用于预测胃癌预后的3-miRNA标志物的开发与临床验证
Development and clinical validation of a 3-miRNA signature to predict prognosis of gastric cancer.
作者信息
Qi Wenqian, Zhang Qian
机构信息
Department of Gastroenterology, China-Japan Union Hospital, Jilin University, Changchun, Jilin Province, China.
出版信息
PeerJ. 2021 Feb 3;9:e10462. doi: 10.7717/peerj.10462. eCollection 2021.
AIMS
Identification of miRNA signature to predict the prognosis of gastric cancer (GC) patients by integrating bioinformatics and experimental validation.
METHODS
The miRNA expression profile and clinical data of GC were collected. The univariable and LASSO-Cox regression were used to construct the risk signature. The receiver operating characteristic (ROC) curve analysis confirmed the good performance of the prognostic model.
RESULTS
A 3-miRNA prognostic signature was constructed, which included hsa-miR-126-3p, hsa-miR-143-5p, and hsa-miR-1275. A nomogram, including the prognostic signature to predict the overall survival, was established, and internal validation in the The Cancer Genome Atlas (TCGA) cohort was performed. We found that compared with the traditional pathological stage, the nomogram was the best at predicting the prognosis.
CONCLUSIONS
The predictive model and the nomogram will enable patients with GC to be more accurately managed in clinical practice.
目的
通过整合生物信息学和实验验证，鉴定用于预测胃癌（GC）患者预后的miRNA特征。
方法
收集GC的miRNA表达谱和临床数据。采用单变量和LASSO-Cox回归构建风险特征。受试者工作特征（ROC）曲线分析证实了预后模型的良好性能。
结果
构建了一个包含hsa-miR-126-3p、hsa-miR-143-5p和hsa-miR-1275的3-miRNA预后特征。建立了一个包括预后特征以预测总生存期的列线图，并在癌症基因组图谱（TCGA）队列中进行了内部验证。我们发现，与传统病理分期相比，列线图在预测预后方面表现最佳。
结论
该预测模型和列线图将使GC患者在临床实践中得到更准确的管理。
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