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Overexpression of lncRNA SNGH3 Predicts Unfavorable Prognosis and Clinical Outcomes in Human Cancers: Evidence from a Meta-Analysis

置信区间 危险系数 优势比 科克伦图书馆 内科学 医学 梅德林 荟萃分析 肿瘤科 算法 生物信息学 生物 计算机科学 生物化学
作者
Yu-Gang Jiang,Lulu Le
出处
期刊:BioMed Research International [Hindawi Limited]
卷期号:2020: 1-13 被引量:7
标识
DOI:10.1155/2020/7974034
摘要

Long noncoding RNAs (lncRNAs) have been confirmed to play a crucial role in human disease, especially in tumor development and progression. Small nucleolar RNA host gene (SNHG3), a newly identified lncRNA, has been found dysregulated in various cancers. Nevertheless, the results remain controversial. Thus, we aim to analyze the comprehensive data to elaborate the association between SNHG3 expression and clinical outcomes in multiple cancers. We searched PubMed, Web of Science, Cochrane Library, Embase, and MEDLINE database to identify eligible articles. STATA software was applied to calculate the hazard ratio (HR) and odds ratio (OR) with 95% confidence interval (95% CI) for survival outcomes and clinical parameters, respectively. Besides, the data from The Cancer Genome Atlas (TCGA) dataset was extracted to verify the results in our meta-analysis. There were thirteen studies totaling 919 cancer patients involved in this meta-analysis. The results demonstrated that high SNHG3 expression was significantly associated with poor overall survival (OS) (HR=2.53, 95% CI: 1.94-3.31) in cancers, disease-free survival (DFS) (HR=3.89, 95% CI: 1.34-11.3), and recurrence-free survival (RFS) (HR=2.42, 95% CI: 1.14-5.15) in hepatocellular carcinoma. Analysis stratified by analysis method, sample size, follow-up time, and cancer type further verified the prognostic value of SNHG3. Additionally, patients with high SNHG3 expression tended to have more advanced clinical stage, higher histological grade, earlier distant metastasis, and earlier lymph node metastasis. Excavation of TCGA dataset valuated that SNHG3 was upregulated in various cancers and predicted worse OS and DFS. Overexpressed SNHG3 was strongly associated with poor survival and clinical outcomes in human cancers and therefore can serve as a promising biomarker for predicting patients’ prognosis.
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