5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer
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...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:1900e6b0d5874f529431d50fa987a7bc2021-12-02T00:21:12Z5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer2296-889X10.3389/fmolb.2021.775304https://doaj.org/article/1900e6b0d5874f529431d50fa987a7bc2021-12-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fmolb.2021.775304/fullhttps://doaj.org/toc/2296-889XThe 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 these lncRNAs are involved in many cellular metabolic pathways. Lastly, MAFG-AS1 was selected for experimental validation; it was upregulated in PCa and probably promoted PCa proliferation and invasion in vitro. These results offer some insights into the m5C's effects on PCa and reveal a predictive model with the potential clinical value to improve the prognosis of patients with PCa.Ke WangKe WangWeibo ZhongZining LongYufei GuoChuanfan ZhongTaowei YangShuo WangHouhua LaiJianming LuPengxiang ZhengPengxiang ZhengXiangming MaoFrontiers Media S.A.article5-methylcytosine in RNA (m5C)lncRNAbiochemical recurrenceprostate cancerprognostic modelBiology (General)QH301-705.5ENFrontiers in Molecular Biosciences, Vol 8 (2021) |
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5-methylcytosine in RNA (m5C) lncRNA biochemical recurrence prostate cancer prognostic model Biology (General) QH301-705.5 |
| spellingShingle |
5-methylcytosine in RNA (m5C) lncRNA biochemical recurrence prostate cancer prognostic model Biology (General) QH301-705.5 Ke Wang Ke Wang Weibo Zhong Zining Long Yufei Guo Chuanfan Zhong Taowei Yang Shuo Wang Houhua Lai Jianming Lu Pengxiang Zheng Pengxiang Zheng Xiangming Mao 5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer |
| description |
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 these lncRNAs are involved in many cellular metabolic pathways. Lastly, MAFG-AS1 was selected for experimental validation; it was upregulated in PCa and probably promoted PCa proliferation and invasion in vitro. These results offer some insights into the m5C's effects on PCa and reveal a predictive model with the potential clinical value to improve the prognosis of patients with PCa. |
| format |
article |
| author |
Ke Wang Ke Wang Weibo Zhong Zining Long Yufei Guo Chuanfan Zhong Taowei Yang Shuo Wang Houhua Lai Jianming Lu Pengxiang Zheng Pengxiang Zheng Xiangming Mao |
| author_facet |
Ke Wang Ke Wang Weibo Zhong Zining Long Yufei Guo Chuanfan Zhong Taowei Yang Shuo Wang Houhua Lai Jianming Lu Pengxiang Zheng Pengxiang Zheng Xiangming Mao |
| author_sort |
Ke Wang |
| title |
5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer |
| title_short |
5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer |
| title_full |
5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer |
| title_fullStr |
5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer |
| title_full_unstemmed |
5-Methylcytosine RNA Methyltransferases-Related Long Non-coding RNA to Develop and Validate Biochemical Recurrence Signature in Prostate Cancer |
| title_sort |
5-methylcytosine rna methyltransferases-related long non-coding rna to develop and validate biochemical recurrence signature in prostate cancer |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
https://doaj.org/article/1900e6b0d5874f529431d50fa987a7bc |
| work_keys_str_mv |
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| _version_ |
1718403785949184000 |