Identification of KIF18B as a Hub Candidate Gene in the Metastasis of Clear Cell Renal Cell Carcinoma by Weighted Gene Co-expression Network Analysis

被引:12
作者
Yang, Huiying [1 ]
Wang, Yukun [2 ]
Zhang, Ziyi [3 ]
Li, Hua [1 ]
机构
[1] Zhejiang Univ, Sch Med, Sir Run Run Shaw Hosp, Dept Nephrol, Hangzhou, Peoples R China
[2] Zhejiang Univ, Sir Run Run Shaw Hosp, Dept Urol, Sch Med, Hangzhou, Peoples R China
[3] Zhejiang Univ, Sir Run Run Shaw Hosp, Dept Endocrinol, Sch Med, Hangzhou, Peoples R China
关键词
clear cell renal cell carcinoma; weighted gene co-expression network analysis; enrichment analysis; maximal clique centrality; survival analysis; precise therapies; sing-gene gene set enrichment analysis; MOTOR PROTEINS; ASSOCIATION; PROGRESSION; GUIDELINES; EXPRESSION; PATHWAY;
D O I
10.3389/fgene.2020.00905
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Background Clear cell renal cell carcinoma (ccRCC) is a common type of fatal malignancy in the urinary system. As the therapeutic strategies of ccRCC are severely limited at present, the prognosis of patients with metastatic carcinoma is usually not promising. Revealing the pathogenesis and identifying hub candidate genes for prognosis prediction and precise treatment are urgently needed in metastatic ccRCC. Methods In the present study, we conducted a series of bioinformatics studies with the gene expression profiles of ccRCC samples from Gene Expression Omnibus (GEO) and the cancer genome atlas (TCGA) database for identifying and validating the hub gene of metastatic ccRCC. We constructed a co-expression network, divided genes into co-expression modules, and identified ccRCC-related modules by weighted gene co-expression network analysis (WGCNA) with data from GEO. Then, we investigated the functions of genes in the ccRCC-related modules by enrichment analyses and built a sub-network accordingly. A hub candidate gene of the metastatic ccRCC was identified by maximal clique centrality (MCC) method. We validate the hub gene by differentially expressed gene analysis, overall survival analysis, and correlation analysis with clinical traits with the external dataset (TCGA). Finally, we explored the function of the hub gene by correlation analysis with targets of precise therapies and single-gene gene set enrichment analysis. Results We conducted WGCNA with the expression profiles of GSE73731 from GEO and divided all genes into 8 meaningful co-expression modules. One module is proved to be positively correlated with pathological stage and tumor grade of ccRCC. Genes in the ccRCC-related module were mainly enriched in functions of mitotic cell division and several proverbial tumor related signal pathways. We then identifiedKIF18Bas a hub gene of the metastasis of ccRCC. Validating analyses in external dataset observed the up-regulation ofKIF18Bin ccRCC and its correlation with worse outcomes. Further analyses found that the expression of KIF18B is related to that of targets of precise therapies. Conclusion Our study proposedKIF18Bas a hub candidate gene of ccRCC for the first time. Our conclusion may provide a brand-new clue for prognosis evaluating and precise treatment for ccRCC in the future.
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页数:13
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