Weighted Gene Co-Expression Network Analysis and Treatment Strategies of Tumor Recurrence-Associated Hub Genes in Lung Adenocarcinoma

Despite the recent progress of lung adenocarcinoma (LUAD) therapy, tumor recurrence remained to be a challenging factor that impedes the effectiveness of treatment. The objective of the present study was to predict the hub genes affecting LUAD recurrence via weighted gene co-expression network analysis (WGCNA). Microarray samples from LUAD dataset of GSE32863 were analyzed, and the modules with the highest correlation to tumor recurrence were selected. Functional enrichment analysis was conducted, followed by establishment of a protein-protein interaction (PPI) network. Subsequently, hub genes were identified by overall survival analyses and further validated by evaluation of expression in both myeloid populations and tissue samples of LUAD. Gene set enrichment analysis (GSEA) was then carried out, and construction of transcription factors (TF)-hub gene and drug-hub gene interaction network was also achieved. A total of eight hub genes (ACTR3, ARPC5, RAB13, HNRNPK, PA2G4, WDR12, SRSF1, and NOP58) were finally identified to be closely correlated with LUAD recurrence. In addition, TFs that regulate hub genes have been predicted, including MYC, PML, and YY1. Finally, drugs including arsenic trioxide, cisplatin, Jinfukang, and sunitinib were mined for the treatment of the eight hub genes. In conclusion, our study may facilitate the invention of targeted therapeutic drugs and shed light on the understanding of the mechanism for LUAD recurrence.

Automated summary

This study aimed to predict hub genes affecting LUAD recurrence using weighted gene co-expression network analysis. Through analysis of microarray samples, a protein-protein interaction network was established, and eight hub genes closely related to LUAD recurrence were identified. Transcription factors regulating these hub genes were predicted, and drugs for treating these genes were explored.