Open AccessA GLO10 score for the prediction of prognosis in high grade gliomas
Author(s) -
Feng Chen,
Peng Peng,
Yi Zhou,
Zhenyu Yang,
Haiquan Zhang,
Xiang-Sheng Ao,
Daohong Zhou,
Chunxiang Xiang
Publication year - 2017
Publication title -
oncotarget
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.373
H-Index - 127
ISSN - 1949-2553
DOI - 10.18632/oncotarget.20195
Subject(s) - medicine , glioblastoma , oncology , glioma , proportional hazards model , pathological , cohort , cancer research
Gliomas are the most common lethal brain tumours and remain great heterogeneity in terms of histopathology and clinical outcomes. Among them, glioblastomas are the most aggressive tumours that lead to a median of less than one-year survival in patients. Despite the little improvement of in diagnosis and treatments for last decades, there is an urgent need for prognostic markers to distinguish high- and low-risk patients before treatment.Here, we generated a list of genes associated with glioblastoma progressions and then performed a comprehensive statistical modelling strategy to derive a 10-gene (GLO10) score from genome wide expression profiles of a large glioblastoma cohort (n=844). Our study demonstrated that the GLO10 score could successfully distinguish high- and low-risk patients with glioblastomas regardless their traditional pathological factors. Validated in four independent cohorts, the utility of GLO10 score could provide clinicians a robust prognostic prediction tool to assess risk levels upfront treatments.