基于生物信息学分析鉴定促进非小细胞肺癌耐药的关键基因.

Objective To analyze the gene expression profiles of gefitinib-sensitive and drug-resistant non-small cell lung cancer (NSCLC) cells in GEO database by bioinformatics, to study the potential key genes leading to acquired drug resistance of NSCLC, and to provide new ideas for the prognosis evaluation of patients with drug-resistant NSCLC. Methods The GEO2R network tool was used to analyze the GSE123066 and GSE83666 data sets to identify differentially expressed genes (DEGs). The key candidate genes were identified by comparing the DEGs between the two groups of data through the Wayne diagram, and then GO analysis. KEGG analysis and protein-protein interaction (PPI) analysis were performed on the candidate genes. The clinical prognosis analysis and expression level analysis of tumor tissues and different stages were performed on the obtained genes. Results A total of 46 core DEGs were significantly associated with drug-resistant NSCLC. Cytoscape identified eight key genes that play an important role in the progression of gefitinib resistance in NSCLC cells, namely SOD2, GADD45A, NCF2, LOX, CYR61, SOX2, JUP and MUC1, respectively. Among them, SOD2 was highly correlated with gefitinib resistance in NSCLC. Conclusion SOD2 may be the key genes leading to acquired drug resistance of NSCLC cells to gefitinib, and their high expression is associated with poor prognosis of NSCLC, indicating that SOD2 may be potential therapeutic targets with clinical application value in the future. [ABSTRACT FROM AUTHOR]