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miRpower: a web-tool to validate survival-associated miRNAs utilizing expression data from 2178 breast cancer patients.

miRpower: a web-tool to validate survival-associated miRNAs utilizing expression data from 2178 breast cancer patients.

Authors :
Lánczky A
Nagy Á
Bottai G
Munkácsy G
Szabó A
Santarpia L
Győrffy B
Source :
Breast cancer research and treatment [Breast Cancer Res Treat] 2016 Dec; Vol. 160 (3), pp. 439-446. Date of Electronic Publication: 2016 Oct 15.
Publication Year :
2016

Abstract

Purpose: The proper validation of prognostic biomarkers is an important clinical issue in breast cancer research. MicroRNAs (miRNAs) have emerged as a new class of promising breast cancer biomarkers. In the present work, we developed an integrated online bioinformatic tool to validate the prognostic relevance of miRNAs in breast cancer.<br />Methods: A database was set up by searching the GEO, EGA, TCGA, and PubMed repositories to identify datasets with published miRNA expression and clinical data. Kaplan-Meier survival analysis was performed to validate the prognostic value of a set of 41 previously published survival-associated miRNAs.<br />Results: All together 2178 samples from four independent datasets were integrated into the system including the expression of 1052 distinct human miRNAs. In addition, the web-tool allows for the selection of patients, which can be filtered by receptors status, lymph node involvement, histological grade, and treatments. The complete analysis tool can be accessed online at: www.kmplot.com/mirpower . We used this tool to analyze a large number of deregulated miRNAs associated with breast cancer features and outcome, and confirmed the prognostic value of 26 miRNAs. A significant correlation in three out of four datasets was validated only for miR-29c and miR-101.<br />Conclusions: In summary, we established an integrated platform capable to mine all available miRNA data to perform a survival analysis for the identification and validation of prognostic miRNA markers in breast cancer.

Details

Language :
English
ISSN :
1573-7217
Volume :
160
Issue :
3
Database :
MEDLINE
Journal :
Breast cancer research and treatment
Publication Type :
Academic Journal
Accession number :
27744485
Full Text :
https://doi.org/10.1007/s10549-016-4013-7