Image_1_OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma.TIF (970.57 kB)

Image_1_OSlgg: An Online Prognostic Biomarker Analysis Tool for Low-Grade Glioma.TIF

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posted on 07.07.2020 by Yang An, Qiang Wang, Lu Zhang, Fengjie Sun, Guosen Zhang, Huan Dong, Yingkun Li, Yanyu Peng, Haojie Li, Wan Zhu, Shaoping Ji, Yunlong Wang, Xiangqian Guo

Glioma is the most frequent primary brain tumor that causes high mortality and morbidity with poor prognosis. There are four grades of gliomas, I to IV, among which grade II and III are low-grade glioma (LGG). Although less aggressive, LGG almost universally progresses to high-grade glioma and eventual causes death if lacking of intervention. Current LGG treatment mainly depends on surgical resection followed by radiotherapy and chemotherapy, but the survival rates of LGG patients are low. Therefore, it is necessary to use prognostic biomarkers to classify patients into subgroups with different risks and guide clinical managements. Using gene expression profiling and long-term follow-up data, we established an Online consensus Survival analysis tool for LGG named OSlgg. OSlgg is comprised of 720 LGG cases from two independent cohorts. To evaluate the prognostic potency of genes, OSlgg employs the Kaplan-Meier plot with hazard ratio and p value to assess the prognostic significance of genes of interest. The reliability of OSlgg was verified by analyzing 86 previously published prognostic biomarkers of LGG. Using OSlgg, we discovered two novel potential prognostic biomarkers (CD302 and FABP5) of LGG, and patients with the elevated expression of either CD302 or FABP5 present the unfavorable survival outcome. These two genes may be novel risk predictors for LGG patients after further validation. OSlgg is public and free to the users at