OSgbm: An Online Consensus Survival Analysis Web Server for Glioblastoma

• Main Authors: 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
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2020-02-01
• Series: Frontiers in Genetics
• Subjects: glioblastoma; survival analysis; prognostic biomarker; OSgbm; transcriptome profiles; clinical information
• Online Access: https://www.frontiersin.org/article/10.3389/fgene.2019.01378/full
• ISSN: 1664-8021

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.