Skip to main content
Top
Published in: BMC Cancer 1/2018

Open Access 01-12-2018 | Research article

Clinical significance of FBXO17 gene expression in high-grade glioma

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

Published in: BMC Cancer | Issue 1/2018

Login to get access

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 < 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.

Conclusion

Epigenetically modulated FBXO17 has a potential as a stratification factor for clinical decision-making in HGG.
Appendix
Available only for authorised users
Literature
1.
go back to reference Stewart LA. Chemotherapy in adult high-grade glioma: a systematic review and meta-analysis of individual patient data from 12 randomised trials. Lancet. 2002;359(9311):1011–8.CrossRefPubMed Stewart LA. Chemotherapy in adult high-grade glioma: a systematic review and meta-analysis of individual patient data from 12 randomised trials. Lancet. 2002;359(9311):1011–8.CrossRefPubMed
2.
go back to reference Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, et al. The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol. 2016;131(6):803–20.CrossRefPubMed Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, et al. The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol. 2016;131(6):803–20.CrossRefPubMed
3.
go back to reference Phillips HS, Kharbanda S, Chen R, Forrest WF, Soriano RH, Wu TD. Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell. 2006;9:157–73.CrossRefPubMed Phillips HS, Kharbanda S, Chen R, Forrest WF, Soriano RH, Wu TD. Molecular subclasses of high-grade glioma predict prognosis, delineate a pattern of disease progression, and resemble stages in neurogenesis. Cancer Cell. 2006;9:157–73.CrossRefPubMed
4.
go back to reference Liang Y, Diehn M, Watson N, Bollen AW, Aldape KD, Nicholas MK. Gene expression profiling reveals molecularly and clinically distinct subtypes of glioblastoma multiforme. Proc Natl Acad Sci U S A. 2005;102:5814–9.CrossRefPubMedPubMedCentral Liang Y, Diehn M, Watson N, Bollen AW, Aldape KD, Nicholas MK. Gene expression profiling reveals molecularly and clinically distinct subtypes of glioblastoma multiforme. Proc Natl Acad Sci U S A. 2005;102:5814–9.CrossRefPubMedPubMedCentral
5.
go back to reference Colman H, Zhang L, Sulman EP, Matthew J, Nasrin M, Shooshtari L, et al. A multigene predictor of outcome in glioblastoma. Neuro-Oncology. 2010;12(1):49–57.CrossRefPubMed Colman H, Zhang L, Sulman EP, Matthew J, Nasrin M, Shooshtari L, et al. A multigene predictor of outcome in glioblastoma. Neuro-Oncology. 2010;12(1):49–57.CrossRefPubMed
6.
go back to reference Kleihues P, Cavenee W. WHO Classificationof Tumours: pathology and genetics of Tumours of the nervous system. Lyon: IARC Press; 2000. Kleihues P, Cavenee W. WHO Classificationof Tumours: pathology and genetics of Tumours of the nervous system. Lyon: IARC Press; 2000.
7.
go back to reference Hegi ME, Liu L, Herman JG, Stupp R, Wick W, Weller M, et al. Correlation of O6-methylguanine methyltransferase (MGMT) promoter methylation with clinical outcomes in glioblastoma and clinical strategies to modulate MGMT activity. J Clin Oncol. 2008;26:4189–99.CrossRefPubMed Hegi ME, Liu L, Herman JG, Stupp R, Wick W, Weller M, et al. Correlation of O6-methylguanine methyltransferase (MGMT) promoter methylation with clinical outcomes in glioblastoma and clinical strategies to modulate MGMT activity. J Clin Oncol. 2008;26:4189–99.CrossRefPubMed
8.
go back to reference Hegi ME, Diserens AC, Gorlia T, Hamou MF, deTribolet N, Weller M. MGMT gene silencing and benefit from temozolomide in glioblastoma. N Engl J Med. 2005;352:997–1003.CrossRefPubMed Hegi ME, Diserens AC, Gorlia T, Hamou MF, deTribolet N, Weller M. MGMT gene silencing and benefit from temozolomide in glioblastoma. N Engl J Med. 2005;352:997–1003.CrossRefPubMed
9.
go back to reference Freije WA, Castro-Vargas FE, Fang Z, Horvath S, Cloughesy T, Liau LM. Gene expression profiling of gliomas strongly predicts survival. Cancer Res. 2004;64:6503–10.CrossRefPubMed Freije WA, Castro-Vargas FE, Fang Z, Horvath S, Cloughesy T, Liau LM. Gene expression profiling of gliomas strongly predicts survival. Cancer Res. 2004;64:6503–10.CrossRefPubMed
10.
go back to reference Nutt CL, Mani DR, Betensky RA, Tamayo P, Cairncross JG, Ladd C. Gene expression-based classificaiton of malignant gliomas correlates better with survival than histological classification. Cancer Res. 2003;63:1602–7.PubMed Nutt CL, Mani DR, Betensky RA, Tamayo P, Cairncross JG, Ladd C. Gene expression-based classificaiton of malignant gliomas correlates better with survival than histological classification. Cancer Res. 2003;63:1602–7.PubMed
11.
go back to reference Tayrac M, Aubry M, Saikli S, Etcheverry A, Surbled C, Guenot F, et al. A 4-gene signature associated with clinical outcome in high-grade gliomas. Clin Cancer Res. 2011;17(2):317–27.CrossRefPubMed Tayrac M, Aubry M, Saikli S, Etcheverry A, Surbled C, Guenot F, et al. A 4-gene signature associated with clinical outcome in high-grade gliomas. Clin Cancer Res. 2011;17(2):317–27.CrossRefPubMed
12.
