Integrated Bioinformatics Analysis to Identify Abnormal Methylated Differentially Expressed Genes for Predicting Prognosis of Human Colon Cancer
Yanbo Luo,1 Fenglin Sun,1 Xiaowen Peng,2 Dong Dong,3 Wentao Ou,3 Yongke Xie,3 Yuqi Luo1 1Department of Gastrointestinal and Hepatobiliary Surgery, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, Guangdong, People’s Republic of China; 2Department of Laboratory Medicine, Nansha Hospital,...
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doaj-03db5ac71e914c6caf6e738385a471f42021-08-24T20:06:34ZengDove Medical PressInternational Journal of General Medicine1178-70742021-08-01Volume 144745475668138Integrated Bioinformatics Analysis to Identify Abnormal Methylated Differentially Expressed Genes for Predicting Prognosis of Human Colon CancerLuo YSun FPeng XDong DOu WXie YLuo YYanbo Luo,1 Fenglin Sun,1 Xiaowen Peng,2 Dong Dong,3 Wentao Ou,3 Yongke Xie,3 Yuqi Luo1 1Department of Gastrointestinal and Hepatobiliary Surgery, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, Guangdong, People’s Republic of China; 2Department of Laboratory Medicine, Nansha Hospital, Guangzhou First People’s Hospital, School of Medicine, Southern China University of Technology, Guangzhou, Guangdong, 511457, People’s Republic of China; 3Department of General Surgery, Nansha Hospital, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, 511457, Guangdong, People’s Republic of ChinaCorrespondence: Yuqi LuoDepartment of Gastrointestinal and Hepatobiliary Surgery, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, Guangdong, People’s Republic of ChinaTel/Fax +86755-28015466Email eyluoyuqi@scut.edu.cnObjective: To identify the value of key differentially expressed genes (DEGs) regulated by differentially methylated regions (DMRs) in predicting the prognosis of human colon cancer.Materials and Methods: RNA sequencing data and DNA methylation data of 455 colon adenocarcinoma (COAD) cases and 41 normal controls were downloaded from The Cancer Genome Atlas (TCGA). Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by the DAVID database. To identify the hub genes regulated by methylation, univariate Cox and multivariate Cox regression analyses were carried out. A nomogram based on the risk score was built to identify the power of the hub genes to predict prognosis in patients with colon cancer.Results: A total of 133 DEGs regulated by DMRs were identified through analyzing RNA sequencing data and DNA methylation data from TCGA. GO functional enrichment and KEGG pathway enrichment analysis showed the genes involved in the initiation and progression of colon cancer. Univariate Cox regression analysis and multivariate Cox regression analysis focused on the seven hub genes (CDH4, CR2, KRT85, LGI4, NPAS4, RUVBL1 and SP140) associated with overall survival, the expression of which negatively correlated with their methylation level. The risk score and nomogram model showed that the hub genes served as potential biomarkers for the prognosis prediction of patients with colon cancer.Conclusion: Our findings suggest that the DEGs regulated by DMRs are involved in the carcinogenesis and development of colon cancer, and the aberrantly methylated DEGs associated with overall survival of patients may be potential diagnostic and therapeutic targets for colon cancer.Keywords: colon cancer, DNA methylation, gene expression regulation, prognosis predictionhttps://www.dovepress.com/integrated-bioinformatics-analysis-to-identify-abnormal-methylated-dif-peer-reviewed-fulltext-article-IJGMcolon cancerdna methylationgene expression regulationprognosis prediction |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Luo Y Sun F Peng X Dong D Ou W Xie Y Luo Y |
spellingShingle |
Luo Y Sun F Peng X Dong D Ou W Xie Y Luo Y Integrated Bioinformatics Analysis to Identify Abnormal Methylated Differentially Expressed Genes for Predicting Prognosis of Human Colon Cancer International Journal of General Medicine colon cancer dna methylation gene expression regulation prognosis prediction |
author_facet |
Luo Y Sun F Peng X Dong D Ou W Xie Y Luo Y |
