Cargando…
Construction and Analysis of the Tumor-Specific mRNA–miRNA–lncRNA Network in Gastric Cancer
Weighted correlation network analysis (WGCNA) is a statistical method that has been widely used in recent years to explore gene co-expression modules. Competing endogenous RNA (ceRNA) is commonly involved in the cancer gene expression regulation mechanism. Some ceRNA networks are recognized in gastr...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7396639/ https://www.ncbi.nlm.nih.gov/pubmed/32848739 http://dx.doi.org/10.3389/fphar.2020.01112 |
_version_ | 1783565629008117760 |
---|---|
author | Zheng, Xiaohao Wang, Xiaohui Zheng, Li Zhao, Hao Li, Wenbin Wang, Bingzhi Xue, Liyan Tian, Yantao Xie, Yibin |
author_facet | Zheng, Xiaohao Wang, Xiaohui Zheng, Li Zhao, Hao Li, Wenbin Wang, Bingzhi Xue, Liyan Tian, Yantao Xie, Yibin |
author_sort | Zheng, Xiaohao |
collection | PubMed |
description | Weighted correlation network analysis (WGCNA) is a statistical method that has been widely used in recent years to explore gene co-expression modules. Competing endogenous RNA (ceRNA) is commonly involved in the cancer gene expression regulation mechanism. Some ceRNA networks are recognized in gastric cancer; however, the prognosis-associated ceRNA network has not been fully identified using WGCNA. We performed WGCNA using datasets from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) to identify cancer-associated modules. The criteria of differentially expressed RNAs between normal stomach samples and gastric cancer samples were set at the false discovery rate (FDR) < 0.01 and |fold change (FC)| > 1.3. The ceRNA relationships obtained from the RNAinter database were examined by both the Pearson correlation test and hypergeometric test to confirm the mRNA–lncRNA regulation. Overlapped genes were recognized at the intersections of genes predicted by ceRNA relationships, differentially expressed genes, and genes in cancer-specific modules. These were then used for univariate and multivariate Cox analyses to construct a risk score model. The ceRNA network was constructed based on the genes in this model. WGCNA-uncovered genes in the green and turquoise modules are those most associated with gastric cancer. Eighty differentially expressed genes were observed to have potential prognostic value, which led to the identification of 12 prognosis-related mRNAs (KIF15, FEN1, ZFP69B, SP6, SPARC, TTF2, MSI2, KYNU, ACLY, KIF21B, SLC12A7, and ZNF823) to construct a risk score model. The risk genes were validated using the GSE62254 and GSE84433 datasets, with 0.82 as the universal cutoff value. 12 genes, 12 lncRNAs, and 35 miRNAs were used to build a ceRNA network with 86 dysregulated lncRNA–mRNA ceRNA pairs. Finally, we developed a 12-gene signature from both prognosis-related and tumor-specific genes, and then constructed a ceRNA network in gastric cancer. Our findings may provide novel insights into the treatment of gastric cancer. |
format | Online Article Text |
id | pubmed-7396639 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-73966392020-08-25 Construction and Analysis of the Tumor-Specific mRNA–miRNA–lncRNA Network in Gastric Cancer Zheng, Xiaohao Wang, Xiaohui Zheng, Li Zhao, Hao Li, Wenbin Wang, Bingzhi Xue, Liyan Tian, Yantao Xie, Yibin Front Pharmacol Pharmacology Weighted correlation network analysis (WGCNA) is a statistical method that has been widely used in recent years to explore gene co-expression modules. Competing endogenous RNA (ceRNA) is commonly involved in the cancer gene expression regulation mechanism. Some ceRNA networks are recognized in gastric cancer; however, the prognosis-associated ceRNA network has not been fully identified using WGCNA. We performed WGCNA using datasets