Global epigenetic profiling identifies methylation subgroups associated with recurrence-free survival in meningioma

Meningioma is the most common primary brain tumor and carries a substantial risk of local recurrence. Methylation profiles of meningioma and their clinical implications are not well understood. We hypothesized that aggressive meningiomas have unique DNA methylation patterns that could be used to bet...

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Bibliographic Details
Published inActa neuropathologica Vol. 133; no. 3; pp. 431 - 444
Main Authors Olar, Adriana, Wani, Khalida M., Wilson, Charmaine D., Zadeh, Gelareh, DeMonte, Franco, Jones, David T. W., Pfister, Stefan M., Sulman, Erik P., Aldape, Kenneth D.
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2017
Springer
Springer Nature B.V
Subjects
Adult
Aged
Aged, 80 and over
Brain research
Cancer
Disease-Free Survival
DNA Copy Number Variations - genetics
DNA methylation
DNA Methylation - physiology
Epigenetic inheritance
Epigenetics
Epigenomics - methods
Female
Follow-Up Studies
Humans
Ki-67 Antigen - metabolism
Male
Medical prognosis
Medical research
Medicine
Medicine & Public Health
Meningeal Neoplasms - mortality
Meningioma
Meningioma - mortality
Methylation
Middle Aged
Morphology
Neoplasm Recurrence, Local - mortality
Neurosciences
Neurosurgery
Oncology
Original Paper
Pathology
Pediatrics
Radiation therapy
Statistics, Nonparametric
Tumors
Young Adult
Canada
United States > US
Germany
Epigenetics
DNA methylation
Recurrence risk
Copy number aberrations
Molecular subgroups
Meningioma
Online AccessGet full text
ISSN0001-6322
1432-0533
DOI10.1007/s00401-017-1678-x

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Abstract Meningioma is the most common primary brain tumor and carries a substantial risk of local recurrence. Methylation profiles of meningioma and their clinical implications are not well understood. We hypothesized that aggressive meningiomas have unique DNA methylation patterns that could be used to better stratify patient management. Samples ( n  = 140) were profiled using the Illumina HumanMethylation450BeadChip. Unsupervised modeling on a training set ( n  = 89) identified 2 molecular methylation subgroups of meningioma (MM) with significantly different recurrence-free survival (RFS) times between the groups: a prognostically unfavorable subgroup (MM-UNFAV) and a prognostically favorable subgroup (MM-FAV). This finding was validated in the remaining 51 samples and led to a baseline meningioma methylation classifier (bMMC) defined by 283 CpG loci (283-bMMC). To further optimize a recurrence predictor, probes subsumed within the baseline classifier were subject to additional modeling using a similar training/validation approach, leading to a 64-CpG loci meningioma methylation predictor (64-MMP). After adjustment for relevant clinical variables [WHO grade, mitotic index, Simpson grade, sex, location, and copy number aberrations (CNAs)] multivariable analyses for RFS showed that the baseline methylation classifier was not significant ( p  = 0.0793). The methylation predictor, however, was significantly associated with tumor recurrence ( p  < 0.0001). CNAs were extracted from the 450k intensity profiles. Tumor samples in the MM-UNFAV subgroup showed an overall higher proportion of CNAs compared to the MM-FAV subgroup tumors and the CNAs were complex in nature. CNAs in the MM-UNFAV subgroup included recurrent losses of 1p, 6q, 14q and 18q, and gain of 1q, all of which were previously identified as indicators of poor outcome. In conclusion, our analyses demonstrate robust DNA methylation signatures in meningioma that correlate with CNAs and stratify patients by recurrence risk.
