Dataset Information

Clinical significance of FBXO17 gene expression in high-grade glioma.

ABSTRACT:

Background

High-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.

Methods

We 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.

Results

Patients 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?ConclusionEpigenetically modulated FBXO17 has a potential as a stratification factor for clinical decision-making in HGG.

SUBMITTER: Du D

PROVIDER: S-EPMC6069786 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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Publications

Clinical significance of FBXO17 gene expression in high-grade glioma.

Du Di D Yuan Jian J Ma Wencai W Ning Jing J Weinstein John N JN Yuan Xianrui X Fuller Greg N GN Liu Yuexin Y

BMC cancer 20180731 1

<h4>Background</h4>High-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.<h4>Methods</h4>We 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 analysi ...[more]

PMID: 30064493

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Dataset Information

Clinical significance of FBXO17 gene expression in high-grade glioma.

Background

Methods

Results

Publications

Clinical significance of FBXO17 gene expression in high-grade glioma.

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