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Clinical significance of FBXO17 gene expression in high-grade glioma

Overview of attention for article published in BMC Cancer, July 2018
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Title
Clinical significance of FBXO17 gene expression in high-grade glioma
Published in
BMC Cancer, July 2018
DOI 10.1186/s12885-018-4680-3
Pubmed ID
Authors

Di Du, Jian Yuan, Wencai Ma, Jing Ning, John N. Weinstein, Xianrui Yuan, Greg N. Fuller, Yuexin Liu

Abstract

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. 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. 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 < 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. Epigenetically modulated FBXO17 has a potential as a stratification factor for clinical decision-making in HGG.

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Mendeley readers

The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 36%
Other 2 18%
Student > Bachelor 1 9%
Researcher 1 9%
Student > Postgraduate 1 9%
Other 0 0%
Unknown 2 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 2 18%
Engineering 2 18%
Psychology 1 9%
Biochemistry, Genetics and Molecular Biology 1 9%
Medicine and Dentistry 1 9%
Other 1 9%
Unknown 3 27%