Qiang Wang1, Lu Zhang1, Zhongyi Yan1, Longxiang Xie1, Yang An1, Huimin Li1, Yali Han1, Guosen Zhang1, Huan Dong1, Hong Zheng1, Wan Zhu2, Yongqiang Li1, Yunlong Wang3, Xiangqian Guo1. 1. Department of Preventive Medicine, Institute of Biomedical Informatics, Kaifeng Municipal Key Laboratory of Cell Signal Transduction, Bioinformatics Center, Henan Provincial Engineering Centre for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng 475004, PR China. 2. Department of Anesthesia, Stanford University, Stanford, CA 94305, USA. 3. Henan Bioengineering Research Center, Zhengzhou 450046, PR China.
Abstract
Aim: To establish a web server that can mutually validate prognostic biomarkers of cervical cancer. Methods: Four datasets including expression profiling and relative clinical follow-up data were collected from Gene Expression Omnibus and The Cancer Genome Atlas. The web server was developed by R software. Results: The web server was named OScc including 690 patients and can be accessed at http://bioinfo.henu.edu.cn/CESC/CESCList.jsp. The Kaplan-Meier survival curves with log-rank p-value and hazard ratio will be generated of interested gene in OScc. Compared with previous predictive tools, OScc had the advantages of registration-free, larger sample size and subgroup analysis. Conclusion: The OScc is highly valuable to perform the preliminary assessment and validation of new or interested prognostic biomarkers for cervical cancer.
Aim: To establish a web server that can mutually validate prognostic biomarkers of cervical cancer. Methods: Four datasets including expression profiling and relative clinical follow-up data were collected from Gene Expression Omnibus and The Cancer Genome Atlas. The web server was developed by R software. Results: The web server was named OScc including 690 patients and can be accessed at http://bioinfo.henu.edu.cn/CESC/CESCList.jsp. The Kaplan-Meier survival curves with log-rank p-value and hazard ratio will be generated of interested gene in OScc. Compared with previous predictive tools, OScc had the advantages of registration-free, larger sample size and subgroup analysis. Conclusion: The OScc is highly valuable to perform the preliminary assessment and validation of new or interested prognostic biomarkers for cervical cancer.
Entities:
Keywords:
biomarker; cervical cancer; prognosis; survival analysis; web server