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

• DOI: 10.1007/s10549-016-4013-7
• Publication Date: 2016-10-15T12:53:26Z
• Authors: András Lánczky; Ádám Nagy; Giulia Bottai; Gyöngyi Munkácsy; András Szabó; Libero Santarpia; Balázs Győrffy
• Keywords: 0303 health sciences; tumorok; 610; Computational Biology; Reproducibility of Results; Breast Neoplasms; onkológia; Web Browser; Prognosis; 3. Good health; Gene Expression Regulation, Neoplastic; MicroRNAs; User-Computer Interface; 03 medical and health sciences; Databases, Genetic; Biomarkers, Tumor; Humans; Female; RC0254 Neoplasms. Tumors. Oncology (including Cancer) / daganatok; Software

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.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.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.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.