OSgbm: An Online Consensus Survival Analysis Web Server for Glioblastoma

Huan Dong; Qiang Wang; Ning Li; Jiajia Lv; Linna Ge; Mengsi Yang; Guosen Zhang; Yang An; Fengling Wang; Longxiang Xie; Yongqiang Li; Wan Zhu; Haiyu Zhang; Minghang Zhang; Xiangqian Guo

doi:10.3389/fgene.2019.01378

OSgbm: An Online Consensus Survival Analysis Web Server for Glioblastoma

Front Genet. 2020 Feb 21:10:1378. doi: 10.3389/fgene.2019.01378. eCollection 2019.

Authors

Huan Dong¹, Qiang Wang¹, Ning Li¹, Jiajia Lv¹, Linna Ge¹, Mengsi Yang¹, Guosen Zhang¹, Yang An¹, Fengling Wang¹, Longxiang Xie¹, Yongqiang Li¹, Wan Zhu², Haiyu Zhang³, Minghang Zhang⁴, Xiangqian Guo¹

Affiliations

¹ Department of Predictive Medicine, Institute of Biomedical Informatics, Cell Signal Transduction Laboratory, Bioinformatics Center, Henan Provincial Engineering Center for Tumor Molecular Medicine, School of Software, School of Basic Medical Sciences, Henan University, Kaifeng, China.
² Department of Anesthesia, Stanford University School of Medicine, Stanford, CA, United States.
³ Department of Pathology, Stanford University School of Medicine, Stanford, CA, United States.
⁴ Nanjing Jiliang Biotechnology Co., Ltd., Nanjing, China.

Abstract

Glioblastoma (GBM) is the most common malignant tumor of the central nervous system. GBM causes poor clinical outcome and high mortality rate, mainly due to the lack of effective targeted therapy and prognostic biomarkers. Here, we developed a user-friendly Online Survival analysis web server for GlioBlastoMa, abbreviated OSgbm, to assess the prognostic value of candidate genes. Currently, OSgbm contains 684 samples with transcriptome profiles and clinical information from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and Chinese Glioma Genome Atlas (CGGA). The survival analysis results can be graphically presented by Kaplan-Meier (KM) plot with Hazard ratio (HR) and log-rank p value. As demonstration, the prognostic value of 51 previously reported survival associated biomarkers, such as PROM1 (HR = 2.4120, p = 0.0071) and CXCR4 (HR = 1.5578, p < 0.001), were confirmed in OSgbm. In summary, OSgbm allows users to evaluate and develop prognostic biomarkers of GBM. The web server of OSgbm is available at http://bioinfo.henu.edu.cn/GBM/GBMList.jsp.

Keywords: OSgbm; clinical information; glioblastoma; prognostic biomarker; survival analysis; transcriptome profiles.