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Stability of the CpG island methylator phenotype during glioma progression and identification of methylated loci in secondary glioblastomas
© Hill et al.; licensee BioMed Central Ltd. 2014
Received: 13 December 2013
Accepted: 2 July 2014
Published: 10 July 2014
Grade IV glioblastomas exist in two forms, primary (de novo) glioblastomas (pGBM) that arise without precursor lesions, and the less common secondary glioblastomas (sGBM) which develop from earlier lower grade lesions. Genetic heterogeneity between pGBM and sGBM has been documented as have differences in the methylation of individual genes. A hypermethylator phenotype in grade IV GBMs is now well documented however there has been little comparison between global methylation profiles of pGBM and sGBM samples or of methylation profiles between paired early and late sGBM samples.
We performed genome-wide methylation profiling of 20 matched pairs of early and late gliomas using the Infinium HumanMethylation450 BeadChips to assess methylation at >485,000 cytosine positions within the human genome.
Clustering of our data demonstrated a frequent hypermethylator phenotype that associated with IDH1 mutation in sGBM tumors. In 80% of cases, the hypermethylator status was retained in both the early and late tumor of the same patient, indicating limited alterations to genome-wide methylation during progression and that the CIMP phenotype is an early event. Analysis of hypermethylated loci identified 218 genes frequently methylated across grade II, III and IV tumors indicating a possible role in sGBM tumorigenesis. Comparison of our sGBM data with TCGA pGBM data indicate that IDH1 mutated GBM samples have very similar hypermethylator phenotypes, however the methylation profiles of the majority of samples with WT IDH1 that do not demonstrate a hypermethylator phenotype cluster separately from sGBM samples, indicating underlying differences in methylation profiles. We also identified 180 genes that were methylated only in sGBM. Further analysis of these genes may lead to a better understanding of the pathology of sGBM vs pGBM.
This is the first study to have documented genome-wide methylation changes within paired early/late astrocytic gliomas on such a large CpG probe set, revealing a number of genes that maybe relevant to secondary gliomagenesis.
Gliomas are classified into 4 grades according to the WHO classification system. These range from curable World Health Organization (WHO) grade I tumors (pilocytic astrocytomas) to the highly malignant WHO grade IV glioblastoma (GBM) with mean survival < 1year. In between these two grades are WHO grade III malignant tumors (anaplastic astrocytomas) with median survival rates of 2–3 years after diagnosis and WHO grade II (diffuse astrocytomas) considered as low grade gliomas with median survival rates of 6–8 years after diagnosis [1, 2]. Glioblastomas are subdivided into 2 distinct types, primary grade IV glioblastoma (pGBM or de novo glioblastomas) that account for >90% of the cases, usually affecting older patients and develop rapidly after a short clinical history and without evidence of a less malignant precursor lesion. While secondary glioblastomas (sGBM) develop slowly through progression from lower grade diffuse or anaplastic astrocytomas and more commonly occur in younger patients. pGBM and sGBM represent not only clinically distinct entities but also demonstrate distinct genetic heterogeneity. For example, pGBM demonstrate mutation of the PTEN gene and frequent loss of heterozygosity on chromosome 10q (inclusive of the PTEN gene locus), amplification of EGFR, deletions of CDKN2A (p16), while sGBM and their lower grade precursor lesions have frequent mutations of the TP53 gene and the IDH1 gene [3–7]. Recent studies have also looked at genetic alterations in early and late paired secondary samples .
