用于预测胃癌患者预后的三长链非编码RNA特征的开发与验证
Development and validation of a three-long noncoding RNA signature for predicting prognosis of patients with gastric cancer.
作者信息
Zhang Jun, Piao Hai-Yan, Wang Yue, Lou Mei-Yue, Guo Shuai, Zhao Yan
机构信息
Department of Gastric Cancer, Liaoning Province Cancer Hospital and Institute (Cancer Hospital of China Medical University), Shenyang 110042, Liaoning Province, China.
Medical Oncology Department of Gastrointestinal Cancer, Liaoning Province Cancer Hospital and Institute (Cancer Hospital of China Medical University), Shenyang 110042, Liaoning Province, China.
出版信息
World J Gastroenterol. 2020 Nov 28;26(44):6929-6944. doi: 10.3748/wjg.v26.i44.6929.
BACKGROUND
Gastric cancer (GC) is one of the most frequently diagnosed gastrointestinal cancers throughout the world. Novel prognostic biomarkers are required to predict the prognosis of GC.
AIM
To identify a multi-long noncoding RNA (lncRNA) prognostic model for GC.
METHODS
Transcriptome data and clinical data were downloaded from The Cancer Genome Atlas. COX and least absolute shrinkage and selection operator regression analyses were performed to screen for prognosis associated lncRNAs. Receiver operating characteristic curve and Kaplan-Meier survival analyses were applied to evaluate the effectiveness of the model.
RESULTS
The prediction model was established based on the expression of AC007991.4, AC079385.3, and AL109615.2 Based on the model, GC patients were divided into "high risk" and "low risk" groups to compare the differences in survival. The model was re-evaluated with the clinical data of our center.
CONCLUSION
The 3-lncRNA combination model is an independent prognostic factor for GC.
背景
胃癌（GC）是全球最常被诊断出的胃肠道癌症之一。需要新的预后生物标志物来预测胃癌的预后。
目的
确定一种用于胃癌的多长链非编码RNA（lncRNA）预后模型。
方法
从癌症基因组图谱下载转录组数据和临床数据。进行COX和最小绝对收缩和选择算子回归分析以筛选与预后相关的lncRNAs。应用受试者工作特征曲线和Kaplan-Meier生存分析来评估模型的有效性。
结果
基于AC007991.4、AC079385.3和AL109615.2的表达建立了预测模型。基于该模型，将胃癌患者分为“高风险”和“低风险”组以比较生存差异。用我们中心的临床数据对该模型进行了重新评估。
结论
3-lncRNA组合模型是胃癌的独立预后因素。
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