A Three Protein-Coding Gene Prognostic Model Predicts Overall Survival in Bladder Cancer Patients. (23rd October 2020)

• Record Type: Journal Article
• Authors: Ning, Xiang-hui; Qi, Yuan-yuan; Wang, Fang-xin; Li, Song-chao; Jia, Zhan-kui; Yang, Jin-jian
• Other Names: Stoehr Robert Academic Editor.
• Is Part Of: BioMed research international. Volume 2020(2020)
• Publication Date: 2020-10-23
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2020/7272960
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : Bladder cancer (BLCA) is the most common urinary tract tumor and is the 11th most malignant cancer worldwide. With the development of in-depth multisystem sequencing, an increasing number of prognostic molecular markers have been identified. In this study, we focused on the role of protein-coding gene methylation in the prognosis of BLCA. We downloaded BLCA clinical and methylation data from The Cancer Genome Atlas (TCGA) database and used this information to identify differentially methylated genes and construct a survival model using lasso regression. We assessed 365 cases, with complete information regarding survival status, survival time longer than 30 days, age, gender, and tumor characteristics (grade, stage, T, M, N), in our study. We identified 353 differentially methylated genes, including 50 hypomethylated genes and 303 hypermethylated genes. After annotation, a total of 227 genes were differentially expressed. Of these, 165 were protein-coding genes. Three genes (zinc finger protein 382 ( ZNF382 ), galanin receptor 1 ( GALR1 ), and structural maintenance of chromosomes flexible hinge domain containing 1 ( SMCHD1 )) were selected for the final risk model. Patients with higher-risk scores represent poorer survival than patients with lower-risk scores in the training set (HR = 2.37, 95% CI 1.43-3.94, p = 0.001 ), in the testing group (HR = 1.85, 95% CI 1.16-2.94, p = 0.01 ), and in the total cohort (HR = 2.06, 95% CI 1.46-2.90, p < 0.001 ). Further univariate and multivariate analyses using the Cox regression method were conducted in these three groups, respectively. All the results indicated that risk score was an independent risk factor for BLCA. Our study screened the different methylation protein-coding genes in the BLCA tissues and constructed a robust risk model for predicting the outcome of BLCA patients. Moreover, these three genes may function in the mechanism of development and progression of BLCA, which should be fully clarified in the future.