期刊
JOURNAL OF GASTROINTESTINAL ONCOLOGY
卷 11, 期 4, 页码 760-+出版社
AME PUBLISHING COMPANY
DOI: 10.21037/jgo-20-140
关键词
Gastric carcinoma (GC); long non-coding RNA (lncRNAs); biomarker; gene set enrichment analysis
资金
- National Natural Scientific Foundation of China [81660415]
- Natural Scientific Foundation of Inner Mongolia [2016MS0835]
Baokground: Accumulating evidence demonstrates that long non-coding RNAs (lncRNAs) play a predictive role in the prognosis of gastric cancer (GC). The present study aims to construct a lncRNA-based model via mining data of The Cancer Genome Atlas (TCGA). Methods: Differentially expressed lncRNAs were first identified, followed by univariate Cox analysis, Robust likelihood-based survival model and multivariate Cox analysis to construct a signature composed of lncRNAs. Results: A three-lncRNA based predictive signature (OVAAL, FLJ16779, FAM230D) was established to stratify GC patients into high- and low-risk groups. Patients in the high-risk group had markedly shorter overall survival (OS) than those in the low-risk group, which was verified by the ROC curve. Then, we validated the predictive power of the scoring system in other two cohorts. Multivariate Cox analysis also indicated that the 3-lncRNA signature was an independent prognostic factor for survival prediction in GC patients. Moreover, Gene Set Enrichment Analysis (GSEA) revealed that diverse metabolic pathways significantly clustered in the low-risk group, which might explain how the 3-lncRNA signature promoted gastric carcinogenesis. Conclusions: We established a robust three-lncRNA model to predict the OS of GC patients, which might benefit the clinical decision making for personalized treatment and prognostic prediction for GC patients.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据