• Medicine · Aug 2018

    Review Meta Analysis

    MicroRNA-200 and microRNA-30 family as prognostic molecular signatures in ovarian cancer: A meta-analysis.

    • Min Shi, Yulan Mu, Hui Zhang, Ming Liu, Jipeng Wan, Xiaoyan Qin, and Changzhong Li.
    • Department of Obstetrics and Gynecology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, Shandong, People's Republic of China.
    • Medicine (Baltimore). 2018 Aug 1; 97 (32): e11505.

    BackgroundMicroRNAs (miRs) play a vital role in the occurrence, development, and progression of human cancers, but its role in the prognosis of ovarian cancer is unclear.MethodsWe performed a meta-analysis by searching PubMed, Embase, and Web of Science databases for eligible studies. The pooled hazard ratios (HRs) and 95% confidence intervals (CIs) were used to explore the association between miRs expression and overall survival (OS) and progression-free survival (PFS) on ovarian cancer patients. We also used Kaplan-Meier to analyze the relationship between miRs and OS in OncoLnc dataset.ResultsA total of 15 records were included into the meta-analysis. The expression level of miR-200 family showed significant association with OS (HR = 0.78, 95% CI: 0.64-0.94) and insignificant association with PFS (HR = 0.72, 95% CI: 0.50-1.03). Subgroup analysis revealed that an increased expression level of miR-200c was associated with better OS (HR = 0.59, 95% CI: 0.45-0.74). An increased expression level of miR-200a, miR-200c, and miR-141 was associated with better PFS (miR-200a, HR = 0.59, 95% CI: 0.42-0.75; miR-200c, HR = 0.50, 95% CI: 0.14-0.87, miR-141, HR = 0.38, 95% CI: 0.12-0.63). Similarly, higher expression of miR-30 family was associated with elevated OS/PFS for ovarian cancer (OS, HR = 0.43, 95% CI: 0.13-0.74; PFS, HR = 0.76, 95% CI: 0.64-0.87). The OncoLnc dataset presented that elevated expression level of miR-30d-5p was associated with better OS (n = 470, P = .0197).ConclusionThe meta-analysis reveals that miR-200 family and miR-30 family could be promising prognostic biomarkers of ovarian cancer.

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