Identification of 9 key genes and small molecule drugs in clear cell renal cell carcinoma

被引:54
|
作者
Luo, Yongwen [1 ]
Shen, Dexin [1 ]
Chen, Liang [1 ]
Wang, Gang [2 ,3 ,4 ]
Liu, Xuefeng [5 ]
Qian, Kaiyu [2 ,3 ]
Xiao, Yu [1 ,2 ,3 ,4 ]
Wang, Xinghuan [1 ,6 ]
Ju, Lingao [2 ,3 ]
机构
[1] Wuhan Univ, Zhongnan Hosp, Dept Urol, Wuhan, Hubei, Peoples R China
[2] Wuhan Univ, Zhongnan Hosp, Dept Biol Repositories, Wuhan, Hubei, Peoples R China
[3] Human Genet Resource Preservat Ctr Hubei Prov, Wuhan, Hubei, Peoples R China
[4] Wuhan Univ, Zhongnan Hosp, Lab Precis Med, Wuhan, Hubei, Peoples R China
[5] Georgetown Univ, Sch Med, Lombardi Comprehens Canc Ctr, Dept Pathol, Washington, DC 20007 USA
[6] Wuhan Univ, Med Res Inst, Wuhan, Hubei, Peoples R China
来源
AGING-US | 2019年 / 11卷 / 16期
关键词
clear cell renal cell carcinoma (ccRCC); biomarker; Weighted Gene Co-expression Network Analysis (WGCNA); Gene Set Enrichment Analysis (GSEA); BREAST-CANCER; EXPRESSION LEVELS; TRIFLUOPERAZINE; PROGNOSIS; GROWTH; CEP55; PROGRESSION; INHIBITION; APOPTOSIS; SURVIVIN;
D O I
10.18632/aging.102161
中图分类号
Q2 [细胞生物学];
学科分类号
071009 ; 090102 ;
摘要
Clear cell renal cell carcinoma (ccRCC) is a heterogeneous tumor that the underlying molecular mechanisms are largely unclear. This study aimed to elucidate the key candidate genes and pathways in ccRCC by integrated bioinformatics analysis. 1387 differentially expressed genes were identified based on three expression profile datasets, including 673 upregulated genes and 714 downregulated genes. Then we used weighted correlation network analysis to identify 6 modules associated with pathological stage and grade, blue module was the most relevant module. GO and KEGG pathway analyses showed that genes in blue module were enriched in cell cycle and metabolic related pathways. Further, 25 hub genes in blue module were identified as hub genes. Based on GEPIA database, 9 genes were associated with progression and prognosis of ccRCC patients, including PTTG1, RRM2, TOP2A, UHRF1, CEP55, BIRC5, UBE2C, FOXM1 and CDC20. Then multivariate Cox regression showed that the risk score base on 9 key genes signature was a clinically independent prognostic factor for ccRCC patients. Moreover, we screened out several new small molecule drugs that have the potential to treat ccRCC. Few of them were identified as biomarkers in ccRCC. In conclusion, our research identified 9 potential prognostic genes and several candidate small molecule drugs for ccRCC treatment.
引用
收藏
页码:6029 / 6052
页数:24
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