author_sort |
Luo Y |
title |
Integrated Bioinformatics Analysis to Identify Abnormal Methylated Differentially Expressed Genes for Predicting Prognosis of Human Colon Cancer |
title_short |
Integrated Bioinformatics Analysis to Identify Abnormal Methylated Differentially Expressed Genes for Predicting Prognosis of Human Colon Cancer |
title_full |
Integrated Bioinformatics Analysis to Identify Abnormal Methylated Differentially Expressed Genes for Predicting Prognosis of Human Colon Cancer |
title_fullStr |
Integrated Bioinformatics Analysis to Identify Abnormal Methylated Differentially Expressed Genes for Predicting Prognosis of Human Colon Cancer |
title_full_unstemmed |
Integrated Bioinformatics Analysis to Identify Abnormal Methylated Differentially Expressed Genes for Predicting Prognosis of Human Colon Cancer |
title_sort |
integrated bioinformatics analysis to identify abnormal methylated differentially expressed genes for predicting prognosis of human colon cancer |
publisher |
Dove Medical Press |
series |
International Journal of General Medicine |
issn |
1178-7074 |
publishDate |
2021-08-01 |
description |
Yanbo Luo,1 Fenglin Sun,1 Xiaowen Peng,2 Dong Dong,3 Wentao Ou,3 Yongke Xie,3 Yuqi Luo1 1Department of Gastrointestinal and Hepatobiliary Surgery, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, Guangdong, People’s Republic of China; 2Department of Laboratory Medicine, Nansha Hospital, Guangzhou First People’s Hospital, School of Medicine, Southern China University of Technology, Guangzhou, Guangdong, 511457, People’s Republic of China; 3Department of General Surgery, Nansha Hospital, Guangzhou First People’s Hospital, School of Medicine, South China University of Technology, Guangzhou, 511457, Guangdong, People’s Republic of ChinaCorrespondence: Yuqi LuoDepartment of Gastrointestinal and Hepatobiliary Surgery, Shenzhen Longhua District Central Hospital, Shenzhen, 518110, Guangdong, People’s Republic of ChinaTel/Fax +86755-28015466Email eyluoyuqi@scut.edu.cnObjective: To identify the value of key differentially expressed genes (DEGs) regulated by differentially methylated regions (DMRs) in predicting the prognosis of human colon cancer.Materials and Methods: RNA sequencing data and DNA methylation data of 455 colon adenocarcinoma (COAD) cases and 41 normal controls were downloaded from The Cancer Genome Atlas (TCGA). Gene Ontology (GO) functional enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed by the DAVID database. To identify the hub genes regulated by methylation, univariate Cox and multivariate Cox regression analyses were carried out. A nomogram based on the risk score was built to identify the power of the hub genes to predict prognosis in patients with colon cancer.Results: A total of 133 DEGs regulated by DMRs were identified through analyzing RNA sequencing data and DNA methylation data from TCGA. GO functional enrichment and KEGG pathway enrichment analysis showed the genes involved in the initiation and progression of colon cancer. Univariate Cox regression analysis and multivariate Cox regression analysis focused on the seven hub genes (CDH4, CR2, KRT85, LGI4, NPAS4, RUVBL1 and SP140) associated with overall survival, the expression of which negatively correlated with their methylation level. The risk score and nomogram model showed that the hub genes served as potential biomarkers for the prognosis prediction of patients with colon cancer.Conclusion: Our findings suggest that the DEGs regulated by DMRs are involved in the carcinogenesis and development of colon cancer, and the aberrantly methylated DEGs associated with overall survival of patients may be potential diagnostic and therapeutic targets for colon cancer.Keywords: colon cancer, DNA methylation, gene expression regulation, prognosis prediction |
topic |
colon cancer dna methylation gene expression regulation prognosis prediction |
url |
https://www.dovepress.com/integrated-bioinformatics-analysis-to-identify-abnormal-methylated-dif-peer-reviewed-fulltext-article-IJGM |
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