Cargando…

Quantitative analysis of MGMT promoter methylation in glioblastoma suggests nonlinear prognostic effect

BACKGROUND: Epigenetic inhibition of the O6-methylguanine-DNA-methyltransferase (MGMT) gene has emerged as a clinically relevant prognostic marker in glioblastoma (GBM). Methylation of the MGMT promoter has been shown to increase chemotherapy efficacy. While traditionally reported as a binary marker...

Descripción completa

Detalles Bibliográficos
Autores principales: Gibson, David, Ravi, Akshay, Rodriguez, Eduardo, Chang, Susan, Oberheim Bush, Nancy, Taylor, Jennie, Clarke, Jennifer, Solomon, David, Scheffler, Aaron, Witte, John, Lambing, Hannah, Okada, Hideho, Berger, Mitchel, Chehab, Farid, Butowski, Nicholas A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611422/
https://www.ncbi.nlm.nih.gov/pubmed/37899778
http://dx.doi.org/10.1093/noajnl/vdad115
_version_ 1785128487775895552
author Gibson, David
Ravi, Akshay
Rodriguez, Eduardo
Chang, Susan
Oberheim Bush, Nancy
Taylor, Jennie
Clarke, Jennifer
Solomon, David
Scheffler, Aaron
Witte, John
Lambing, Hannah
Okada, Hideho
Berger, Mitchel
Chehab, Farid
Butowski, Nicholas A
author_facet Gibson, David
Ravi, Akshay
Rodriguez, Eduardo
Chang, Susan
Oberheim Bush, Nancy
Taylor, Jennie
Clarke, Jennifer
Solomon, David
Scheffler, Aaron
Witte, John
Lambing, Hannah
Okada, Hideho
Berger, Mitchel
Chehab, Farid
Butowski, Nicholas A
author_sort Gibson, David
collection PubMed
description BACKGROUND: Epigenetic inhibition of the O6-methylguanine-DNA-methyltransferase (MGMT) gene has emerged as a clinically relevant prognostic marker in glioblastoma (GBM). Methylation of the MGMT promoter has been shown to increase chemotherapy efficacy. While traditionally reported as a binary marker, recent methodological advancements have led to quantitative methods of measuring promoter methylation, providing clearer insight into its functional relationship with survival. METHODS: A CLIA assay and bisulfite sequencing was utilized to develop a quantitative, 17-point, MGMT promoter methylation index. GBMs of 240 newly diagnosed patients were sequenced and risk for mortality was assessed. Nonlinearities were captured by fitting splines to Cox proportional hazard models and plotting smoothed residuals. Covariates included age, Karnofsky performance status, IDH1 mutation, and extent of resection. RESULTS: Median follow-up time and progression-free survival were 16 and 9 months, respectively. A total of 176 subjects experienced death. A one-unit increase in promoter CpG methylation resulted in a 4% reduction in hazard (95% CI 0.93–0.99, P < .005). GBM patients with low levels of promoter methylation (1-6 CpG sites) fared markedly worse (HR = 1.62, 95% CI 1.03–2.54, P < .036) than individuals who were unmethylated. Subjects with medium levels of promoter methylation (7–12 sites) had the greatest reduction in hazard (HR = 0.48, 95% CI 0.29–0.80, P < .004), followed by individuals in the highest promoter methylation tertile (HR = 0.62, 95% CI 0.40–0.97, P < .035). CONCLUSIONS: Our findings suggest that the relationship between the extent of MGMT promoter methylation and survival in GBM may be nonlinear. These findings challenge the current understanding of MGMT and underlines the clinical importance of determining its prognostic utility. Potential limitations include censoring, sample size, and extraneous mutations.
format Online
Article
Text
id pubmed-10611422
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher Oxford University Press
record_format MEDLINE/PubMed
spelling pubmed-106114222023-10-28 Quantitative analysis of MGMT promoter methylation in glioblastoma suggests nonlinear prognostic effect Gibson, David Ravi, Akshay Rodriguez, Eduardo Chang, Susan Oberheim Bush, Nancy Taylor, Jennie Clarke, Jennifer Solomon, David Scheffler, Aaron Witte, John Lambing, Hannah Okada, Hideho Berger, Mitchel Chehab, Farid Butowski, Nicholas A Neurooncol Adv Basic and Translational Investigations BACKGROUND: Epigenetic inhibition of the O6-methylguanine-DNA-methyltransferase (MGMT) gene has emerged as a clinically relevant prognostic marker in glioblastoma (GBM). Methylation of the MGMT promoter has been shown to increase chemotherapy efficacy. While traditionally reported as a binary marker, recent methodological