In recent years large scale genome-wide epigenetic studies have been performed with the aim of developing clinically relevant biomarkers for glioblastoma [9–11]. A good example is the epigenetic silencing of the MGMT promoter that has provided an exciting and clinically relevant epigenetic marker in gliomas. The MGMT gene encodes for an O-6-methylguanine methyltransferase that removes alkyl groups from the O-6 position of guanine. Thus loss of its activity greatly impairs a cells ability to tolerate alkylating agents and studies have shown that MGMT-promoter methylation is associated with longer survival of patients treated with alkylating agents such as temozolomide [12, 13]. Recently, the Cancer Genome Atlas (TCGA) research network identified a CpG island methylator phenotype (CIMP) in a subset of human gliomas with distinct clinical and molecular features, including improved survival outcomes for those gliomas demonstrating CIMP . The gain of function mutations within the isocitrate dehydrogenase 1 gene (IDH1) are thought to be largely responsible for the glioma hypermethylator phenotype due to the massively increased production of the 2-hydroxyglutarate oncometabolite and have recently been shown to be sufficient to result in a hypermethylator phenotype in glioma cell lines [14, 15]. At least some individual genes have demonstrated differential methylation frequencies in grade IV pGBM and sGBM samples  and although much progress has been made in assessing genome-wide methylation of pGBM tumors, much less is known about genome-wide methylation in early grade tumors and their subsequent higher grade sGBM manifestations.
Recent technological advances have made it possible to quantitatively assess genome-wide methylation at the individual CpG loci level using the Illumina Infinium BeadChips. The most recent version of this BeadChip (Infinium HumanMethylation450 BeadChip) is able to quantitatively assess the levels of methylation at specific CpG loci throughout the genome, including CpG islands and regions of much lower CpG dinucleotide density. In this report we utilized these comprehensive Infinium HumanMethylation450 BeadChip arrays to define genome-wide methylation in paired samples of early/late astrocytic gliomas and to demonstrate any alterations induced by progression.
Forty DNA samples from 20 astrocytoma/glioma patients were used in this study. These patient samples consisted of; 10 WHO grade II astrocytomas, 15 WHO grade III astrocytomas and 15 WHO grade IV glioblastomas. The 40 DNA samples represent 20 cases of paired early and late lesions from the same patient. The DNA was extracted from tissue samples consisting of a minimum of 80% tumor. The DNA from four non-disease brain samples was used to provide the normal, expected levels of methylation. Ethical guidelines were followed for patient sample collection and all samples have been anonymised. Research was conducted according to the principles expressed in the Declaration of Helsinki. Patients gave written informed consent for analysis of tumor samples. The study was approved by the Institutional Ethics Committees of University of Technology Dresden and University of Birmingham.
The Illumina Infinium HumanMethylation450 array (Illumina, San Diego, CA, USA) was performed on 0.5 μg bisulfite modified patient DNA according to manufacturers’ instructions. Bisulfite modification of DNA and array hybridization was carried out by Cambridge Genomics Services. Raw data was obtained using Genome Studio software from Illumina. The raw data were processed using the lumi R  package to correct for the color bias present due to the use of different dye on the array. To correct this bias, Infinium type I and type II are separated, then both channel are also separated and the color bias is corrected using a within array smooth quantile normalization. After correction the two channels and probe types are combined and a between array quantile normalization is performed. The beta score are then calculated. The raw files have been deposited in NCBI’s Gene Expression Omnibus  and are accessible through GEO Series accession number GSE58298.
Probes demonstrating detection p-values greater than 0.01 in any sample were removed along with probes located on the X and Y chromosomes. To ensure tumor specific hypermethylation, probes showing a beta value ≥0.25 in any of the four normal samples were also removed. Hypermethylation was subsequently determined as a beta value ≥0.5. This was considered relevant if present in >30% tumor samples. Additional filtering was achieved limiting selection to genes for which the hypermethylation criteria were met in ≥3 probes associated to that gene.
The top 2000 most variable loci for each clustering event were determined by selecting the 2000 probes with the greatest standard deviation across all the given samples. Clustering was performed using the Cluster3 program (http://bonsai.hgc.jp/~mdehoon/software/cluster/software.htm#ctv) and visualized using the Java TreeView program (http://jtreeview.sourceforge.net/). Unsupervised hierarchical clustering was performed using the Euclidean based algorithm.