AbstractList Meningioma is the most common primary brain tumor and carries a substantial risk of local recurrence. Methylation profiles of meningioma and their clinical implications are not well understood. We hypothesized that aggressive meningiomas have unique DNA methylation patterns that could be used to better stratify patient management. Samples (n = 140) were profiled using the Illumina HumanMethylation450BeadChip. Unsupervised modeling on a training set (n = 89) identified 2 molecular methylation subgroups of meningioma (MM) with significantly different recurrence-free survival (RFS) times between the groups: a prognostically unfavorable subgroup (MM-UNFAV) and a prognostically favorable subgroup (MM-FAV). This finding was validated in the remaining 51 samples and led to a baseline meningioma methylation classifier (bMMC) defined by 283 CpG loci (283-bMMC). To further optimize a recurrence predictor, probes subsumed within the baseline classifier were subject to additional modeling using a similar training/validation approach, leading to a 64-CpG loci meningioma methylation predictor (64-MMP). After adjustment for relevant clinical variables [WHO grade, mitotic index, Simpson grade, sex, location, and copy number aberrations (CNAs)] multivariable analyses for RFS showed that the baseline methylation classifier was not significant (p = 0.0793). The methylation predictor, however, was significantly associated with tumor recurrence (p < 0.0001). CNAs were extracted from the 450k intensity profiles. Tumor samples in the MM-UNFAV subgroup showed an overall higher proportion of CNAs compared to the MM-FAV subgroup tumors and the CNAs were complex in nature. CNAs in the MM-UNFAV subgroup included recurrent losses of 1p, 6q, 14q and 18q, and gain of 1q, all of which were previously identified as indicators of poor outcome. In conclusion, our analyses demonstrate robust DNA methylation signatures in meningioma that correlate with CNAs and stratify patients by recurrence risk.
Meningioma is the most common primary brain tumor and carries a substantial risk of local recurrence. Methylation profiles of meningioma and their clinical implications are not well understood. We hypothesized that aggressive meningiomas have unique DNA methylation patterns that could be used to better stratify patient management. Samples (n = 140) were profiled using the Illumina HumanMethylation450BeadChip. Unsupervised modeling on a training set (n = 89) identified 2 molecular methylation subgroups of meningioma (MM) with significantly different recurrence-free survival (RFS) times between the groups: a prognostically unfavorable subgroup (MM-UNFAV) and a prognostically favorable subgroup (MM-FAV). This finding was validated in the remaining 51 samples and led to a baseline meningioma methylation classifier (bMMC) defined by 283 CpG loci (283-bMMC). To further optimize a recurrence predictor, probes subsumed within the baseline classifier were subject to additional modeling using a similar training/validation approach, leading to a 64-CpG loci meningioma methylation predictor (64-MMP). After adjustment for relevant clinical variables [WHO grade, mitotic index, Simpson grade, sex, location, and copy number aberrations (CNAs)] multivariable analyses for RFS showed that the baseline methylation classifier was not significant (p = 0.0793). The methylation predictor, however, was significantly associated with tumor recurrence (p < 0.0001). CNAs were extracted from the 450k intensity profiles. Tumor samples in the MM-UNFAV subgroup showed an overall higher proportion of CNAs compared to the MM-FAV subgroup tumors and the CNAs were complex in nature. CNAs in the MM-UNFAV subgroup included recurrent losses of 1p, 6q, 14q and 18q, and gain of 1q, all of which were previously identified as indicators of poor outcome. In conclusion, our analyses demonstrate robust DNA methylation signatures in meningioma that correlate with CNAs and stratify patients by recurrence risk.
Meningioma is the most common primary brain tumor and carries a substantial risk of local recurrence. Methylation profiles of meningioma and their clinical implications are not well understood. We hypothesized that aggressive meningiomas have unique DNA methylation patterns that could be used to better stratify patient management. Samples (n=140) were profiled using the Illumina HumanMethylation450 BeadChip. Unsupervised modeling on a training set (n=89) identified 2 molecular methylation subgroups of meningioma (MM) with significantly different recurrence free survival (RFS) times between the groups: a prognostically unfavorable subgroup (MM-UNFAV) and a prognostically favorable subgroup (MM-FAV). This finding was validated in the remaining 51 samples and led to a baseline meningioma methylation classifier (bMMC) defined by 283 CpG loci (283-bMMC). To further optimize a recurrence predictor, probes subsumed within the baseline classifier were subject to additional modeling using a similar training/validation approach, leading to a 64-CpG loci meningioma methylation predictor (64-MMP). After adjustment for relevant clinical variables [WHO grade, mitotic index, Simpson grade, sex, location, and copy number aberrations (CNA)] multivariable analyses for RFS showed that the baseline methylation classifier was not significant (p=0.0793). The methylation predictor however was significantly associated with tumor recurrence (p<0.0001). CNA were extracted from the 450k intensity profiles. Tumor samples in the MM-UNFAV subgroup showed an overall higher proportion of CNAs compared to the MM-FAV subgroup tumors and the CNAs were complex in nature. CNAs in the MM-UNFAV subgroup included recurrent losses of 1p, 6q, 14q and 18q, and gain of 1q, all of which were previously identified as indicators of poor outcome. In conclusion, our analyses demonstrate robust DNA methylation signatures in meningioma that correlate with CNAs and stratify patients by recurrence risk.
