Identification of Hub Genes Associated With Progression and Prognosis in Patients With Bladder Cancer
Open Access
- 7 May 2019
- journal article
- research article
- Published by Frontiers Media SA in Frontiers in Genetics
- Vol. 10, 408
- https://doi.org/10.3389/fgene.2019.00408
Abstract
Given that most bladder cancers (BCs) are diagnosed in advanced stages with poor prognosis, this study aims to find novel biomarkers associated with the progression and prognosis in patients with BC. 1,779 differentially expressed genes (DEGs) between BC samples and normal bladder tissues were identified in total. Then, 24 DEGs were regarded as candidate hub genes by constructing a protein–protein interaction (PPI) network and a random forest model. Among them, six genes (BUB1B, CCNB1, CDK1, ISG15, KIF15, and RAD54L) were eventually identified by using five analysis methods (one-way Analysis of Variance analysis, spearman correlation analysis, distance correlation analysis, receiver operating characteristic curve, and expression values comparison), which were correlated with the progression and prognosis of BC. Moreover, the validation of hub genes was conducted based on GSE13507, Oncomine, and CBioPortal. Results of univariate Cox regression analysis showed that the expression levels of all the hub genes were influence features of overall survival (OS) and cancer specific survival (CSS) based on GSE13507, and we further established a six-gene signature based on the expression levels of the six genes and their Cox regression coefficients. This signature showed good potential for clinical application suggested by survival analysis (OS: Hazard Ratio = 0.484, 95%CI: 0.298–0.786; P = 0.0034; CSS: Hazard Ratio = 0.244, 95%CI: 0.121–0.493, P < 0.0001) and decision curve analysis. In conclusion, our study indicates that six hub genes have great predictive value for the prognosis and progression of BC and may contribute to the exploration of further basic and clinical research of BC.This publication has 57 references indexed in Scilit:
- Cyclin-dependent kinase inhibitor therapy for hematologic malignanciesExpert Opinion on Investigational Drugs, 2013
- The cBio Cancer Genomics Portal: An Open Platform for Exploring Multidimensional Cancer Genomics DataCancer Discovery, 2012
- clusterProfiler: an R Package for Comparing Biological Themes Among Gene ClustersOMICS: A Journal of Integrative Biology, 2012
- Estimates of worldwide burden of cancer in 2008: GLOBOCAN 2008International Journal of Cancer, 2010
- Predictive value of progression-related gene classifier in primary non-muscle invasive bladder cancerMolecular Cancer, 2010
- edgeR: a Bioconductor package for differential expression analysis of digital gene expression dataBioinformatics, 2009
- Diagnostic Value of Fine Needle Aspiration Cytology in Gouty TophiActa Cytologica, 2006
- Cyclin B1 and Other Cyclins as Tumor Antigens in Immunosurveillance and Immunotherapy of CancerCancer Research, 2006
- Cytoscape: A Software Environment for Integrated Models of Biomolecular Interaction NetworksGenome Research, 2003
- Susceptibility of 57 Bloodstream and Urinary Isolates of Candida Species from a Single Children’s University Hospital to 6 AntifungalsChemotherapy, 2002