A Novel CpG Methylation Risk Indicator for Predicting Prognosis in Bladder Cancer - Guo, Yufeng; Yin, Jianjian; Dai, Yuanheng; Guan, Yudong; Chen, Pinjin; Chen, Yongqiang; Huang, Chenzheng; Lu, Yong-Jie; Zhang, Lirong; Song, Dongkui (Frontiers in Cell and Developmental Biology, 2021)
Abstract Purpose: Bladder cancer (BLCA) is one of the most common cancers worldwide. In a large proportion of BLCA patients, disease recurs and/or progress after treatment, which remains a major clinical issue in BLCA management. Therefore, it is vital to identify prognostic biomarkers for treatment stratification. We investigated the efficiency of CpG methylation for the potential as prognostic biomarker for patients with BLCA. Patients and Methods: Overall, 357 bladder cancer patients from The Cancer Genome Atlas(TCGA) were randomly separated into the training and internal validation cohorts. Least absolute shrinkage and selector operation(LASSO) and support vector machine-recursive feature elimination(SVM-RFE) were used to select candidate CpGs and build the methylation risk score model, which was validated for its prognostic value by Kaplan–Meier analysis. Hazard curves were generated to reveal the risk nodes throughout the follow-up. Gene Set Enrichment Analysis(GSEA) was used to reveal the potential biological pathways associated with the model. Quantitative real-time PCR and western blotting of the target was conducted to verify the expression level. Results: After incorporating the CpGs obtained by the two algorithms, eight CpGs corresponding to TNFAIP8L3, KRTDAP, APC, ZC3H3, COL9A2, SLCO4A1, POU3F3 and ADARB2 were prominent candidate predictors in establishing a methylation risk score for BLCA(MRSB), which was used to divide the patients into high- and low-risk progression groups(P <0.001). The effectiveness of the MRSB was validated in the internal cohort (P<0.001). In the MRSB high-risk group, the hazard curve exhibited an initial wide, high peak within 10 months after treatment, whereas some gentle peaks around 2 years were noted. Furthermore, a nomogram comprising MRSB, age, sex and tumor clinical stage was used to predict the individual progression risk, and it performed well. Survival analysis implicated the effectiveness of MRSB was not affected by the subgroup of the clinical features. Functional analysis of MRSB and the corresponding genes revealed potential pathways affecting tumor progression. Validation of quantitative real-time PCR and western blotting revealed that TNFAIP8L3 was upregulated in the BLCA tissues. Conclusion: We developed the MRSB, an eight-gene-based methylation signature, which has great potential to be used to predict the post-surgery progression risk of bladder cancer.