from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression (GTEx) to identify cancer-associated modules. The criteria of differentially expressed RNAs between normal stomach samples and gastric cancer samples were set at the false discovery rate (FDR) < 0.01 and |fold change (FC)| > 1.3. The ceRNA relationships obtained from the RNAinter database were examined by both the Pearson correlation test and hypergeometric test to confirm the mRNA–lncRNA regulation. Overlapped genes were recognized at the intersections of genes predicted by ceRNA relationships, differentially expressed genes, and genes in cancer-specific modules. These were then used for univariate and multivariate Cox analyses to construct a risk score model. The ceRNA network was constructed based on the genes in this model. WGCNA-uncovered genes in the green and turquoise modules are those most associated with gastric cancer. Eighty differentially expressed genes were observed to have potential prognostic value, which led to the identification of 12 prognosis-related mRNAs (KIF15, FEN1, ZFP69B, SP6, SPARC, TTF2, MSI2, KYNU, ACLY, KIF21B, SLC12A7, and ZNF823) to construct a risk score model. The risk genes were validated using the GSE62254 and GSE84433 datasets, with 0.82 as the universal cutoff value. 12 genes, 12 lncRNAs, and 35 miRNAs were used to build a ceRNA network with 86 dysregulated lncRNA–mRNA ceRNA pairs. Finally, we developed a 12-gene signature from both prognosis-related and tumor-specific genes, and then constructed a ceRNA network in gastric cancer. Our findings may provide novel insights into the treatment of gastric cancer. Frontiers Media S.A. 2020-07-21 /pmc/articles/PMC7396639/ /pubmed/32848739 http://dx.doi.org/10.3389/fphar.2020.01112 Text en Copyright © 2020 Zheng, Wang, Zheng, Zhao, Li, Wang, Xue, Tian and Xie http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Pharmacology Zheng, Xiaohao Wang, Xiaohui Zheng, Li Zhao, Hao Li, Wenbin Wang, Bingzhi Xue, Liyan Tian, Yantao Xie, Yibin Construction and Analysis of the Tumor-Specific mRNA–miRNA–lncRNA Network in Gastric Cancer |
title | Construction and Analysis of the Tumor-Specific mRNA–miRNA–lncRNA Network in Gastric Cancer |
title_full | Construction and Analysis of the Tumor-Specific mRNA–miRNA–lncRNA Network in Gastric Cancer |
title_fullStr | Construction and Analysis of the Tumor-Specific mRNA–miRNA–lncRNA Network in Gastric Cancer |
title_full_unstemmed | Construction and Analysis of the Tumor-Specific mRNA–miRNA–lncRNA Network in Gastric Cancer |
title_short | Construction and Analysis of the Tumor-Specific mRNA–miRNA–lncRNA Network in Gastric Cancer |
title_sort | construction and analysis of the tumor-specific mrna–mirna–lncrna network in gastric cancer |
topic | Pharmacology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7396639/ https://www.ncbi.nlm.nih.gov/pubmed/32848739 http://dx.doi.org/10.3389/fphar.2020.01112 |
work_keys_str_mv | AT zhengxiaohao constructionandanalysisofthetumorspecificmrnamirnalncrnanetworkingastriccancer AT wangxiaohui constructionandanalysisofthetumorspecificmrnamirnalncrnanetworkingastriccancer AT zhengli constructionandanalysisofthetumorspecificmrnamirnalncrnanetworkingastriccancer AT zhaohao constructionandanalysisofthetumorspecificmrnamirnalncrnanetworkingastriccancer AT liwenbin constructionandanalysisofthetumorspecificmrnamirnalncrnanetworkingastriccancer AT wangbingzhi constructionandanalysisofthetumorspecificmrnamirnalncrnanetworkingastriccancer AT xueliyan constructionandanalysisofthetumorspecificmrnamirnalncrnanetworkingastriccancer AT tianyantao constructionandanalysisofthetumorspecificmrnamirnalncrnanetworkingastriccancer AT xieyibin constructionandanalysisofthetumorspecificmrnamirnalncrnanetworkingastriccancer |