Clone sequencing was used for array validation. 0.5 μg of DNA for each sample was bisulfite modified using the Qiagen EpiTect kit (Qiagen, Heidelberg, Germany) according to manufacturers’ instructions. PCR reactions were performed using FastStart Taq DNA polymerase (Roche, West Sussex, UK) on a semi-nested basis for all genes using the primers listed in Additional file 1. A touchdown PCR program for primary and secondary reactions using gene specific annealing temperatures was performed. Selected PCR products were cloned into the pGEM-T easy vector (Promega, Madison, WI, USA) according to manufacturers’ instructions and cultured overnight at 37°C. Up to 12 colonies were selected for single colony PCR using primer sequences F: 5′- TAATACGACTCACTATAGGG -3′ and R: 5′- ACACTATAGAATACTCAAGC -3′. PCR products were cleaned for sequencing using thermosensitive alkaline phosphatase (Fermentas UK, York, UK) and Exonuclease I (NEB, Ipswich, MA, USA) and then sequenced using cycle sequencing on an ABI 3730 (Applied Biosystems, Carlsbad, CA, USA). Methylation indexes were calculated as a percentage of the number of methylated CpGs out of the total number of CpGs sequenced.
IDH1 and IDH2mutation status
Previously described primers were used to amplify 129 bp and 150 bp fragments of the IDH1 and IDH2 genes . The IDH1 forward primer 5′-CTCCTGATGAGAAGAGGGTTG-3′ and IDH1 reverse primer 5′-TGGAAATTTCTGGGCCATG-3′ were used to sequence codon 132 and the IDH2 forward primer 5′-TGGAACTATCCGGAACATCC-3′ and IDH2 reverse primer 5′-AGTCTGTGGCCTTGTACTGC-3 were used to sequence codon 172 of IDH2. Twenty nanograms of genomic DNA were used as starting material for a 25 μl total volume PCR reaction using Go Taq polymerase. An annealing temperature of 58°C was used for 35 cycles. PCR products were bi-directionally sequenced using cycle sequencing on an ABI 3730x (Applied Biosystems, Carlsbad, CA, USA).
Illumina Infinium HumanMethylation450 BeadChip array data was used for the following 19 TCGA primary glioblastomas: TCGA-06-5416, TCGA-06-0171, TCGA-26-5136, TCGA-06-0190, TCGA-06-5418, TCGA-06-0210, TCGA-26-5135, TCGA-26-5134, TCGA-26-5132, TCGA-12-5295, TCGA-06-5414, TCGA-06-0211, TCGA-26-5133, TCGA-06-5417, TCGA-06-0221, TCGA-26-1442, TCGA-06-6389, TCGA-06-6701, TCGA-15-1444. All array data was downloaded from the TCGA Data Portal (https://tcga-data.nci.nih.gov/tcga/tcgaHome2.jsp). IDH1 and IDH2 mutation status for these tumors was identified using the cBioPortal for Cancer Genomics (http://www.cbioportal.org/public-portal/).
To determine whether aberrant DNA methylation differs between early and late secondary glioma lesions we have used the new Illumina Infinium HumanMethylation450 BeadChip array on 40 astrocytic secondary glioma tumors, consisting of 20 pairs of early and late lesions for individual patients and four normal brain samples. Of the 20 patient paired samples; 5 pairs are WHO grade II astrocytomas progressing to grade III astrocytomas, 5 pairs are WHO grade II astrocytomas progressing to WHO grade IV glioblastomas, and 10 pairs are grade III astrocytomas progressing to grade IV glioblastomas. In order to adjust for potential bias based on the differences in probe design between Illumina Type I/II probes we ran all raw data through a correction pipeline prior to analysis. In addition, these samples had been assessed for IDH1 and IDH2 mutation status, 14 out of 20 (70%) samples demonstrated mutation in the IDH1 R132 codon. No IDH2 mutations were detected (Additional file 2: Table S1).
