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Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis

Gastric cancer is one of the common malignant tumors worldwide. Increasing studies have indicated that circular RNAs (circRNAs) play critical roles in the cancer progression and have shown great potential as useful markers and therapeutic targets. However, the precise mechanism and functions of most...

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Autores principales: Gu, Wei, Sun, Ying, Zheng, Xiong, Ma, Jin, Hu, Xiao-Ying, Gao, Tian, Hu, Mei-Jie
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5878900/
https://www.ncbi.nlm.nih.gov/pubmed/29744354
http://dx.doi.org/10.1155/2018/2381680
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author Gu, Wei
Sun, Ying
Zheng, Xiong
Ma, Jin
Hu, Xiao-Ying
Gao, Tian
Hu, Mei-Jie
author_facet Gu, Wei
Sun, Ying
Zheng, Xiong
Ma, Jin
Hu, Xiao-Ying
Gao, Tian
Hu, Mei-Jie
author_sort Gu, Wei
collection PubMed
description Gastric cancer is one of the common malignant tumors worldwide. Increasing studies have indicated that circular RNAs (circRNAs) play critical roles in the cancer progression and have shown great potential as useful markers and therapeutic targets. However, the precise mechanism and functions of most circRNAs are still unknown in gastric cancer. In the present study, we performed a microarray analysis to detect circRNA expression changes between tumor samples and adjacent nontumor samples. The miRNA expression profiles were obtained from the National Center of Biotechnology Information Gene Expression Omnibus (GEO). The differentially expressed circRNAs and miRNAs were identified through fold change filtering. The interactions between circRNAs and miRNAs were predicted by Arraystar's home-made miRNA target prediction software. After circRNA-related miRNAs and dysregulated miRNAs were intersected, 23 miRNAs were selected. The target mRNAs of miRNAs were predicted by TarBase v7.0. Gene ontology (GO) enrichment analysis and pathway analysis were performed using standard enrichment computational methods for the target mRNAs. The results of pathway analysis showed that p53 signaling pathway and hippo signal pathway were significantly enriched and CCND2 was a cross-talk gene associated with them. Finally, a circRNA-miRNA-mRNA regulation network was constructed based on the gene expression profiles and bioinformatics analysis results to identify hub genes and hsa_circRNA_101504 played a central role in the network.
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spelling pubmed-58789002018-05-09 Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis Gu, Wei Sun, Ying Zheng, Xiong Ma, Jin Hu, Xiao-Ying Gao, Tian Hu, Mei-Jie Biomed Res Int Research Article Gastric cancer is one of the common malignant tumors worldwide. Increasing studies have indicated that circular RNAs (circRNAs) play critical roles in the cancer progression and have shown great potential as useful markers and therapeutic targets. However, the precise mechanism and functions of most circRNAs are still unknown in gastric cancer. In the present study, we performed a microarray analysis to detect circRNA expression changes between tumor samples and adjacent nontumor samples. The miRNA expression profiles were obtained from the National Center of Biotechnology Information Gene Expression Omnibus (GEO). The differentially expressed circRNAs and miRNAs were identified through fold change filtering. The interactions between circRNAs and miRNAs were predicted by Arraystar's home-made miRNA target prediction software. After circRNA-related miRNAs and dysregulated miRNAs were intersected, 23 miRNAs were selected. The target mRNAs of miRNAs were predicted by TarBase v7.0. Gene ontology (GO) enrichment analysis and pathway analysis were performed using standard enrichment computational methods for the target mRNAs. The results of pathway analysis showed that p53 signaling pathway and hippo signal pathway were significantly enriched and CCND2 was a cross-talk gene associated with them. Finally, a circRNA-miRNA-mRNA regulation network was constructed based on the gene expression profiles and bioinformatics analysis results to identify hub genes and hsa_circRNA_101504 played a central role in the network. Hindawi 2018-03-18 /pmc/articles/PMC5878900/ /pubmed/29744354 http://dx.doi.org/10.1155/2018/2381680 Text en Copyright © 2018 Wei Gu et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Gu, Wei
Sun, Ying
Zheng, Xiong
Ma, Jin
Hu, Xiao-Ying
Gao, Tian
Hu, Mei-Jie
Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis
title Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis
title_full Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis
title_fullStr Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis
title_full_unstemmed Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis
title_short Identification of Gastric Cancer-Related Circular RNA through Microarray Analysis and Bioinformatics Analysis
title_sort identification of gastric cancer-related circular rna through microarray analysis and bioinformatics analysis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5878900/
https://www.ncbi.nlm.nih.gov/pubmed/29744354
http://dx.doi.org/10.1155/2018/2381680
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