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pmid:35693937

Identification of Hub Genes in Colorectal Adenocarcinoma by Integrated Bioinformatics.

Yang Liu · Lanlan Chen · Xiangbo Meng · Shujun Ye · Lianjun Ma

Frontiers in cell and developmental biology · 2022 doi:10.3389/fcell.2022.897568

Paper

complete

Experiment

complete

Data

partial

Analysis

partial

Execution

absent

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title
Identification of Hub Genes in Colorectal Adenocarcinoma by Integrated Bioinformatics.
doi
10.3389/fcell.2022.897568
pmid
35693937
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Yang Liu
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Lanlan Chen
[2]
Xiangbo Meng
[3]
Shujun Ye
[4]
Lianjun Ma
journal
Frontiers in cell and developmental biology
year
2022
abstract
An improved understanding of the molecular mechanism of colorectal adenocarcinoma is necessary to predict the prognosis and develop new target gene therapy strategies. This study aims to identify hub genes associated with colorectal adenocarcinoma and further analyze their prognostic significance. In this study, The Cancer Genome Atlas (TCGA) COAD-READ database and the gene expression profiles of GSE25070 from the Gene Expression Omnibus were collected to explore the differentially expressed genes between colorectal adenocarcinoma and normal tissues. The weighted gene co-expression network analysis (WGCNA) and differential expression analysis identified 82 differentially co-expressed genes in the collected datasets. Enrichment analysis was applied to explore the regulated signaling pathway in colorectal adenocarcinoma. In addition, 10 hub genes were identified in the protein-protein interaction (PPI) network by using the cytoHubba plug-in of Cytoscape, where five genes were further proven to be significantly related to the survival rate. Compared with normal tissues, the expressions of the five genes were both downregulated in the GSE110224 dataset. Subsequently, the expression of the five hub genes was confirmed by the Human Protein Atlas database. Finally, we used Cox regression analysis to identify genes associated with prognosis, and a 3-gene signature (CLCA1-CLCA4-GUCA2A) was constructed to predict the prognosis of patients with colorectal cancer. In conclusion, our study revealed that the five hub genes and CLCA1-CLCA4-GUCA2A signature are highly correlated with the development of colorectal adenocarcinoma and can serve as promising prognosis factors to predict the overall survival rate of patients.
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In this study, WGCNA and differential gene expression analysis was performed to analyze the mRNA expression data of COAD-READ in TCGA and GEO databases, and the differentially co-expressed genes were obtained.
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In this study, WGCNA and differential gene expression analysis was performed to analyze the mRNA expression data of COAD-READ in TCGA and GEO databases, and the differentially co-expressed genes were obtained.
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Integrating weighted gene co-expression network analysis and differential gene expression analysis identified five survival-related hub genes and a three-gene prognostic signature for colorectal adenocarcinoma.
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In conclusion, our study revealed that the five hub genes and CLCA1–CLCA4–GUCA2A signature are highly correlated with the development of colorectal adenocarcinoma and can serve as promising prognosis factors to predict the overall survival rate of patients.
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Integrating weighted gene co-expression network analysis and differential gene expression analysis identified five survival-related hub genes and a three-gene prognostic signature for colorectal adenocarcinoma.
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This study aims to identify hub genes associated with colorectal adenocarcinoma and further analyze their prognostic significance. In this study, The Cancer Genome Atlas (TCGA) COAD-READ database and the gene expression profiles of GSE25070 from the Gene Expression Omnibus were collected to explore the differentially expressed genes between colorectal adenocarcinoma and normal tissues. The weighted gene co-expression network analysis (WGCNA) and differential expression analysis identified 82 differentially co-expressed genes in the collected datasets. Enrichment analysis was applied to explore the regulated signaling pathway in colorectal adenocarcinoma. In addition, 10 hub genes were identified in the protein-protein interaction (PPI) network by using the cytoHubba plug-in of Cytoscape, where five genes were further proven to be significantly related to the survival rate. Compared with normal tissues, the expressions of the five genes were both downregulated in the GSE110224 dataset. Subsequently, the expression of the five hub genes was confirmed by the Human Protein Atlas database. Finally, we used Cox regression analysis to identify genes associated with prognosis, and a 3-gene signature (CLCA1-CLCA4-GUCA2A) was constructed to predict the prognosis of patients with colorectal cancer. 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