Meningioma is the most common primary brain tumor and carries a substantial risk of local recurrence. Methylation profiles of meningioma and their clinical implications are not well understood. We hypothesized that aggressive meningiomas have unique DNA methylation patterns that could be used to better stratify patient management. Samples ( n  = 140) were profiled using the Illumina HumanMethylation450BeadChip. Unsupervised modeling on a training set ( n  = 89) identified 2 molecular methylation subgroups of meningioma (MM) with significantly different recurrence-free survival (RFS) times between the groups: a prognostically unfavorable subgroup (MM-UNFAV) and a prognostically favorable subgroup (MM-FAV). This finding was validated in the remaining 51 samples and led to a baseline meningioma methylation classifier (bMMC) defined by 283 CpG loci (283-bMMC). To further optimize a recurrence predictor, probes subsumed within the baseline classifier were subject to additional modeling using a similar training/validation approach, leading to a 64-CpG loci meningioma methylation predictor (64-MMP). After adjustment for relevant clinical variables [WHO grade, mitotic index, Simpson grade, sex, location, and copy number aberrations (CNAs)] multivariable analyses for RFS showed that the baseline methylation classifier was not significant ( p  = 0.0793). The methylation predictor, however, was significantly associated with tumor recurrence ( p  < 0.0001). CNAs were extracted from the 450k intensity profiles. Tumor samples in the MM-UNFAV subgroup showed an overall higher proportion of CNAs compared to the MM-FAV subgroup tumors and the CNAs were complex in nature. CNAs in the MM-UNFAV subgroup included recurrent losses of 1p, 6q, 14q and 18q, and gain of 1q, all of which were previously identified as indicators of poor outcome. In conclusion, our analyses demonstrate robust DNA methylation signatures in meningioma that correlate with CNAs and stratify patients by recurrence risk.
Audience Academic
Author Wani, Khalida M.
Zadeh, Gelareh
Sulman, Erik P.
DeMonte, Franco
Jones, David T. W.
Pfister, Stefan M.
Aldape, Kenneth D.
Wilson, Charmaine D.
Olar, Adriana
AuthorAffiliation 5 The University of Texas MD Anderson Cancer Center, Dept. of Neurosurgery, 1515 Holcombe Blvd., Houston, TX, 77030, USA
4 MacFeeters-Hamilton Brain Tumour Centre, Princess Margaret Cancer Centre, College Street 101, Toronto, M5G 1L7 Ontario, Canada
8 The University of Texas MD Anderson Cancer Center, Depts. of Radiation Oncology & Genomic Medicine, 1515 Holcombe Blvd., Houston, TX, 77030, USA
3 The University of Texas School of Nursing, Center for Nursing Research, 6901 Bertner St., Houston, TX, 77030, USA
1 Medical University of South Carolina & Hollings Cancer Center, Depts. of Pathology and Laboratory Medicine & Neurosurgery, 171 Ashley Ave., MSC 908, Charleston, SC, 29425, USA
7 Heidelberg University Hospital, Department of Pediatric Hematology and Oncology, Im Neuenheimer Feld 430, 69120 Heidelberg, Germany
6 German Cancer Network (DKTK), German Cancer Research Center (DKFZ), Division of Pediatric Neurooncology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
2 The University of Texa
AuthorAffiliation_xml – name: 2 The University of Texas MD Anderson Cancer Center, Dept. of Translational Molecular Pathology, 2130 W Holcombe Blvd., Houston, TX, 77030, USA
– name: 7 Heidelberg University Hospital, Department of Pediatric Hematology and Oncology, Im Neuenheimer Feld 430, 69120 Heidelberg, Germany
– name: 1 Medical University of South Carolina & Hollings Cancer Center, Depts. of Pathology and Laboratory Medicine & Neurosurgery, 171 Ashley Ave., MSC 908, Charleston, SC, 29425, USA
– name: 4 MacFeeters-Hamilton Brain Tumour Centre, Princess Margaret Cancer Centre, College Street 101, Toronto, M5G 1L7 Ontario, Canada
– name: 6 German Cancer Network (DKTK), German Cancer Research Center (DKFZ), Division of Pediatric Neurooncology, Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
– name: 8 The University of Texas MD Anderson Cancer Center, Depts. of Radiation Oncology & Genomic Medicine, 1515 Holcombe Blvd., Houston, TX, 77030, USA
– name: 5 The University of Texas MD Anderson Cancer Center, Dept. of Neurosurgery, 1515 Holcombe Blvd., Houston, TX, 77030, USA
– name: 3 The University of Texas School of Nursing, Center for Nursing Research, 6901 Bertner St., Houston, TX, 77030, USA
Author_xml – sequence: 1
  givenname: Adriana
  orcidid: 0000-0001-7119-7654
  surname: Olar
  fullname: Olar, Adriana
  email: adriana_olar@yahoo.com, olar@musc.edu
  organization: Departments of Pathology and Laboratory Medicine and Neurosurgery, Medical University of South Carolina and Hollings Cancer Center
– sequence: 2
  givenname: Khalida M.
