses were performed and interactions between proteins were predicted using Cytoscape. Aa subnetwork regulatory module was built using the MCODE plugin. RESULTS: A total of eight DEcircRNAs, 240 DEmiRNAs, and 4578 DEmRNAs were identified. The circRNA–miRNA–mRNA network was constructed based on seven circRNAs, 33 miRNAs, 69 mRNAs in GC. GO and KEGG pathway analysis indicated DEmRNAs might be associated with GC onset and progression. A PPI network was established and four hub genes (MCM4, KIF23, MCM8, and NCAPD2) were determined from the network. Then a circRNA–miRNA-hub gene subnetwork was constructed based on the four DEcircRNAs, three DEmiRNAs, and four DEmRNAs. CONCLUSIONS: Our findings provide a deeper understanding the circRNA-related competing endogenous RNA regulatory mechanism in GC pathogenesis. BioMed Central 2019-07-16 /pmc/articles/PMC6636116/ /pubmed/31346318 http://dx.doi.org/10.1186/s12935-019-0905-z Text en © The Author(s) 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Primary Research
Guan, Yong-jun
Ma, Jian-ying
Song, Wei
Identification of circRNA–miRNA–mRNA regulatory network in gastric cancer by analysis of microarray data
title Identification of circRNA–miRNA–mRNA regulatory network in gastric cancer by analysis of microarray data
title_full Identification of circRNA–miRNA–mRNA regulatory network in gastric cancer by analysis of microarray data
title_fullStr Identification of circRNA–miRNA–mRNA regulatory network in gastric cancer by analysis of microarray data
title_full_unstemmed Identification of circRNA–miRNA–mRNA regulatory network in gastric cancer by analysis of microarray data
title_short Identification of circRNA–miRNA–mRNA regulatory network in gastric cancer by analysis of microarray data
title_sort identification of circrna–mirna–mrna regulatory network in gastric cancer by analysis of microarray data
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6636116/
https://www.ncbi.nlm.nih.gov/pubmed/31346318
http://dx.doi.org/10.1186/s12935-019-0905-z
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