Weighted gene coexpression network analysis identifies a new biomarker of CENPF for prediction disease prognosis and progression in nonmuscle invasive bladder cancer

BACKGROUND: The dreadful prognosis of nonmuscle invasive bladder cancer mainly results from the delay in recognition of individuals with a high risk of progression. Thus, the emphasis of this work lies in developing valuable biomarkers that is conducive to accurately predicting the progression of NMIBC. METHODS: Microarray data from GSE32894 including 209 NMIBC samples were performed by weighted gene coexpression network analysis (WGCNA), which could find modules of highly correlated genes and relate modules to external sample traits. Besides, we constructed a protein–protein interaction to facilitate screening the hub gene. At last, we used RNA‐seq and microarray data and clinical information from ArrayExpress (E‐MTAB‐4321) and GSE13507 to select and validate the candidate gene. RESULTS: In current paper, blue module of 13 gene coexpression clusters we identified was selected as the key modules. Seven genes namely: CDCA8, CENPF, MCM6, MELK, PRC1, STIL, and TPX2 have been identified as candidate genes. Notably, among them, only elevated CENPF in NIMBC tissue was closely associated with low progression‐free survival (PFS) and overall survival (OS) rate in three datasets and had a large area under receiver operating characteristic (ROC) curve. Finally, CENPF was identified as an effective biomarker in NMIBC. CONCLUSION: Therefore, our findings submit a new progressive and prognostic molecular marker and therapeutic target for NMIBC. Moreover, these genes that deserve to be further researched may improve the comprehension about the occurrence and development of superficial bladder cancer.