Identification of Functional Gene Modules and Biomarkers of Apatinib Against Lung Adenocarcinoma Based on Weighted Gene Co-expression Network Ansalysis (WGCNA)

Objective: Apatinib is a drug for the treatment of gastric cancer. In recent years, studies have found that it also has good efficacy in lung adenocarcinoma, but its mechanism action still not clear. Therefore, this study uses bioinformatics and Experimental verification explores apatinib adenocarcinoma. To explore potential biological targets against adenocarcinoma based on weighted gene co-expression network analysis (WGCNA). Methods: The PharmMapper server was first used to reversely predict apatinib. Subsequently, combined with WGCNA mine GSE10072 data set GEO database National Center Biotechnology Information (NCBI) obtain co-expressed module. Next, Predict target matching mapping anti-lung STRING Cytoscape software visualize protein interaction apatinib's perform topology analysis, as well core from network. Kaplan Meier plotter applied analyze relationship between key genes prognosis patients Molecular docking technology Anti-lung finally verified by molecular interaction. Finally, Western blot employed expression level protein. Results: A total 300 were obtained, 50 screened. From included CASP3, EGFR, MMP9, SRC, CASP8, CASP9, STAT3 MAPK1. High MAPK1 STAT3, low CASP9 MMP9 closely related poor showed MAPK1, comparable positive control. increasing concentration, down-regulated, CASP8 up-regulated. Conclusion: mainly through regulation signal transduction pathway apoptosis pathway, which provides scientific basis mechanism.