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Identification of key gene modules and genes in colorectal cancer by co-expression analysis weighted gene co-expression network analysis.

ABSTRACT: Colorectal cancer (CRC) has been one of the most common malignancies worldwide, which tends to get worse for the growth and aging of the population and westernized lifestyle. However, there is no effective treatment due to the complexity of its etiology. Hence, the pathogenic mechanisms remain to be clearly defined. In the present study, we adopted an advanced analytical method-Weighted Gene Co-expression Network Analysis (WGCNA) to identify the key gene modules and hub genes associated with CRC. In total, five gene co-expression modules were highly associated with CRC, of which, one gene module correlated with CRC significantly positive (R = 0.88). Functional enrichment analysis of genes in primary gene module found metabolic pathways, which might be a potentially important pathway involved in CRC. Further, we identified and verified some hub genes positively correlated with CRC by using Cytoscape software and UALCAN databases, including PAICS, ATR, AASDHPPT, DDX18, NUP107 and TOMM6. The present study discovered key gene modules and hub genes associated with CRC, which provide references to understand the pathogenesis of CRC and may be novel candidate target genes of CRC.

SUBMITTER: Wang P

PROVIDER: S-EPMC7463304 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Identification of key gene modules and genes in colorectal cancer by co-expression analysis weighted gene co-expression network analysis.

Wang Peng P Zheng Huaixin H Zhang Jiayu J Wang Yashu Y Liu Pingping P Xuan Xiaoyan X Li Qianru Q Du Ying Y

Bioscience reports 20200901 9

Colorectal cancer (CRC) has been one of the most common malignancies worldwide, which tends to get worse for the growth and aging of the population and westernized lifestyle. However, there is no effective treatment due to the complexity of its etiology. Hence, the pathogenic mechanisms remain to be clearly defined. In the present study, we adopted an advanced analytical method-Weighted Gene Co-expression Network Analysis (WGCNA) to identify the key gene modules and hub genes associated with CRC ...[more]

PMID: 32815531

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Dataset Information

Identification of key gene modules and genes in colorectal cancer by co-expression analysis weighted gene co-expression network analysis.

Publications

Identification of key gene modules and genes in colorectal cancer by co-expression analysis weighted gene co-expression network analysis.

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