Non-small cell lung cancer (NSCLC) is the most common type in lung cancer in the world, and it severely threatens the life of patients. Resveratrol has been reported to inhibit cancer. However, mechanisms of resveratrol inhibiting NSCLC were unclear. The aim of this study was to identify differentially expressed genes (DEGs) of NSCLC treated with resveratrol and reveal the potential targets of resveratrol in NSCLC. We obtained mRNA expression profiles of two datasets from the National Center for Biotechnology Information Gene Expression Omnibus (NCBI-GEO) and 271 DEGs were selected for further analysis. Data from STRING shown that 177 nodes and 342 edges were in the protein-protein interaction (PPI) network, and 10 hub genes (ANPEP, CD69, ITGAL, PECAM1, PTPRC, CD34, ITGA1, CCL2, SOX2, and EGFR) were identified by Cytoscape plus-in cytoHubba. Survival analysis revealed that NSCLC patients showing low expression of PECAM1, ANPEP, CD69, ITGAL, and PTPRC were associated with worse overall survival (OS) (P < 0.05), and high expression of SOX2 and EGFR was associated with worse OS for NSCLC patients (P < 0.05). Overall, we identified ANPEP, CD69, ITGAL, and PTPRC as potential candidate genes which were main effects of resveratrol on the treatment of NSCLC. ANPEP, ITGAL, CD69, and PTPRC are all clusters of differentiation (CD) antigens, might be the targets of resveratrol. The bioinformatic results suggested that the inhibitory effect of resveratrol on lung cancer may be related to the immune signaling pathway. Further studies are needed to validate these findings and to explore their functional mechanisms.