The Construction and Analysis of Gene Co-Expression Network in Lung Cancer

Lung cancer, a complex molecular network disease, is a malignant tumor with the highest incidence and mortality around the world at present. In order to further understand the pathogenic molecular mechanism of lung cancer, we firstly identified differentially expressed gene (DEG) between cancer tissue and the corresponding adjacent normal tissue. Then, we used weighted gene co-expression network analysis (WGCNA) to screen for the DEG. In total, eight gene modules of DEG were detected and hub genes were identified. By calculating the Pearson’s correlation coefficient between module eigengene and sample traits, we obtained the blue module which was highly associated with lung cancer, and found the hub gene of blue module was carbonic anhydrase 4. Hub gene plays an important role in the blue module. By using Database for Annotation, Visualization and Integrated Discovery (DAVID), the Gene Ontology (GO) enrichment analysis and KEGG pathway analysis were performed for blue module. The analysis of GO showed that blue module played important roles in biological functions, such as regulation of Rho protein signal transduction, biological adhesion, and carbohydrate binding. The analysis of KEGG indicated that blue module took part in the pathways of axon guidance and O-Glycan biosynthesis. The results showed that high correlations modules of lung cancer and hub gene identified in this paper played a potentially important role in the development of lung cancer.