Systematic Construction and Validation of an RNA-Binding Protein-Associated Model for Prognosis Prediction in Hepatocellular Carcinoma.
Systematic Construction and Validation of an RNA-Binding Protein-Associated Model for Prognosis Prediction in Hepatocellular Carcinoma.
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用于肝细胞癌预后预测的 RNA 结合蛋白相关模型的系统构建和验证
DOI：
10.3389/fonc.2020.597996
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发表时间：
2020
影响因子：
4.7
通讯作者：
Han Y
中科院分区：
文献类型：
--
作者：
Tian S;Liu J;Sun K;Liu Y;Yu J;Ma S;Zhang M;Jia G;Zhou X;Shang Y;Han Y
背景研究表明，肝细胞癌是全球死亡率最高的癌症之一。由RNA结合蛋白(RNAbindingProteins，RBPs)调控的转录后水平的基因调控是改变肝癌多种生物学行为的重要机制。目前，RBPs如何影响肝细胞癌的预后尚不完全清楚。在这项研究中，我们的目的是构建和验证RBP相关模型来预测肝癌患者的预后。方法基于基因表达总表(GEO)数据库中的GSE54236数据集，对肝癌患者中差异表达的限制性商业惯例进行鉴定。进行综合生物信息学分析以选择HUB基因。在癌症基因组图谱(TCGA)数据库中验证基因表达模式，然后进行单变量和多变量Cox回归分析以及Kaplan-Meier分析以建立预后模型。然后，使用受试者工作特征(ROC)曲线和临床病理相关性分析来评估预后模型的性能。此外，来自国际癌症基因组联合会(ICGC)数据库的数据被用于外部验证。最后，结合临床病理参数和预后模型建立了个体生存概率预测的诺模图。结果最终构建了基于BOP1和EZH2两个RBP的预后风险模型，便于对肝癌患者进行风险分层。低风险组的存活率明显高于高风险组。此外，风险评分越高，病理分级越高，临床分期越晚。此外，多因素分析发现，风险评分是一个独立的预后因素。包括危险评分和临床分期的诺模图在预测患者预后方面具有较好的效果。结论本研究建立的RBP相关预后模型可作为肝细胞癌的预后指标，为临床决策提供依据。
Background Evidence from prevailing studies show that hepatocellular carcinoma (HCC) is among the top cancers with high mortality globally. Gene regulation at post-transcriptional level orchestrated by RNA-binding proteins (RBPs) is an important mechanism that modifies various biological behaviors of HCC. Currently, it is not fully understood how RBPs affects the prognosis of HCC. In this study, we aimed to construct and validate an RBP-related model to predict the prognosis of HCC patients. Methods Differently expressed RBPs were identified in HCC patients based on the GSE54236 dataset from the Gene Expression Omnibus (GEO) database. Integrative bioinformatics analyses were performed to select hub genes. Gene expression patterns were validated in The Cancer Genome Atlas (TCGA) database, after which univariate and multivariate Cox regression analyses, as well as Kaplan-Meier analysis were performed to develop a prognostic model. Then, the performance of the prognostic model was assessed using receiver operating characteristic (ROC) curves and clinicopathological correlation analysis. Moreover, data from the International Cancer Genome Consortium (ICGC) database were used for external validation. Finally, a nomogram combining clinicopathological parameters and prognostic model was established for the individual prediction of survival probability. Results The prognostic risk model was finally constructed based on two RBPs (BOP1 and EZH2), facilitating risk-stratification of HCC patients. Survival was markedly higher in the low-risk group relative to the high-risk group. Moreover, higher risk score was associated with advanced pathological grade and late clinical stage. Besides, the risk score was found to be an independent prognosis factor based on multivariate analysis. Nomogram including the risk score and clinical stage proved to perform better in predicting patient prognosis. Conclusions The RBP-related prognostic model established in this study may function as a prognostic indicator for HCC, which could provide evidence for clinical decision making.
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Zeste同源物2（EZH2）增强子的抑制剂激活人类癌细胞中的肿瘤抑制剂。
影响因子：
6.2
作者：
Hibino, S.;Saito, Y.;Muramatsu, T.;Otani, A.;Kasai, Y.;Kimura, M.;Saito, H.
通讯作者：
Saito, H.
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影响因子：
13.5
作者：
Hu, Zhixiang;Dong, Liangqing;He, Xianghuo
通讯作者：
He, Xianghuo
影响因子：
7.3
作者：
Marchese, Domenica;Sanchez de Groot, Natalia;Lorenzo Gotor, Nieves;Maria Livi, Carmen;Tartaglia, Gian G.
通讯作者：
Tartaglia, Gian G.
DOI：
10.1073/pnas.1933744100
发表时间：
2003-09-30
影响因子：
11.1
作者：
Kleer, CG;Cao, Q;Chinnaiyan, AM
通讯作者：
Chinnaiyan, AM
影响因子：
5.7
作者：
Li T;Li S;Chen D;Chen B;Yu T;Zhao F;Wang Q;Yao M;Huang S;Chen Z;He X
通讯作者：
He X