A comprehensive analysis of WGCNA and serum metabolomics manifests the lung cancer-associated disordered glucose metabolism.
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.
['Ding|Mingchao|M|0000-0001-9647-6887', 'Li|Fang|F|', 'Wang|Bin|B|', 'Chi|Guoqing|G|', 'Liu|Hao|H|']
D001271:Atlases as Topic D016000:Cluster Analysis D030541:Databases, Genetic D020869:Gene Expression Profiling D015972:Gene Expression Regulation, Neoplastic D063990:Gene Ontology D053263:Gene Regulatory Networks D005943:Gluconeogenesis D005947:Glucose D006019:Glycolysis D006801:Humans D008175:Lung Neoplasms D055432:Metabolomics D058977:Molecular Sequence Annotation D009363:Neoplasm Proteins D059467:Transcriptome
metabolomics glucose metabolism lung cancer weighted gene coexpression network analysis