CIMP is an early event in secondary gliomagenesis that can be retained throughout progression
Identification of hypermethylated loci dependent upon glioma grade
Identification of the hypermethylated loci conserved during tumor grade progression
To try and identify genes important throughout secondary gliomagenesis it was assumed that genes hypermethylated in all glioma grades would be the most relevant. This analysis identified 939 hypermethylated CpG loci across all grades for further analysis. This list represents 232 genes and was, as before, reduced to 218 genes (represented by 914 CpG loci) by selecting genes that were represented in the list by ≥3 CpG loci probes. The gene list and beta values for these probes are provided in Additional file 4: Tables S2 and S3 respectively. Three genes (ALS2CL, GNMT and WNK2) were chosen from the list of 218 genes to confirm array values with regard to methylation. We chose two genes that had not previously been shown to be methylated in GBM (ALS2CL and GNMT) and one gene that has (WNK2)  for this technical validation of array results. Results from clone sequencing confirmed β-values >0.5 are representative of methylation and that very low β-values correspond to no methylation (Additional file 5: Figure S2; Additional file 1). Use of the Ingenuity Pathway Analysis software identified 47.7% (104/218) of genes as falling within five molecular and cellular function groups; cell morphology, cellular movement, cellular development, cellular growth and proliferation, and cellular assembly and organization. Of these 104 genes, 39 have been previously associated with cancer (Additional file 6: Table S4-S5).
Identification of sGBM preferentially methylated targets
Ingenuity Pathway Analysis software assessment of molecular and cellular functions of exclusively methylated genes in either pGBM grade IV glioblastomas or sGBM grade IV glioblastomas
sGBM Ingenuity analysis(w)
No. of Genes(y)
Diseases and disorder
2.52E-04 – 1.05E-02
Molecular and cellular functions
3.53E-06 – 8.01E-03
Molecular and cellular functions
Cellular assembly and organization
1.56E-05 – 7.76E-03
Molecular and cellular functions
1.29E-04 – 1.29E-04
Molecular and cellular functions
cell death and survival
2.52E-04 – 1.02E-02
Molecular and cellular functions
Cellular function and maintenance
2.52E-04 – 1.05E-02
pGBM Ingenuity analysis (w)
No. of Genes (y)
p-value range (z)
Diseases and disorder
7.67E-09 – 2.68E-04
Molecular and cellular functions
7.23E-23 – 1.28E-04
Molecular and cellular functions
4.44E-20 – 7.94E-04
Molecular and cellular functions
1.16E-09 – 8.32E-04
Molecular and cellular functions
4.41E-09 – 6.52E-04
Molecular and cellular functions
Cellular growth and proliferation
2.45E-08 – 7.69E-04
Secondary GBM represents a smaller subset (5%) of GBM tumors which develop from preexisting lower grade tumors (grade II/III), are more often seen in younger patients and patients with sGBM have longer survival times . These tumors demonstrate distinct genetic heterogeneity compared to primary GBM, including a considerably greater mutation rate of the IDH1 gene that has been shown to result in a CpG island methylator phenotype (CIMP). In this report we have used the latest Illumina Infinium HumanMethylation450 BeadChips to assess the genome-wide methylation of 20 secondary glioblastomas and their matching lower grade precursors. Sandoval et al.  recently validated the Illumina Infinium HumanMethylation450 BeadChip array and demonstrated that this latest array consistently and significantly detects CpG methylation changes in the HCT-116 colorectal tumor cell line in comparison with normal colon mucosa or HCT-116 cells with defective DNA methytransferases . While whole-genome bisulfite sequencing is the gold standard for comprehensive mapping of methylation events, it is still expensive and requires a high level of specialization. However, the Illumina Infinium HumanMethylation450 BeadChip offers a powerful technique for better understanding of the DNA methylation changes occurring in human diseases at a reasonable cost. Our study represents the first to utilize the Illumina Infinium HumanMethylation450 BeadChips to evaluate epigenetic changes occurring during glioma progression.
