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

Abstract

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 identified KIF18B as a hub gene of the metastasis of ccRCC. Validating analyses in external dataset observed the up-regulation of KIF18B in ccRCC and its correlation with worse outcomes. Further analyses found that the expression of KIF18B is related to that of targets of precise therapies.

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“…The other method was Maximal Que Centrality (MCC) algorithm [ 44 ] from plug-in cytoHubba in Cytoscape (Version 3.6.0) software [ 45 ]. The top ten genes ranked by MCC values were considered as hub candidates [ 46 , 47 , 48 , 49 ].…”

IQGAP3 May Serve as a Promising Biomarker in Clear Cell Renal Cell Carcinoma

“…KIF18B, a member of kinesin superfamily, has a long-reported significant effect on the onset and progression of cancer. 23 , 24 Wang et al 25 have identified KIF18B as a risk gene in the metastasis of ccRCC. HJURP, a histone H3 chaperone, was identified as a crucial factor in DNA binding and phosphorylation, which promotes chromosome segregation and cell mitosis.…”

Identification of Key Modules and Genes Associated with Major Depressive Disorder in Adolescents

“…Furthermore, we conducted module analysis using cythubba with the Maximal Que Centrality (MCC) method in Cytoscape (Version 3.7.2) [ 63 ]. The top ten genes ranked by MCC values were considered as hub candidates [ 64 , 65 , 66 , 67 ]. The overlapped candidates obtained from the two methods were identified as the hub genes.…”