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