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A comprehensive analysis of WGCNA and serum metabolomics manifests the lung cancer‐associated disordered glucose metabolism
Author(s) -
Ding Mingchao,
Li Fang,
Wang Bin,
Chi Guoqing,
Liu Hao
Publication year - 2019
Publication title -
journal of cellular biochemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.028
H-Index - 165
eISSN - 1097-4644
pISSN - 0730-2312
DOI - 10.1002/jcb.28377
Subject(s) - lung cancer , biology , carcinogenesis , metabolomics , transcriptome , computational biology , disease , gene , cancer , bioinformatics , cancer research , genetics , oncology , medicine , gene expression
Lung cancer is a worldwide disease and highly heterogeneous at a molecular level. In this study, we both performed the pathway enrichment analysis and the transcriptome‐based weighted gene coexpression network analysis (WGCNA) so as to find the critical pathways involved in lung cancer. Our analysis results indicated that genes in viability modules (0 < Z‐summary < 2) selected by WGCNA were more reliable for identifying crucial pathways, while gene enrichment analysis provided a wide range of pathways with a little emphasis on target pathways for lung cancer. On the basis of genes, which were classified into various modules by WGCNA, we found a significant aberration of glucose metabolism in lung cancer cells, demonstrating that the glucose metabolism has been perturbed, especially the glycolysis pathway. Our study revealed that disordered glucose metabolism might be closely associated with the carcinogenesis of lung cancer based on the integrated analysis of WGCNA and metabolomics, which could be a potential therapeutic target for lung cancer.