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

Abstract 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 progressi...

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Main Authors: Jiawei Shi, Pu Zhang, Lilong Liu, Xiaobo Min, Yajun Xiao
Format: Article
Language:English
Published: Wiley 2019-11-01
Series:Molecular Genetics & Genomic Medicine
Subjects:
Online Access:https://doi.org/10.1002/mgg3.982
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spelling doaj-a5d07079e01d475dbb16a78f2b456c2f2020-11-25T02:36:30ZengWileyMolecular Genetics & Genomic Medicine2324-92692019-11-01711n/an/a10.1002/mgg3.982Weighted gene coexpression network analysis identifies a new biomarker of CENPF for prediction disease prognosis and progression in nonmuscle invasive bladder cancerJiawei Shi0Pu Zhang1Lilong Liu2Xiaobo Min3Yajun Xiao4Department of Urology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan ChinaDepartment of Urology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan ChinaDepartment of Urology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan ChinaDepartment of Hepatology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan ChinaDepartment of Urology Union Hospital Tongji Medical College Huazhong University of Science and Technology Wuhan ChinaAbstract 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.https://doi.org/10.1002/mgg3.982biomarkersCENPFnonmuscle invasive bladder cancer (NMIBC)progressionweighted gene coexpression network analysis (WGCNA)
collection DOAJ
language English
format Article
sources DOAJ
author Jiawei Shi
Pu Zhang
Lilong Liu
Xiaobo Min
Yajun Xiao
spellingShingle Jiawei Shi
Pu Zhang
Lilong Liu
Xiaobo Min
Yajun Xiao
Weighted gene coexpression network analysis identifies a new biomarker of CENPF for prediction disease prognosis and progression in nonmuscle invasive bladder cancer
Molecular Genetics & Genomic Medicine
biomarkers
CENPF
nonmuscle invasive bladder cancer (NMIBC)
progression
weighted gene coexpression network analysis (WGCNA)
author_facet Jiawei Shi
Pu Zhang
Lilong Liu
Xiaobo Min
Yajun Xiao
author_sort Jiawei Shi
title Weighted gene coexpression network analysis identifies a new biomarker of CENPF for prediction disease prognosis and progression in nonmuscle invasive bladder cancer
title_short Weighted gene coexpression network analysis identifies a new biomarker of CENPF for prediction disease prognosis and progression in nonmuscle invasive bladder cancer
title_full Weighted gene coexpression network analysis identifies a new biomarker of CENPF for prediction disease prognosis and progression in nonmuscle invasive bladder cancer
title_fullStr Weighted gene coexpression network analysis identifies a new biomarker of CENPF for prediction disease prognosis and progression in nonmuscle invasive bladder cancer
title_full_unstemmed Weighted gene coexpression network analysis identifies a new biomarker of CENPF for prediction disease prognosis and progression in nonmuscle invasive bladder cancer
title_sort weighted gene coexpression network analysis identifies a new biomarker of cenpf for prediction disease prognosis and progression in nonmuscle invasive bladder cancer
publisher Wiley
series Molecular Genetics & Genomic Medicine
issn 2324-9269
publishDate 2019-11-01
description Abstract 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.
topic biomarkers
CENPF
nonmuscle invasive bladder cancer (NMIBC)
progression
weighted gene coexpression network analysis (WGCNA)
url https://doi.org/10.1002/mgg3.982
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AT puzhang weightedgenecoexpressionnetworkanalysisidentifiesanewbiomarkerofcenpfforpredictiondiseaseprognosisandprogressioninnonmuscleinvasivebladdercancer
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