OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer Patients

Bladder cancer (BC) is one of the most common malignant tumors in the 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 in easily evaluating the prognostic potency of...

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Main Authors: Guosen Zhang, Qiang Wang, Mengsi Yang, Quan Yuan, Yifang Dang, Xiaoxiao Sun, Yang An, Huan Dong, Longxiang Xie, Wan Zhu, Yunlong Wang, Xiangqian Guo
Format: Article
Language:English
Published: Frontiers Media S.A. 2019-06-01
Series:Frontiers in Oncology
Subjects:
Online Access:https://www.frontiersin.org/article/10.3389/fonc.2019.00466/full
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record_format Article
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language English
format Article
sources DOAJ
author Guosen Zhang
Qiang Wang
Mengsi Yang
Quan Yuan
Yifang Dang
Xiaoxiao Sun
Yang An
Huan Dong
Longxiang Xie
Wan Zhu
Yunlong Wang
Xiangqian Guo
spellingShingle Guosen Zhang
Qiang Wang
Mengsi Yang
Quan Yuan
Yifang Dang
Xiaoxiao Sun
Yang An
Huan Dong
Longxiang Xie
Wan Zhu
Yunlong Wang
Xiangqian Guo
OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer Patients
Frontiers in Oncology
bladder cancer
prognostic biomarker analysis
web server
kaplan-meier curve
cox regression model
author_facet Guosen Zhang
Qiang Wang
Mengsi Yang
Quan Yuan
Yifang Dang
Xiaoxiao Sun
Yang An
Huan Dong
Longxiang Xie
Wan Zhu
Yunlong Wang
Xiangqian Guo
author_sort Guosen Zhang
title OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer Patients
title_short OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer Patients
title_full OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer Patients
title_fullStr OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer Patients
title_full_unstemmed OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer Patients
title_sort osblca: a web server for investigating prognostic biomarkers of bladder cancer patients
publisher Frontiers Media S.A.
series Frontiers in Oncology
issn 2234-943X
publishDate 2019-06-01
description Bladder cancer (BC) is one of the most common malignant tumors in the 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 in easily evaluating the prognostic potency of genes in BC patients, we developed 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 1,075 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, and 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 set up as optional parameters to meet the specific needs of different researchers. To test the performance of the web server, we have tested and validated its reliability using previously reported prognostic biomarkers, including KPNA2, TP53, and MYC etc., which had their prognostic values validated 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.
topic bladder cancer
prognostic biomarker analysis
web server
kaplan-meier curve
cox regression model
url https://www.frontiersin.org/article/10.3389/fonc.2019.00466/full
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spelling doaj-0863ae11623444238c564c278f2c76e82020-11-24T21:54:18ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2019-06-01910.3389/fonc.2019.00466458328OSblca: A Web Server for Investigating Prognostic Biomarkers of Bladder Cancer PatientsGuosen Zhang0Qiang Wang1Mengsi Yang2Quan Yuan3Yifang Dang4Xiaoxiao Sun5Yang An6Huan Dong7Longxiang Xie8Wan Zhu9Yunlong Wang10Xiangqian Guo11Cell Signal Transduction Laboratory, Department of Preventive Medicine, Bioinformatics Center, School of Basic Medical Sciences, School of Software, Institute of Biomedical Informatics, Henan University, Kaifeng, ChinaCell Signal Transduction Laboratory, Department of Preventive Medicine, Bioinformatics Center, School of Basic Medical Sciences, School of Software, Institute of Biomedical Informatics, Henan University, Kaifeng, ChinaCell Signal Transduction Laboratory, Department of Preventive Medicine, Bioinformatics Center, School of Basic Medical Sciences, School of Software, Institute of Biomedical Informatics, Henan University, Kaifeng, ChinaCell Signal Transduction Laboratory, Department of Preventive Medicine, Bioinformatics Center, School of Basic Medical Sciences, School of Software, Institute of Biomedical Informatics, Henan University, Kaifeng, ChinaCell Signal Transduction Laboratory, Department of Preventive Medicine, Bioinformatics Center, School of Basic Medical Sciences, School of Software, Institute of Biomedical Informatics, Henan University, Kaifeng, ChinaCell Signal Transduction Laboratory, Department of Preventive Medicine, Bioinformatics Center, School of Basic Medical Sciences, School of Software, Institute of Biomedical Informatics, Henan University, Kaifeng, ChinaCell Signal Transduction Laboratory, Department of Preventive Medicine, Bioinformatics Center, School of Basic Medical Sciences, School of Software, Institute of Biomedical Informatics, Henan University, Kaifeng, ChinaCell Signal Transduction Laboratory, Department of Preventive Medicine, Bioinformatics Center, School of Basic Medical Sciences, School of Software, Institute of Biomedical Informatics, Henan University, Kaifeng, ChinaCell Signal Transduction Laboratory, Department of Preventive Medicine, Bioinformatics Center, School of Basic Medical Sciences, School of Software, Institute of Biomedical Informatics, Henan University, Kaifeng, ChinaDepartment of Anesthesia, Stanford University, Stanford, CA, United StatesHenan Bioengineering Research Center, Zhengzhou, ChinaCell Signal Transduction Laboratory, Department of Preventive Medicine, Bioinformatics Center, School of Basic Medical Sciences, School of Software, Institute of Biomedical Informatics, Henan University, Kaifeng, ChinaBladder cancer (BC) is one of the most common malignant tumors in the 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 in easily evaluating the prognostic potency of genes in BC patients, we developed 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 1,075 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, and 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 set up as optional parameters to meet the specific needs of different researchers. To test the performance of the web server, we have tested and validated its reliability using previously reported prognostic biomarkers, including KPNA2, TP53, and MYC etc., which had their prognostic values validated 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.https://www.frontiersin.org/article/10.3389/fonc.2019.00466/fullbladder cancerprognostic biomarker analysisweb serverkaplan-meier curvecox regression model