go back to reference Arimappamagan A, Somassundaram K, Thennarasu K, Peddagangannagari S, Srinivasan H, Shailaja BC, et al. A fourteen gene GBM prognostic signature identifies association of immune response pathway and mesenchymal subtype with high risk group. PLoS One. 2013;8(4):e62042.CrossRefPubMedPubMedCentral Arimappamagan A, Somassundaram K, Thennarasu K, Peddagangannagari S, Srinivasan H, Shailaja BC, et al. A fourteen gene GBM prognostic signature identifies association of immune response pathway and mesenchymal subtype with high risk group. PLoS One. 2013;8(4):e62042.CrossRefPubMedPubMedCentral
13.
go back to reference Colman H, Aldape K. Molecular predictors in glioblastoma: toward personalized therapy. Arch Neurol. 2008;65:877–83.CrossRefPubMed Colman H, Aldape K. Molecular predictors in glioblastoma: toward personalized therapy. Arch Neurol. 2008;65:877–83.CrossRefPubMed
14.
go back to reference Hong F, Breitling R. A comparison of meta-analysis methods for detecting differentially expressed genes in microarray experiments. Bioinformatics. 2008;24:374–82.CrossRefPubMed Hong F, Breitling R. A comparison of meta-analysis methods for detecting differentially expressed genes in microarray experiments. Bioinformatics. 2008;24:374–82.CrossRefPubMed
15.
go back to reference The Cancer Genome Atlas Research Network. The somatic genomic landscape of glioblastoma. Cell. 2013;155(2):462–77.CrossRef The Cancer Genome Atlas Research Network. The somatic genomic landscape of glioblastoma. Cell. 2013;155(2):462–77.CrossRef
16.
go back to reference TCGA. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008;455:1061–8.CrossRef TCGA. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008;455:1061–8.CrossRef
17.
go back to reference Du D, Ma W, Yates MS, Chen T, Lu KH, Lu Y, et al. High-risk endometrioid carcinomas using proteins. Oncotarget. 2018;9:19704–15.PubMedPubMedCentral Du D, Ma W, Yates MS, Chen T, Lu KH, Lu Y, et al. High-risk endometrioid carcinomas using proteins. Oncotarget. 2018;9:19704–15.PubMedPubMedCentral
18.
go back to reference Newlands ES, Stevens MF, Wedge SR, Wheelhouse RT, Brock C. Temozolomide: a review of its discovery, chemical properties, pre-clinical development and clinical trials. Cancer Treat Rev. 1997;23(1):35–61.CrossRefPubMed Newlands ES, Stevens MF, Wedge SR, Wheelhouse RT, Brock C. Temozolomide: a review of its discovery, chemical properties, pre-clinical development and clinical trials. Cancer Treat Rev. 1997;23(1):35–61.CrossRefPubMed
19.
go back to reference Glenn KA, Nelson RF, Wen HM, Mallinger AJ, Paulson HL. Diversity in tissue expression, substrate binding, and SCF complex formation for a lectin family of ubiquitin ligases. J Biol Chem. 2008;283:12717–29.CrossRefPubMedPubMedCentral Glenn KA, Nelson RF, Wen HM, Mallinger AJ, Paulson HL. Diversity in tissue expression, substrate binding, and SCF complex formation for a lectin family of ubiquitin ligases. J Biol Chem. 2008;283:12717–29.CrossRefPubMedPubMedCentral
20.
go back to reference Yoshida Y, Tokunaga F, Chiba T, Iwai K, Tanaka K, Tai T. Fbs2 is a new member of the E3 ubiquitin ligase family that recognizes sugar chains. J Biol Chem. 2003;278:43877–84.CrossRefPubMed Yoshida Y, Tokunaga F, Chiba T, Iwai K, Tanaka K, Tai T. Fbs2 is a new member of the E3 ubiquitin ligase family that recognizes sugar chains. J Biol Chem. 2003;278:43877–84.CrossRefPubMed
21.
go back to reference Bell A, Bell D, Weber RS, Ei-Naggar AK. CpG island methylation profiling in human salivary gland adenoid cystic carcinoma. Cancer. 2011;117(13):2898–909.CrossRefPubMedPubMedCentral Bell A, Bell D, Weber RS, Ei-Naggar AK. CpG island methylation profiling in human salivary gland adenoid cystic carcinoma. Cancer. 2011;117(13):2898–909.CrossRefPubMedPubMedCentral
22.
go back to reference Noushmehr H, Weisenberger DJ, Diefes K, Philips HS, Pujara K, Berman BP et al. Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. Cancer Cell. 2010;17(5):510-22. Noushmehr H, Weisenberger DJ, Diefes K, Philips HS, Pujara K, Berman BP et al. Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. Cancer Cell. 2010;17(5):510-22.
23.
go back to reference Liu Y, Sun Y, Broaddus R, Liu J, Sood AK, Shmulevich J, et al. Integrated analysis of gene expression and tumor nuclear image profiles associated with chemotherapy response in serous ovarian carcinoma. PLoS One. 2012;7(5):e36383.CrossRefPubMedPubMedCentral Liu Y, Sun Y, Broaddus R, Liu J, Sood AK, Shmulevich J, et al. Integrated analysis of gene expression and tumor nuclear image profiles associated with chemotherapy response in serous ovarian carcinoma. PLoS One. 2012;7(5):e36383.CrossRefPubMedPubMedCentral
Metadata
Title
Clinical significance of FBXO17 gene expression in high-grade glioma
Authors
Di Du
Jian Yuan
Wencai Ma
Jing Ning
John N. Weinstein
Xianrui Yuan
Greg N. Fuller
Yuexin Liu
Publication date
01-12-2018
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2018
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/s12885-018-4680-3

Other articles of this Issue 1/2018

BMC Cancer 1/2018 Go to the issue
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine