Identification of candidate genes and pathways in cisplatin-resistant NSCLC by integrated bioinformatics analysis

Cisplatin resistance is a main barrier in the treatment of non-small cell lung cancer (NSCLC), but the underlying mechanisms remain poorly understood. This study analyzed transcriptome data in cisplatin-resistant NSCLC cells and identified differentially expressed genes (DEGs), which were further subjected to gene ontology (GO) and pathway enrichment analysis, protein-protein interaction network establishment and survival analysis. A total of 235 DEGs (99 up-regulated and 136 down-regulated) were identified from the GSE21656 dataset. PPI network identified 9 hub genes correlated significantly with patient's prognosis. In conclusion, this study identified candidate genes and pathways associated with the development of cisplatin resistance. These findings provide potential targets for improving efficacy of cisplatin-based chemotherapy in NSCLC patients.