  surname: Wani
  fullname: Wani, Khalida M.
  organization: Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center
– sequence: 3
  givenname: Charmaine D.
  surname: Wilson
  fullname: Wilson, Charmaine D.
  organization: Center for Nursing Research, The University of Texas School of Nursing
– sequence: 4
  givenname: Gelareh
  surname: Zadeh
  fullname: Zadeh, Gelareh
  organization: Princess Margaret Cancer Centre, MacFeeters-Hamilton Brain Tumour Centre
– sequence: 5
  givenname: Franco
  surname: DeMonte
  fullname: DeMonte, Franco
  organization: Department of Neurosurgery, The University of Texas MD Anderson Cancer Center
– sequence: 6
  givenname: David T. W.
  surname: Jones
  fullname: Jones, David T. W.
  organization: Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Network (DKTK)
– sequence: 7
  givenname: Stefan M.
  surname: Pfister
  fullname: Pfister, Stefan M.
  organization: Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ), German Cancer Network (DKTK), Department of Pediatric Hematology and Oncology, Heidelberg University Hospital
– sequence: 8
  givenname: Erik P.
  surname: Sulman
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– sequence: 9
  givenname: Kenneth D.
  surname: Aldape
  fullname: Aldape, Kenneth D.
  organization: Princess Margaret Cancer Centre, MacFeeters-Hamilton Brain Tumour Centre
BackLink https://www.ncbi.nlm.nih.gov/pubmed/28130639$$D View this record in MEDLINE/PubMed
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ContentType Journal Article
Copyright Springer-Verlag Berlin Heidelberg 2017
COPYRIGHT 2017 Springer
Acta Neuropathologica is a copyright of Springer, 2017.
Copyright_xml – notice: Springer-Verlag Berlin Heidelberg 2017
– notice: COPYRIGHT 2017 Springer
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Keywords Epigenetics
DNA methylation
Recurrence risk
Copy number aberrations
Molecular subgroups
Meningioma
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Hovestadt, Remke, Kool, Pietsch, Northcott, Fischer, Cavalli, Ramaswamy, Zapatka, Reifenberger, Rutkowski, Schick, Bewerunge-Hudler, Korshunov, Lichter, Taylor, Pfister, Jones (CR29) 2013; 125
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Snippet Meningioma is the most common primary brain tumor and carries a substantial risk of local recurrence. Methylation profiles of meningioma and their clinical...
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SubjectTerms Adult
Aged
Aged, 80 and over
Brain research
Cancer
Disease-Free Survival
DNA Copy Number Variations - genetics
DNA methylation
DNA Methylation - physiology
Epigenetic inheritance
Epigenetics
Epigenomics - methods
Female
Follow-Up Studies
Humans
Ki-67 Antigen - metabolism
Male
Medical prognosis
Medical research
Medicine
Medicine & Public Health
Meningeal Neoplasms - mortality
Meningioma
Meningioma - mortality
Methylation
Middle Aged
Morphology
Neoplasm Recurrence, Local - mortality
Neurosciences
Neurosurgery
Oncology
Original Paper
Pathology
Pediatrics
Radiation therapy
Statistics, Nonparametric
Tumors
Young Adult
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Title Global epigenetic profiling identifies methylation subgroups associated with recurrence-free survival in meningioma
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