Literature DB >> 31264215

Gene coexpression analysis offers important modules and pathway of human lung adenocarcinomas.

Zhongheng Wei1, Tan Zhongqiu1, Shuxiong Lu2, Fang Zhang3, Wei Xie4, Ying Wang5.   

Abstract

Lung adenocarcinomas injured greatly on the people worldwide. Although clinic experiments and gene profiling analyses had been well performed, to our knowledge, systemic coexpression analysis of human genes for this cancer is still limited to date. Here, using the published data GSE75037, we built the coexpression modules of genes by Weighted Gene Co-Expression Network Analysis (WGCNA), and investigated function and protein-protein interaction network of coexpression genes by Database for Annotation, visualization, and Integrated Discovery (DAVID) and String database, respectively. First, 11 coexpression modules were conducted for 5,000 genes in the 83 samples recently. Number of genes for each module ranged from 90 to 1,260, with the mean of 454. Second, interaction relationships of hub-genes between pairwise modules showed great differences, suggesting relatively high scale independence of the modules. Third, functional enrichment of the coexpression modules showed great differences. We found that genes in modules 8 significantly enriched in the biological process and/or pathways of cell adhesion, extracellular matrix (ECM)-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway, and so forth. It was inferred as the key module underlying lung adenocarcinomas. Furthermore, PPI analysis revealed that the genes COL1A1, COL1A2, COL3A1, CTGF, and BGN owned the largest number of adjacency genes, unveiling that they may functioned importantly during the occurrence of lung adenocarcinomas. To summary, genes involved in cell adhesion, ECM-receptor interaction, focal adhesion, and PI3K-Akt signaling pathway play crucial roles in human lung adenocarcinomas.
© 2019 Wiley Periodicals, Inc.

Entities:  

Keywords:  coexpression modules; function; lung adenocarcinomas; network

Year:  2019        PMID: 31264215     DOI: 10.1002/jcp.28985

Source DB:  PubMed          Journal:  J Cell Physiol        ISSN: 0021-9541            Impact factor:   6.384


  7 in total

1.  Weighted Gene Co-Expression Network Analysis (WGCNA) Reveals the Functions of Syndecan-1 to Regulate Immune Infiltration by Influenced T Cells in Glioma.

Authors:  Jiacheng Zhong; Shuang Shi; Wen Peng; Bei Liu; Biao Yang; Wenyong Niu; Biao Zhang; Chuan Qin; Dong Zhong; Hongjuan Cui; Zhengbao Zhang; Xiaochuan Sun
Journal:  Front Genet       Date:  2022-05-20       Impact factor: 4.772

2.  Bioinformatics Identification of Key Genes for the Development and Prognosis of Lung Adenocarcinoma.

Authors:  Xuan Luo; Jian Guo Xu; ZhiYuan Wang; XiaoFang Wang; QianYing Zhu; Juan Zhao; Li Bian
Journal:  Inquiry       Date:  2022 Jan-Dec       Impact factor: 2.099

3.  Identification of Hub Genes as Biomarkers Correlated with the Proliferation and Prognosis in Lung Cancer: A Weighted Gene Co-Expression Network Analysis.

Authors:  Xuting Xu; Limin Xu; Huilian Huang; Jing Li; Shunli Dong; Lili Jin; Zhihong Ma; Liqin Li
Journal:  Biomed Res Int       Date:  2020-06-10       Impact factor: 3.411

4.  Identification of a Potentially Functional microRNA-mRNA Regulatory Network in Lung Adenocarcinoma Using a Bioinformatics Analysis.

Authors:  Xiao-Jun Wang; Jing Gao; Zhuo Wang; Qin Yu
Journal:  Front Cell Dev Biol       Date:  2021-02-18

5.  Weighted gene co-expression network analysis of hub genes in lung adenocarcinoma.

Authors:  Xuan Luo; Lei Feng; WenBo Xu; XueJing Bai; MengNa Wu
Journal:  Evol Bioinform Online       Date:  2021-04-12       Impact factor: 1.625

6.  Identification of Novel Biomarkers Related to Lung Squamous Cell Carcinoma Using Integrated Bioinformatics Analysis.

Authors:  Haiyan Wang; Lizhi Huang; Li Chen; Jing Ji; Yuanyuan Zheng; Zhen Wang
Journal:  Comput Math Methods Med       Date:  2021-10-08       Impact factor: 2.238

7.  Weighted Gene Co-expression Network Analysis Revealed That CircMARK3 Is a Potential CircRNA Affects Fat Deposition in Buffalo.

Authors:  Xue Feng; Jinhui Zhao; Fen Li; Bandar Hamad Aloufi; Ahmed Mohajja Alshammari; Yun Ma
Journal:  Front Vet Sci       Date:  2022-07-07
  7 in total

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