Abstract
BackgroundHigh-grade gliomas (HGGs) exhibit marked heterogeneity in clinical behavior. The purpose of this study was to identify a novel biomarker that predicts patient outcome, which is helpful in HGG patient management.MethodsWe analyzed gene expression profiles of 833 HGG cases, representing the largest patient population ever reported. Using the data set from the Cancer Genome Atlas (TCGA) and random partitioning approach, we performed Cox proportional hazards model analysis to identify novel prognostic mRNAs in HGG. The predictive capability was further assessed via multivariate analysis and validated in 4 additional data sets. The Kaplan-Meier method was used to evaluate survival difference between dichotomic groups of patients. Correlation of gene expression and DNA methylation was evaluated via Student’s t-test.ResultsPatients with elevated FBXO17 expression had a significantly shorter overall survival (OS) (P = 0.0011). After adjustment by IDH1 mutation, sex, and patient age, FBXO17 gene expression was significantly associated with OS (HR = 1.29, 95% CI =1.04–1.59, P = 0.018). In addition, FBXO17 expression can significantly distinguish patients by OS not only among patients who received temozolomide chemotherapy (HR 1.35, 95% CI =1.12–1.64, P = 0.002) but also among those who did not (HR = 1.48, 95% CI =1.20–1.82, P < 0.0001). The significant association of FBXO17 gene expression with OS was further validated in four external data sets. We further found that FBXO17 endogenous expression is significantly contributable from its promoter methylation.ConclusionEpigenetically modulated FBXO17 has a potential as a stratification factor for clinical decision-making in HGG.
Highlights
High-grade gliomas (HGGs) exhibit marked heterogeneity in clinical behavior
HGGs are classified as either grade III or grade IV on the basis of histopathologic features established by the World Health Organization [2]
To mimic a large number of data sets for biomarker identification, in this study we developed a random-partitioning methodology and used it in a training set with a large patient population to identify a novel biomarker, F-box protein 17 (FBXO17), that predicts patient outcome in HGG
Summary
High-grade gliomas (HGGs) exhibit marked heterogeneity in clinical behavior. HGGs are classified as either grade III or grade IV (referred to as glioblastoma multiforme, GBM) on the basis of histopathologic features established by the World Health Organization [2]. These tumors demonstrate marked heterogeneity in clinical behavior, with survival durations ranging from less than 1 month to a few years. To the best of our knowledge, we, for the first time, developed this approach and applied it to identify a robust biomarker that could predict patient prognosis in HGG
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