We demonstrated that these samples had the expected high levels of IDH1 mutation and that in the lower grade precursors this nearly uniformly resulted in a CIMP phenotype. We saw one case (P16, early and late lesions) where there was evidence of an IDH1 mutation but no CIMP phenotype. We also saw one case (P19.E) where there was no evidence of IDH1 or IDH2 mutation but was CIMP positive. However, it has previously been suggested that even when negative for the known IDH1 p.R132H mutation, it is possible that other IDH1 mutations could be present in some cases that might therefore potentially affect CIMP status . The early presentation of IDH1 mutation and CIMP that we have seen in our study suggests this is an early and important event in gliomagenesis and that if not acquired at an early stage is not gained during progression as no later stage glioblastoma presented with CIMP where the precursor did not. Although the total number of samples is small the large degree of IDH1 mutation and CIMP argues strongly that this is true. In addition to increased overall survival, IDH1 mutation status has been shown to correlate with genetic features including the presence of MGMT methylation and codeletion of 1p and 19q, as well as inversely correlating with EGFR amplification, chromosome 10 loss and chromosome 7 polysomy [5, 24] and therefore if we had been able to analyze a larger sample set, it would have been interesting to look at the relationship between these factors.
The effects of tumor grade progression on the genome-wide methylation of these paired samples of sGBM tumors and their earlier lower grade lesions could be assessed in the most comprehensive manner to date due to the large amount of data provided by the Illumina Infinium HumanMethylation450 BeadChips. Firstly, as mentioned above samples lacking CIMP in their precursor lesions never gained it via progression, presumably due to the early gain of some other genetic or environmental factor capable of driving gliomagenesis without the subsequent need for hypermethylation. While those samples presenting with CIMP in their precursor lesion, largely in association with IDH1 mutation, split approximately in half to follow two paths after progression. Some samples appeared to fully retain and maintain CIMP in their higher grade lesions whatever level CIMP hypermethylation was observed within the lower grade precursor lesions, presumably due to the importance of this high level of general hypermethylation to the tumors survival. Interestingly, some samples notably reduced their levels of general hypermethylation, some retaining what we defined as CIMP and some losing it. This could potentially be due the initial lower grade lesion demonstrating epigenetic heterogeneity with different cells having differing hypermethylation patterns that together present as CIMP positive. If a subset of these cells contained hypermethylation of a particular tumor suppressor that resulted in a considerable growth advantage then these cells could grow out and progress to be the higher grade lesion. This lesion would still have the evolutionary pressure to maintain the hypermethylation of this specific tumor suppressor but not necessarily the need to maintain a global methylation phenotype, although in general you would expect some degree of maintenance by the IDH1 mutation, it is plausible that due to changing tumor heterogeneity this would be visualized at a lesser extent. Unfortunately we were unable to assess different regions from within the same tumor to investigate this hypothesis. Furthermore, we observed that these differences were not simply due to pairs progressing from grade II to grade III compared to grade III to grade IV or grade II to grade IV. Due to the relatively small size of our cohort we were unable to identify the specific genetic differences that may support this hypothesis as we would assume them to be tumor specific. Nonetheless this is an interesting observation that could possibly affect the effectiveness of therapies based on demethylating agents on these tumors. Naturally, we would assume they would be more effective in samples that at some stage demonstrated CIMP but they may still be effective in samples that do not demonstrate CIMP in the later grades if CIMP was present in the precursor lesion. It is hard to estimate whether a demethylating agent would be more effective on tumors dependent on global hypermethylation or are reliant on the hypermethylation of only a small number of targets. Promisingly, 5-azacitidine has recently been shown to be effective in reducing selected promoter methylation, tumor growth, cell proliferation and inducing differentiation in an in vivo primary xenograft IDH1 mutant glioma .
Further evidence for the loss of some hypermethylation due to tumor grade progression was observed when the levels of hypermethylated loci and genes were assessed simply by the grade of each tumor rather than looking for differences between paired samples. We noticed a trend towards decreasing levels of methylated targets with increasing tumor grade which has previously been documented [11, 20]. This loss of methylation as tumors progress to later grades may indicate changes in tumor heterogeneity resulting in refinement of the most beneficial effects of hypermethylation as proposed above, but could also represent a potential increase in normal contamination as the tumor becomes more invasive and thus the tumor sample more intermingled with normal.
By analyzing grade II, III and IV tumors separately, we were able to identify a list of genes where hypermethylation was retained in all 3 grades, likely representing the most generally important methylated genes within this cohort of sGBM tumors. This identified preferential hypermethylation of several genes associated with cell morphology, cellular movement, cellular development, cellular growth and proliferation, and cellular assembly and organization, with many of these select genes having been previously associated with cancer. Due to the relatively small number of tumors assessed, this analysis would greatly benefit from expansion into a larger cohort that could highlight which genes and pathways are most important to sGBM gliomagenesis and progression.
