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Systematic Evaluation of the Diagnostic and Prognostic Significance of Competitive Endogenous RNA Networks in Prostate Cancer.
Frontiers in Genetics ( IF 3.7 ) Pub Date : 2020-07-01 , DOI: 10.3389/fgene.2020.00785
Zihu Guo 1, 2 , Liang Han 3 , Yingxue Fu 1 , Ziyin Wu 4 , Yaohua Ma 2 , Yueping Li 5 , Haiqing Wang 2 , Li Jiang 5 , Shengnan Liang 6 , Zhenzhong Wang 4 , Furong Li 7 , Wei Xiao 4 , Jingbo Wang 7 , Yonghua Wang 1, 2
Affiliation  

Long non-coding RNA (lncRNA)-mediated competitive endogenous RNA (ceRNA) networks act as essential mechanisms in tumor initiation and progression, but their diagnostic and prognostic significance in prostate cancer (PCa) remains poorly understood. Presently, using the RNA expression data derived from multiple independent PCa-related studies, we constructed a high confidence and PCa-specific core ceRNA network by employing three lncRNA-gene inference approaches and key node filter strategies and then established a logistic model and risk score formula to evaluate its diagnostic and prognostic values, respectively. The core ceRNA network consists of 10 nodes, all of which are significantly associated with clinical outcomes. Combination of expression of the 10 ceRNAs with a logistic model achieved AUC of ROC and PR curve up to ∼96 and 99% in excluding normal prostate samples, respectively. Additionally, a risk score formula constructed with the ceRNAs exhibited significant association with disease-free survival. More importantly, utilizing the expression of RNAs in the core ceRNA network as a molecular signature, the TCGA-PRAD cohort was divided into four novel clinically relevant subgroups with distinct expression patterns, highlighting a feasible way for improving patient stratification in the future. Overall, we constructed a PCa-specific core ceRNA network, which provides diagnostic and prognostic value.



中文翻译:

竞争性内源性RNA网络在前列腺癌中的诊断和预后意义的系统评价。

长的非编码RNA(lncRNA)介导的竞争性内源RNA(ceRNA)网络是肿瘤起始和进展的基本机制,但它们在前列腺癌(PCa)中的诊断和预后意义仍然知之甚少。目前,我们使用来自多个独立PCa相关研究的RNA表达数据,通过采用三种lncRNA基因推论方法和关键节点过滤策略构建了高可信度和PCa特异性核心ceRNA网络,然后建立了逻辑模型和风险评分分别评估其诊断和预后价值的公式。核心ceRNA网络由10个节点组成,所有这些节点均与临床结果显着相关。在排除正常前列腺样品的情况下,将10种ceRNA的表达与逻辑模型相结合,可实现ROC和PR曲线的AUC分别高达〜96和99%。此外,用ceRNA构建的风险评分公式与无病生存率显着相关。更重要的是,利用核心ceRNA网络中RNA的表达作为分子标记,TCGA-PRAD队列被划分为四个具有独特表达模式的临床相关的新亚组,从而突出了未来改善患者分层的可行方法。总体而言,我们构建了PCa特定的核心ceRNA网络,可提供诊断和预后价值。用ceRNA构建的风险评分公式与无病生存率显着相关。更重要的是,利用核心ceRNA网络中RNA的表达作为分子标记,TCGA-PRAD队列被划分为四个具有独特表达模式的临床相关的新亚组,从而突出了未来改善患者分层的可行方法。总体而言,我们构建了PCa特定的核心ceRNA网络,可提供诊断和预后价值。用ceRNA构建的风险评分公式与无病生存率显着相关。更重要的是,利用核心ceRNA网络中RNA的表达作为分子标记,TCGA-PRAD队列被划分为四个具有独特表达模式的临床相关的新亚组,从而突出了未来改善患者分层的可行方法。总体而言,我们构建了PCa特定的核心ceRNA网络,可提供诊断和预后价值。

更新日期:2020-07-30
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