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

被引：0
|
作者：
Yu, Fang [1 ]
Fang, Chengtao [2 ]
Ren, Yinghong [1 ]
机构：
[1] Shangluo Cent Hosp, Dept Internal Med, 148 Beixin St, Shangluo 726000, Shaanxi, Peoples R China
[2] Shangluo Cent Hosp, Dept Cardiothorac Surg, Shangluo, Shaanxi, Peoples R China
来源：
INTERNATIONAL JOURNAL OF CLINICAL AND EXPERIMENTAL MEDICINE | 2019年 / 12卷 / 05期
关键词：
Lung cancer; cisplatin resistance; bioinformatics analysis; CELL LUNG-CANCER; GROWTH; OVEREXPRESSION; STATISTICS; EXPRESSION;
D O I：
暂无
中图分类号：
R-3 [医学研究方法]; R3 [基础医学];
学科分类号：
1001 ;
摘要：
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.
引用
收藏
页码：4912 / 4919
页数：8
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