By comparison of methylation profile of our grade IV lesions with a subset of the publically available methylation profiles of grade IV pGBM provided by the Cancer Genome Atlas (TCGA) network we demonstrated that in general the methylation profiles between these two tumor types differ in a similar manner to their respective genetic alterations. This was further observed when comparing the functions of genes commonly hypermethylated in grade IV sGBMs compared to grade IV pGBMs with sGBMs preferentially hypermethylating genes involved in cell death, survival and maintenance pathways and pGBMs preferentially hypermethylating genes that alter or control gene expression. Interestingly, a small number of the pGBM tumors demonstrated CIMP that was also largely associated with IDH1 mutation, demonstrating a very similar hypermethylation profile to CIMP positive grade IV sGBM. This represented a specific epigenetic overlap between a subset of the pGBM and sGBM tumors. Included in this were two pGBM tumors exhibiting CIMP that lacked mutation in IDH1 or IDH2 that could possibly retain other mutations capable of resulting in CIMP such as could be present in our 19th pair. Overall, this small sGBM/pGBM analysis offers an insight into different tumorigenic processes giving rise to these different types of GBM tumors.
In summary, this data offers an insight into different epigenetic, methylation-related processes that give rise to these different types of GBM tumors and provides interesting rationales for further study of this kind on much larger cohorts. The increased use of genome-wide analysis of methylation using technologies such as the Illumina Infinium HumanMethylation450 BeadChips, that are relatively cheap and can be performed using both archival tissue DNA from FFPE blocks and small amounts of DNA acquired from biopsies, may well increase their usefulness as diagnostic or therapeutic markers. Thus, providing a greater understanding on these tumor specific methylation patterns may prove useful in a number of ways.
VH was sponsored in part by the Department of Neurosurgery, University Hospital Dresden, Germany. TS were sponsored by King Abdulaziz University, Jeddah, Saudi Arabia.
- Tortosa A, Vinolas N, Villa S, Verger E, Gil JM, Brell M, Caral L, Pujol T, Acebes JJ, Ribalta T, Ferrer I, Graus F: Prognostic implication of clinical, radiologic, and patholofic features in patients with anaplastic gliomas. Cancer. 2003, 15: 1063-1071.View ArticleGoogle Scholar
- Kaye AH, Walker DG: Low grade astrocytomas: controversies in management. J Clin Neurosci. 2000, 7: 475-483.View ArticlePubMedGoogle Scholar
- Ohgaki H, Kleihues P: The definition of primary and secondary glioblastoma. Clin Cancer Res. 2013, 19: 764-772.View ArticlePubMedGoogle Scholar
- Guo C, Pirozzi CJ, Lopez GY, Yan H: Isocitrate dehydrogenase mutations in gliomas: mechanisms, biomarkers and therapeutic target. Curr Opin Neurol. 2011, 24: 648-652.View ArticlePubMedPubMed CentralGoogle Scholar
- Parsons DW, Jones S, Zhang X, Lin JC, Leary RJ, Angenendt P, Mankoo P, Carter H, Siu IM, Gallia GL, Olivi A, McLendon R, Rasheed BA, Keir S, Nikolskaya T, Nikolsky Y, Busam DA, Tekleab H, Diaz LA, Hartigan J, Smith DR, Strausberg RL, Marie SK, Shinjo SM, Yan H, Riggins GJ, Bigner DD, Karchin R, Papadopoulos N, Parmigiani G: An integrated genomic analysis of human glioblastoma multiforme. Science. 2008, 321: 1807-1812.View ArticlePubMedPubMed CentralGoogle Scholar
