标题：Prognostic Value of MicroRNA-15a in Human Cancers: A Meta-Analysis and Bioinformatics
作者：Yang, Fei-ran; Li, Hui-jie; Li, Ting-ting; Zhao, Yu-feng; Liu, Zong-kai; Li, Xiu-rong
作者机构：[Yang, Fei-ran; Li, Ting-ting] Shandong Univ Tradit Chinese Med, Coll Tradit Chinese Med, Jinan, Shandong, Peoples R China.; [Li, Hui-jie; Zhao, Yu- 更多
通讯作者地址：[Li, XR]Shandong Univ Tradit Chinese Med, Affiliated Hosp, Dept Oncol, Jinan, Shandong, Peoples R China.
来源：BIOMED RESEARCH INTERNATIONAL
摘要：Background. Although several studies have proved the relationship between the prognostic value of miRNA-15a and different types of cancer, the result remains controversial. Thus, a meta-analysis was conducted to clarify the prognostic value of miRNA-15a expression level in human cancers. Methods. We enrolled appropriate literature by searching the databases of PubMed, Embase, and Web of Science. Subsequently, we extracted HRs and their 95% CIs and calculated pooled results of miRNA-15a for overall survival (OS) and disease-free survival (DFS). Besides, subgroup analysis, sensitivity analysis, and publication bias were also revealed in this study. We also further validated this meta-analysis using the Kaplan-Meier plotter database. Result. 10 studies, including 1616 patients, were embraced in our meta-analysis. The result showed the lower expression of miRNA-15a significantly predicted adverse OS (HR=2.17, 95% CI: 1.41-3.34), but there is no significant association between the expressing level and DFS in cancer patient (HR=2.04, 95% CI: 0.60-6.88). Based on Kaplan-Meier plotter database, we found the same results in bladder Carcinoma, head-neck squamous cell carcinoma, liver hepatocellular carcinoma, lung squamous cell carcinoma, pancreatic ductal adenocarcinoma, rectum adenocarcinoma, stomach adenocarcinoma, and uterine corpus endometrial carcinoma, but opposite results were found in cervical squamous cell carcinoma and esophageal carcinoma. Conclusion. Low expressing levels of miRNA-15a indicated poor OS, while miRNA-15a can be used as a prediction biomarker in different cancer types.