Song Bic-Na, Kim Seon-Kyu, Chu In-Sun
Korean Bioinformation Center, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Korea.
Department of Bioinformatics, Korea University of Science and Technology, Daejeon, Korea.
Exp Mol Med. 2017 Jan 13;49(1):e282. doi: 10.1038/emm.2016.120.
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.
非肌肉浸润性膀胱癌(NMIBC)患者由于其临床和生物学多样性,常常对治疗无反应并经历疾病进展。在本研究中,我们通过对拷贝数和基因表达数据进行综合分析,确定了一种用于预测NMIBC异质性的预后分子特征。我们分析了从癌症基因组图谱(TCGA)联盟获得的404例膀胱癌患者的拷贝数和基因表达谱。在先前报道的14个具有显著拷贝数改变的分子中,有13个与拷贝数和表达变化显著相关。基于这13个基因开发了预后基因集,并在三个独立的患者队列(n = 501)中验证了它们的预后价值。其中,CCNE1及其共表达基因的特征与疾病进展显著相关,并在独立队列中得到验证。基于多变量分析结果,CCNE1特征是一个独立的危险因素(风险比= 6.849,95%置信区间= 1.613 - 29.092,P = 0.009)。最后,基因网络和上游调节因子分析表明,NMIBC进展可能由CCND1 - CCNE1 - SP1通路介导。由CCNE1的拷贝数和表达变化定义的预后分子特征提示了一种预测NMIBC进展可能性的新型诊断工具。