- Yan H, Parsons DW, Jin G, McLendon R, Rasheed BA, Yuan W, Kos I, Batinic-Haberle I, Jones S, Riggins GJ, Friedman H, Friedman A, Reardon D, Herndon J, Kinzler KW, Velculescu VE, Vogelstein B, Bigner DD: IDH1 and IDH2 mutations in gliomas. N Engl J Med. 2009, 360: 765-773.View ArticlePubMedPubMed CentralGoogle Scholar
- Jiao Y, Killela PJ, Reitman ZJ, Rasheed AB, Heaphy CM, de Wilde RF, Rodriguez FJ, Rosemberg S, Oba-Shinjo SM, Nagahashi Marie SK, Bettegowda C, Agrawal N, Lipp E, Pirozzi C, Lopez G, He Y, Friedman H, Friedman AH, Riggins GJ, Holdhoff M, Burger P, McLendon R, Bigner DD, Vogelstein B, Meeker AK, Kinzler KW, Papadopoulos N, Diaz LA, Yan H: Frequent ATRX, CIC, FUBP1 and IDH1 mutations refine the classification of malignant gliomas. Oncotarget. 2012, 3: 709-722.View ArticlePubMedPubMed CentralGoogle Scholar
- Juratli TA, Kirsch M, Robel K, Soucek S, Geiger K, von Kummer R, Schackert G, Krex D: IDH mutations as an early and consistent marker in low-grade astrocytomas WHO grade II and their consecutive secondary high-grade gliomas. J Neurooncol. 2012, 108: 403-410.View ArticlePubMedGoogle Scholar
- Martinez R, Esteller M: The DNA methylome of glioblastoma multiforme. Neurobiol Dis. 2010, 39: 40-46.View ArticlePubMedGoogle Scholar
- Noushmehr H, Weisenberger DJ, Diefes K, Phillips HS, Pujara K, Berman BP, Pan F, Pelloski CE, Sulman EP, Bhat KP, Verhaak RG, Hoadley KA, Hayes DN, Perou CM, Schmidt HK, Ding L, Wilson RK, Van Den Berg D, Shen H, Bengtsson H, Neuvial P, Cope LM, Buckley J, Herman JG, Baylin SB, Laird PW, Aldape K, Cancer Genome Atlas Research Network: Identification of a CpG island methylator phenotype that defines a distinct subgroup of glioma. Cancer Cell. 2010, 17: 510-522.View ArticlePubMedPubMed CentralGoogle Scholar
- Wu X, Rauch TA, Zhong X, Bennett WP, Latif F, Krex D, Pfeifer GP: CpG island hypermethylation in human astrocytomas. Cancer Res. 2010, 70: 2718-2727.View ArticlePubMedPubMed CentralGoogle Scholar
- Esteller M, Garcia-Foncillas J, Andion E, Goodman SN, Hidalgo OF, Vanaclocha V, Baylin SB, Herman JG: Inactivation of the DNA-repair gene MGMT and the clinical response of gliomas to alkylating agents. N Engl J Med. 2000, 343: 1350-1354.View ArticlePubMedGoogle Scholar
- Weller M, Stupp R, Reifenberger G, Brandes AA, van den Bent MJ, Wick W, Hegi ME: MGMT promoter methylation in malignant gliomas: ready for personalized medicine?. Nat Rev Neurol. 2010, 6: 39-51.View ArticlePubMedGoogle Scholar
- Dang L, White DW, Gross S, Bennett BD, Bittinger MA, Driggers EM, Fantin VR, Jang HG, Jin S, Keenan MC, Marks KM, Prins RM, Ward PS, Yen KE, Liau LM, Rabinowitz JD, Cantley LC, Thompson CB, Vander Heiden MG, Su SM: Cancer-associated IDH1 mutations produce 2-hydroxyglutarate. Nature. 2009, 462: 739-744.View ArticlePubMedPubMed CentralGoogle Scholar
- Turcan S, Rohle D, Goenka A, Walsh LA, Fang F, Yilmaz E, Campos C, Fabius AW, Lu C, Ward PS, Thompson CB, Kaufman A, Guryanova O, Levine R, Heguy A, Viale A, Morris LG, Huse JT, Mellinghoff IK, Chan TA: IDH1 mutation is sufficient to establish the glioma hypermethylator phenotype. Nature. 2012, 483: 479-483.View ArticlePubMedPubMed CentralGoogle Scholar
