Lánczky András, Nagy Ádám, Bottai Giulia, Munkácsy Gyöngyi, Szabó András, Santarpia Libero, Győrffy Balázs
MTA TTK Lendület Cancer Biomarker Research Group, Magyar Tudósok körútja 2, Budapest, 1117, Hungary.
Department of Pediatrics, Semmelweis University, Budapest, Hungary.
Breast Cancer Res Treat. 2016 Dec;160(3):439-446. doi: 10.1007/s10549-016-4013-7. Epub 2016 Oct 15.
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.
对乳腺癌预后生物标志物进行恰当验证是乳腺癌研究中的一个重要临床问题。微小RNA（miRNA）已成为一类有前景的新型乳腺癌生物标志物。在本研究中，我们开发了一个综合性在线生物信息学工具，以验证miRNA在乳腺癌中的预后相关性。
通过搜索基因表达综合数据库（GEO）、欧洲基因组-表型档案库（EGA）、癌症基因组图谱（TCGA）和医学期刊数据库（PubMed）建立一个数据库，以识别已发表的miRNA表达和临床数据的数据集。进行Kaplan-Meier生存分析，以验证一组41个先前发表的与生存相关的miRNA的预后价值。
来自四个独立数据集的总共2178个样本被整合到该系统中，包括1052种不同人类miRNA的表达。此外，该网络工具允许选择患者，可按受体状态、淋巴结受累情况、组织学分级和治疗方法进行筛选。完整的分析工具可在线访问：www.kmplot.com/mirpower 。我们使用该工具分析了大量与乳腺癌特征和预后相关的失调miRNA，并证实了26种miRNA的预后价值。仅在四个数据集中的三个数据集中，miR-29c和miR-101被验证存在显著相关性。
总之，我们建立了一个综合平台，能够挖掘所有可用的miRNA数据，以进行生存分析，从而识别和验证乳腺癌中的预后miRNA标志物。
