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

Peng Wang, Huaixin Zheng, Jiayu Zhang, Yashu Wang, Pingping Liu, Xiaoyan Xuan, Qianru Li, Ying Du
Author Information
  1. Peng Wang: Department of Immunology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, China.
  2. Huaixin Zheng: Department of Immunology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, China.
  3. Jiayu Zhang: State Key Laboratory of Membrane Biology, University of Chinese Academy of Science, Beijing, China.
  4. Yashu Wang: Department of Immunology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, China.
  5. Pingping Liu: Department of Immunology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, China.
  6. Xiaoyan Xuan: Department of Immunology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, China.
  7. Qianru Li: Department of Immunology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, China.
  8. Ying Du: Department of Immunology, School of Basic Medical Sciences, Zhengzhou University, Zhengzhou 450001, China.

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.

Keywords

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MeSH Term

Colorectal Neoplasms
Computational Biology
Databases, Genetic
Gene Expression Regulation, Neoplastic
Gene Ontology
Gene Regulatory Networks
Humans
Oligonucleotide Array Sequence Analysis

Word Cloud

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