Journal
JOURNAL OF EXPERIMENTAL & CLINICAL CANCER RESEARCH
Volume 34, Issue -, Pages -Publisher
BIOMED CENTRAL LTD
DOI: 10.1186/s13046-015-0167-0
Keywords
Bladder cancer; miRNA profiles; miRNA signature; Prognosis; Integrated analysis
Categories
Funding
- National Natural Science Foundation of China [31072238, 31172441, 31372562, 81170650]
- National Major Scientific and Technological Special Project for Significant New Drugs Development [2012ZX09303018]
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Background: There is increasing evidence to suggest that miRNAs play an important role in predicting cancer survival. To identify a panel of miRNA signature that can divided tumor from normal bladder using miRNA expression levels, and to assess the prognostic value of this specific miRNA markers in bladder cancer (BCa). Methods: A comprehensive meta-review of published miRNA expression profiles that compared BCa and adjacent normal tissues was performed to determine candidate miRNAs as prognostic biomarkers for BCa. Vote-counting strategy and Robust Rank Aggregation method were used to identify significant meta-signature miRNAs. Results: We identified an eight-miRNA signature including three upregulated (miR-141, miR-200c, miR-21) and five downregulated (miR-145, miR-125, miR-199a, let-7c and miR-99a) miRNAs for the prediction of overall survival (OS) using TCGA dataset, and validated in our 48 BCa patients. X-tile plot was used to generate the optimum cut-off point and Kaplan-Meier method was used to calculate OS. A linear prognostic model of eight miRNAs was constructed and weighted by the importance scores from the supervised principal component method to divide patients into high- and low-risk groups. Patients assigned to the high- risk group were associated with poor OS compared with patients in the low- risk group (HR = 5.21, p < 0.001). Our validation cohort of 48 patients confirmed the panel of 8-miRNAs as a reliable prognostic tool for OS in patients with BCa (HR = 5.04, p < 0.001). Conclusion: The present meta-analysis identified eight highly significant and consistently dysregulated miRNAs from 19 datasets. We also constructed an eight-miRNA signature which provided predictive and prognostic value that complements traditional clinicopathological risk factors.
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