5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer

作者：Ke Wang, Weibo Zhong, Zining Long, Yufei Guo, Chuanfan Zhong, Taowei Yang, Shuo Wang, Houhua Lai, Jianming Lü, Pengxiang Zheng, Xiangming Mao · 发表于：Frontiers in Molecular Biosciences · 年份：2021 · DOI：10.3389/fmolb.2021.775304 · 被引用次数：26 · 研究领域：Cancer-related molecular mechanisms research、RNA modifications and cancer、RNA Research and Splicing

The effects of 5-methylcytosine in RNA (m5C) in various human cancers have been increasingly studied recently; however, the m5C regulator signature in prostate cancer (PCa) has not been well established yet. In this study, we identified and characterized a series of m5C-related long non-coding RNAs (lncRNAs) in PCa. Univariate Cox regression analysis and least absolute shrinkage and selector operation (LASSO) regression analysis were implemented to construct a m5C-related lncRNA prognostic signature. Consequently, a prognostic m5C-lnc model was established, including 17 lncRNAs: MAFG-AS1 , AC012510.1 , AC012065.3 , AL117332.1 , AC132192.2 , AP001160.2 , AC129510.1 , AC084018.2 , UBXN10-AS1 , AC138956.2 , ZNF32-AS2 , AC017100.1 , AC004943.2 , SP2-AS1 , Z93930.2 , AP001486.2 , and LINC01135 . The high m5C-lnc score calculated by the model significantly relates to poor biochemical recurrence (BCR)-free survival ( p < 0.0001). Receiver operating characteristic (ROC) curves and a decision curve analysis (DCA) further validated the accuracy of the prognostic model. Subsequently, a predictive nomogram combining the prognostic model with clinical features was created, and it exhibited promising predictive efficacy for BCR risk stratification. Next, the competing endogenous RNA (ceRNA) network and lncRNA–protein interaction network were established to explore the potential functions of these 17 lncRNAs mechanically. In addition, functional enrichment analysis revealed that thes...