A novel risk signature that combines 10 long noncoding RNAs to predict neuroblastoma prognosis
A novel risk signature that combines 10 long noncoding RNAs to predict neuroblastoma prognosis
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DOI：
10.1002/jcp.29277
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发表时间：
2019-10-14
影响因子：
5.6
通讯作者：
Chen, Gang
中科院分区：
文献类型：
--
作者：
Gao, Li;Lin, Peng;Chen, Gang
神经母细胞瘤（NBL）是最常见的颅外实体瘤，对患者的生存影响显着，特别是在肿瘤晚期或复发的情况下。本文提出了一种长非编码 RNA (lncRNA) 特征来预测 NBL 患者的生存情况。根据从治疗应用研究生成有效治疗数据库和基因型组织表达数据库下载的 RNA 测序数据，使用 R 中的 Limma plus Voom 软件包选择差异表达的 lncRNA (DElncRNA)。进行单变量cox回归分析、最小绝对收缩和选择算子回归分析以及多变量cox回归分析来识别风险特征的候选DElncRNA。因此，10 个 DElncRNA 被指定为风险特征的候选 DElncRNA。时间依赖性受试者工作特征曲线和 Kapan-Meier 生存曲线证实了风险特征在预测 NBL 患者生存方面的有效性（曲线下面积 = 0.941；p
Neuroblastoma (NBL) is the most frequently encountered extracranial solid neoplasm and impacts significantly on the survival of patients, especially in cases of advanced tumor stage or relapse. A long noncoding RNA (lncRNA) signature to predict the survival of patients with NBL is proposed in this paper. Differentially expressed lncRNA (DElncRNA) was selected using the Limma plus Voom package in R based on the RNA-sequencing data downloaded from the Therapeutically Applicable Research To Generate Effective Treatments database and Genotype-Tissue Expression database. Univariate cox regression analysis, least absolute shrinkage and selection operator regression analysis, and multivariate cox regression analysis were conducted to identify candidate DElncRNAs for the risk signature. Consequently, 10 DElncRNAs were designated as candidate DElncRNAs for the risk signature. Time-dependent receiver operating characteristic curves and Kapan-Meier survival curves confirmed the efficacy of the risk signature in predicting the survival of patients with NBL (area under the curve = 0.941; p