4.6 Article

OSbrca: A Web Server for Breast Cancer Prognostic Biomarker Investigation With Massive Data From Tens of Cohorts

Journal

FRONTIERS IN ONCOLOGY
Volume 9, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fonc.2019.01349

Keywords

survival; breast cancer; prognosis; biomarker; OSbrca

Categories

Funding

  1. Kaifeng Science and Technology Major Project [18ZD008]
  2. National Natural Science Foundation of China [81602362, 81801569]
  3. Program for Science and Technology Development in Henan Province [162102310391, 172102210187, 192102310302]
  4. Program for Innovative Talents of Science and Technology in Henan Province [18HASTIT048]
  5. Henan University [2015YBZR048, B2015151]
  6. Yellow River Scholar Program [H2016012]

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Potential prognostic mRNA biomarkers are exploited to assist in the clinical management and treatment of breast cancer, which is the first life-threatening tumor in women worldwide. However, it is technically challenging for untrained researchers to process high dimensional profiling data to screen and validate the potential prognostic values of genes of interests in multiple cohorts. Our aim is to develop an easy-to-use web server to facilitate the screening, developing, and evaluating of prognostic biomarkers in breast cancers. Herein, we collected more than 7,400 cases of breast cancer with gene expression profiles and clinical follow-up information from The Cancer Genome Atlas and Gene Expression Omnibus data, and built an Online consensus Survival analysis web server for Breast Cancers, abbreviated OSbrca, to generate the Kaplan-Meier survival plot with a hazard ratio and log rank P-value for given genes in an interactive way. To examine the performance of OSbrca, the prognostic potency of 128 previously published biomarkers of breast cancer was reassessed in OSbrca. In conclusion, it is highly valuable for biologists and clinicians to perform the preliminary assessment and validation of novel or putative prognostic biomarkers for breast cancers. OSbrca could be accessed at http://bioinfo.henu.edu.cn/BRCA/BRCAList.jsp.

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