Development of a novel prognostic signature for predicting the overall survival of bladder cancer patients. Issue 6 (10th June 2020)

• Record Type: Journal Article
• Authors: Tang, Huamei; Kan, Lijuan; Ou, Tong; Chen, Dayang; Dou, Xiaowen; Wu, Wei; Ji, Xiang; Wang, Mengmeng; Zong, Zengyan; Mo, Hongmei; Zhang, Xiuming; Xiong, Dan
• Is Part Of: Bioscience reports. Volume 40:Issue 6(2020)
• Publication Date: 2020-06-10
• Subjects: bladder cancer -- overall survival -- prognostic signature; Molecular biology -- Periodicals; Cytology -- Periodicals; 572.8
• DOI: 10.1042/BSR20194432
• Languages: English
• ISSNs: 0144-8463

Abstract

Abstract: Background: Bladder cancer is one of the most common malignancies. So far, no effective biomarker for bladder cancer prognosis has been identified. Aberrant DNA methylation is frequently observed in the bladder cancer and holds considerable promise as a biomarker for predicting the overall survival (OS) of patients. Materials and methods: We downloaded the DNA methylation and transcriptome data for bladder cancer from The Cancer Genome Atlas (TCGA), a public database, screened hypo-methylated and up-regulated genes, similarly, hyper-methylation with low expression genes, then retrieved the relevant methylation sites. Cox regression analysis was used to identify a nine-methylation site signature of a training group. Predictive ability was validated in a test group by receiver operating characteristic (ROC) analysis. Results: We identified nine bladder cancer-specific methylation sites as potential prognostic biomarkers and established a risk score system based on the methylation site signature to evaluate the OS. The performance of the signature was accurate, with area under curve was 0.73 in the training group and 0.71 in the test group. Taking clinical features into consideration, we constructed a nomogram consisting of the nine-methylation site signature and patients' clinical variables, and found that the signature was an independent risk factor. Conclusions: Overall, the significant nine methylation sites could be novel prediction biomarkers, which could aid in treatment and also predict the overall survival likelihoods of bladder cancer patients.