AUTHOR=Zhang Guosen , Wang Qiang , Yang Mengsi , Yuan Quan , Dang Yifang , Sun Xiaoxiao , An Yang , Dong Huan , Xie Longxiang , Zhu Wan , Wang Yunlong , Guo Xiangqian TITLE=OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer Patients JOURNAL=Frontiers in Oncology VOLUME=Volume 9 - 2019 YEAR=2019 URL=https://www.frontiersin.org/journals/oncology/articles/10.3389/fonc.2019.00466 DOI=10.3389/fonc.2019.00466 ISSN=2234-943X ABSTRACT=Bladder cancer (BC) is one of the most common malignant tumors in urinary system. The discovery of prognostic biomarkers is still one of the major challenges to improve clinical treatment of BC patients. In order to assist biologists and clinicians easily evaluate the prognostic potency of genes in BC patients, we develop a user-friendly Online consensus Survival tool for bladder cancer (OSblca), to analyze the prognostic value of genes. The OSblca includes gene expression profiles of 1075 BC patients and their respective clinical follow-up information. The clinical follow-up data include overall survival (OS), disease specific survival (DSS), disease free interval (DFI), and progression free interval (PFI). To analyze the prognostic value of a gene, users only need to input the official gene symbol and then click the ‘Kaplan-Meier plot’ button, Kaplan-Meier curve with the hazard ratio, 95% confidence intervals and log-rank P value are generated and graphically displayed on the website using default options. For advanced analysis, users could limit their analysis by confounding factors including data source, survival type, TNM stage, histological type, smoking history, gender, lymph invasion and race, which are setup as optional parameters to meet the special needs from different researchers. To show performance of the webserver, we have tested and validated the reliability of our web server using previously reported prognostic biomarkers, including KPNA2, TP53 and MYC etc., which are validated their prognostic values as reported in OSblca. In conclusion, OSblca is a useful tool to evaluate and discover novel prognostic biomarkers in BC. The web server can be accessed at http://bioinfo.henu.edu.cn/BLCA/BLCAList.jsp.