Identification of key genes involved in the pathogenesis of cutaneous melanoma using bioinformatics analysis

被引:6
|
作者
Chen, Jianqin [1 ]
Sun, Wen [2 ]
Mo, Nian [1 ]
Chen, Xiangjun [1 ]
Yang, Lihong [3 ]
Tu, Shaozhong [4 ]
Zhang, Siwen [1 ]
Liu, Jing [3 ]
机构
[1] Guangzhou Univ Chinese Med, Guangzhou, Peoples R China
[2] First Peoples Hosp Jingmen, Dept Dermatol, Jingmen, Peoples R China
[3] Guangzhou Univ Chinese Med, Affiliated Hosp 1, Dept Dermatol, 16 Airport Rd, Guangzhou 510000, Guangdong, Peoples R China
[4] Beijing Univ Chinese Med, Shenzhen Hosp, Dept Dermatol, Shenzhen, Peoples R China
基金
中国国家自然科学基金;
关键词
Melanoma; bioinformatics; biomarkers; genes; Gene Expression Omnibus; protein-protein interactions; G-PROTEIN; CDC20; OVEREXPRESSION; EXPRESSION; APOPTOSIS; SURVIVAL; INSIGHTS; PATHWAY; GROWTH;
D O I
10.1177/0300060519895867
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
Objective: Malignant melanoma is a highly invasive cancer whose pathogenesis remains unclear. We analyzed the microarray dataset GDS1375 in the Gene Expression Omnibus database to search for key genes involved in the occurrence and development of melanoma. Methods: The dataset included 52 samples (7 normal skin and 45 melanoma samples). We identified differentially expressed genes (DEGs) between the two groups and used integrated discovery databases for Gene Ontology (GO) and Kyoto Gene and Genome Encyclopedia (KEGG) pathway analyses. In addition, we used the STRING and MCODE plugins of Cytoscape to visualize the protein-protein interactions (PPI) for these DEGs. Results: A total of 509 upregulated and 618 downregulated DEGs were identified, which were enriched in GO terms including integrin binding, protein binding, and structural constituent of cytoskeleton, and in KEGG pathways such as melanogenesis, prostate cancer, focal adhesion, and renin secretion. Three major modules from the PPI networks and 10 hub genes were identified, including CDC20, GNB2, PPP2R1A, AURKB, POLR2E, and AGTR1. Overall survival was low when these six hub genes were highly expressed. Conclusion: This bioinformatics analysis identified hub genes that may promote the development of melanoma and represent potential new biomarkers for diagnosis and treatment of melanoma.
引用
收藏
页数:10
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