- Hill VK, Underhill-Day N, Krex D, Robel K, Sangan CB, Summersgill HR, Morris M, Gentle D, Chalmers AD, Maher ER, Latif F: Epigenetic inactivation of the RASSF10 candidate tumor suppressor gene is a frequent and an early event in gliomagenesis. Oncogene. 2011, 30: 978-989.View ArticlePubMedGoogle Scholar
- Du P, Kibbe WA, Lin SM: lumi: a pipeline for processing Illumina microarray. Bioinformatics. 2008, 24: 1547-1548.View ArticlePubMedGoogle Scholar
- Edgar R, Domrachev M, Lash AE: Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002, 30: 207-210.View ArticlePubMedPubMed CentralGoogle Scholar
- Hartmann C, Meyer J, Balss J, Capper D, Mueller W, Christians A, Felsberg J, Wolter M, Mawrin C, Wick W, Weller M, Herold-Mende C, Unterberg A, Jeuken JW, Wesseling P, Reifenberger G, von Deimling A: Type and frequency of IDH1 and IDH2 mutations are related to astrocytic and oligodendroglial differ- entiation and age: a study of 1,010 diffuse gliomas. Acta Neuropathol. 2009, 118: 469-474.View ArticlePubMedGoogle Scholar
- Christensen BC, Smith AA, Zheng S, Koestler DC, Houseman EA, Marsit CJ, Wiemels JL, Nelson HH, Karagas MR, Wrensch MR, Kelsey KT, Wiencke JK: DNA methylation, isocitrate dehydrogenase mutation, and survival in glioma. J Natl Cancer Inst. 2011, 103: 143-153.View ArticlePubMedPubMed CentralGoogle Scholar
- Moniz S, Martinho O, Pinto F, Sousa B, Loureiro C, Oliveira MJ, Moita LF, Honavar M, Pinheiro C, Pires M, Lopes JM, Jones C, Costello JF, Paredes J, Reis RM, Jordan P: Loss of WNK2 expression by promoter gene methylation occurs in adult gliomas and triggers Rac1-mediated tumour cell invasiveness. Hum Mol Genet. 2013, 22: 84-95.View ArticlePubMedGoogle Scholar
- Sandoval J, Heyn H, Moran S, Serra-Musach J, Pujana MA, Bibikova M, Esteller M: Validation of a DNA methylation microarray for 450,000 CpG sites in the human genome. Epigenetics. 2011, 6: 692-702.View ArticlePubMedGoogle Scholar
- Gravendeel LA, Kloosterhof NK, Bralten LBC, van Marion R, Dubbink HJ, Dinjens W, Bleeker FE, Hoogenraad CC, Michiels E, Kros JM, van den Bent M, Smitt PA, French PJ: Segregation of Non-p.R132H Mutations in IDH1 in Distinct Molecular Subtypes of Glioma. Hum Mutat. 2010, 31: E1186-E1199.View ArticlePubMedGoogle Scholar
- van den Bent MJ, Dubbink HJ, Marie Y, Brandes AA, Taphoorn MJ, Wesseling P, Frenay M, Tijssen CC, Lacombe D, Idbaih A, van Marion R, Kros JM, Dinjens WN, Gorlia T, Sanson M: IDH1 and IDH2 mutations Are prognostic but not predictive for outcome in anaplastic oligodendroglial tumors: a report of the European organization for research and treatment of cancer brain tumor group. Clin Cancer Res. 2010, 16: 1597-1604.View ArticlePubMedGoogle Scholar
- Borodovsky A, Salmasi V, Turcan S, Fabius AW, Baia GS, Eberhart CG, Weingart JD, Gallia GL, Baylin SB, Chan TA, Riggins GJ: 5-azacytidine reduces methylation, promotes differentiation and induces tumor regression in a patient-derived IDH1 mutant glioma xenograft. Oncotarget. 2013, 4: 1737-1747.View ArticlePubMedPubMed CentralGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2407/14/506/prepub
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