Bioinformatic identification of prognostic signature defined by copy number alteration and expression of CCNE1 in non-muscle invasive bladder cancer

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Title
Bioinformatic identification of prognostic signature defined by copy number alteration and expression of CCNE1 in non-muscle invasive bladder cancer
Author(s)
Bic Na Song; Seon-Kyu Kim; In-Sun Chu
Bibliographic Citation
Experimental and Molecular Medicine, vol. 49, no. 1, pp. e282-e282
Publication Year
2017
Abstract
Non-muscle invasive bladder cancer (NMIBC) patients frequently fail to respond to treatment and experience disease progression because of their clinical and biological diversity. In this study, we identify a prognostic molecular signature for predicting the heterogeneity of NMIBC by using an integrative analysis of copy number and gene expression data. We analyzed the copy number and gene expression profiles of 404 patients with bladder cancer obtained from The Cancer Genome Atlas (TCGA) consortium. Of the 14 molecules with significant copy number alterations that were previously reported, 13 were significantly correlated with copy number and expression changes. Prognostic gene sets based on the 13 genes were developed, and their prognostic values were verified in three independent patient cohorts (n=501). Among them, a signature of CCNE1 and its coexpressed genes was significantly associated with disease progression and validated in the independent cohorts. The CCNE1 signature was an independent risk factor based on the result of a multivariate analysis (hazard ratio=6.849, 95% confidence interval=1.613-29.092, P=0.009). Finally, gene network and upstream regulator analyses revealed that NMIBC progression is potentially mediated by CCND1-CCNE1-SP1 pathways. The prognostic molecular signature defined by copy number and expression changes of CCNE1 suggests a novel diagnostic tool for predicting the likelihood of NMIBC progression. ⓒ 2017 KSBMB.
ISSN
I000-0028
Publisher
Springer-Nature Pub Group
DOI
http://dx.doi.org/10.1038/emm.2016.120
Type
Article
Appears in Collections:
Aging Convergence Research Center > 1. Journal Articles
Division of Biomedical Research > Metabolic Regulation Research Center > 1. Journal Articles
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