advancements have led to quantitative methods of measuring promoter methylation, providing clearer insight into its functional relationship with survival. METHODS: A CLIA assay and bisulfite sequencing was utilized to develop a quantitative, 17-point, MGMT promoter methylation index. GBMs of 240 newly diagnosed patients were sequenced and risk for mortality was assessed. Nonlinearities were captured by fitting splines to Cox proportional hazard models and plotting smoothed residuals. Covariates included age, Karnofsky performance status, IDH1 mutation, and extent of resection. RESULTS: Median follow-up time and progression-free survival were 16 and 9 months, respectively. A total of 176 subjects experienced death. A one-unit increase in promoter CpG methylation resulted in a 4% reduction in hazard (95% CI 0.93–0.99, P < .005). GBM patients with low levels of promoter methylation (1-6 CpG sites) fared markedly worse (HR = 1.62, 95% CI 1.03–2.54, P < .036) than individuals who were unmethylated. Subjects with medium levels of promoter methylation (7–12 sites) had the greatest reduction in hazard (HR = 0.48, 95% CI 0.29–0.80, P < .004), followed by individuals in the highest promoter methylation tertile (HR = 0.62, 95% CI 0.40–0.97, P < .035). CONCLUSIONS: Our findings suggest that the relationship between the extent of MGMT promoter methylation and survival in GBM may be nonlinear. These findings challenge the current understanding of MGMT and underlines the clinical importance of determining its prognostic utility. Potential limitations include censoring, sample size, and extraneous mutations. Oxford University Press 2023-09-19 /pmc/articles/PMC10611422/ /pubmed/37899778 http://dx.doi.org/10.1093/noajnl/vdad115 Text en © The Author(s) 2023. Published by Oxford University Press, the Society for Neuro-Oncology and the European Association of Neuro-Oncology. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Basic and Translational Investigations
Gibson, David
Ravi, Akshay
Rodriguez, Eduardo
Chang, Susan
Oberheim Bush, Nancy
Taylor, Jennie
Clarke, Jennifer
Solomon, David
Scheffler, Aaron
Witte, John
Lambing, Hannah
Okada, Hideho
Berger, Mitchel
Chehab, Farid
Butowski, Nicholas A
Quantitative analysis of MGMT promoter methylation in glioblastoma suggests nonlinear prognostic effect
title Quantitative analysis of MGMT promoter methylation in glioblastoma suggests nonlinear prognostic effect
title_full Quantitative analysis of MGMT promoter methylation in glioblastoma suggests nonlinear prognostic effect
title_fullStr Quantitative analysis of MGMT promoter methylation in glioblastoma suggests nonlinear prognostic effect
title_full_unstemmed Quantitative analysis of MGMT promoter methylation in glioblastoma suggests nonlinear prognostic effect
title_short Quantitative analysis of MGMT promoter methylation in glioblastoma suggests nonlinear prognostic effect
title_sort quantitative analysis of mgmt promoter methylation in glioblastoma suggests nonlinear prognostic effect
topic Basic and Translational Investigations
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10611422/
https://www.ncbi.nlm.nih.gov/pubmed/37899778
http://dx.doi.org/10.1093/noajnl/vdad115
work_keys_str_mv AT gibsondavid quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT raviakshay quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT rodriguezeduardo quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT changsusan quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT oberheimbushnancy quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT taylorjennie quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT clarkejennifer quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT solomondavid quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT scheffleraaron quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT wittejohn quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT lambinghannah quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT okadahideho quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT bergermitchel quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT chehabfarid quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect
AT butowskinicholasa quantitativeanalysisofmgmtpromotermethylationinglioblastomasuggestsnonlinearprognosticeffect