MGMT promoter methylation in gliomas-assessment by pyrosequencing and quantitative methylation-specific PCR
© Håvik et al; licensee BioMed Central Ltd. 2012
Received: 19 September 2011
Accepted: 6 March 2012
Published: 6 March 2012
Methylation of the O6-methylguanine-DNA methyltransferase (MGMT) gene promoter is a favorable prognostic factor in glioblastoma patients. However, reported methylation frequencies vary significantly partly due to lack of consensus in the choice of analytical method.
We examined 35 low- and 99 high-grade gliomas using quantitative methylation specific PCR (qMSP) and pyrosequencing. Gene expression level of MGMT was analyzed by RT-PCR.
When examined by qMSP, 26% of low-grade and 37% of high-grade gliomas were found to be methylated, whereas 97% of low-grade and 55% of high-grade gliomas were found methylated by pyrosequencing. The average MGMT gene expression level was significantly lower in the group of patients with a methylated promoter independent of method used for methylation detection. Primary glioblastoma patients with a methylated MGMT promoter (as evaluated by both methylation detection methods) had approximately 5 months longer median survival compared to patients with an unmethylated promoter (log-rank test; pyrosequencing P = .02, qMSP P = .06). One third of the analyzed samples had conflicting methylation results when comparing the data from the qMSP and pyrosequencing. The overall survival analysis shows that these patients have an intermediate prognosis between the groups with concordant MGMT promoter methylation results when comparing the two methods.
In our opinion, MGMT promoter methylation analysis gives sufficient prognostic information to merit its inclusion in the standard management of patients with high-grade gliomas, and in this study pyrosequencing came across as the better analytical method.
KeywordsGlioma Glioblastoma MGMT Methylation Gene expression Low-grade glioma High-grade gliomas Pyrosequencing qMSP RT-PCR
Gliomas are histologically divided into several subgroups including astrocytomas, oligodendrogliomas, and oligoastrocytomas and are graded from I to IV according to the WHO classification . Prognosis is highly variable depending on histopathology, grade, patient age, and genetic tumor factors such as the presence of a 1p/19q co-deletion, IDH1 and IDH2 mutations, and MGMT promoter methylation [1, 2]. The most common glioma subtype in adults is glioblastoma (GBM) with an annual incidence of 3-4/100 000 . This is also the subgroup with the least favorable prognosis. In 2005, Stupp and coworkers reported a 2.5 months increase in median overall survival for GBM patients when adding concomitant and adjuvant temozolomide (TMZ) to postoperative radiotherapy . It should be noted, however, that clinical trials tend to report higher median overall survival rates than retrospective studies, possibly due to selection bias . Therefore, it is not surprising that a retrospective population-based Norwegian study reported a lower median overall survival for GBM patients (9.9 months) than that of the Stupp study patients (14.6 months and 12.1 months) [3, 4].
About 5% of the DNA methylation induced by TMZ is located at the O6-position of guanine and methylation in this position is considered to be the main contributor to the cytotoxic effect [5–7]. The DNA repair enzyme O-6-methylguanine-DNA methyltransferase (MGMT) removes methyl groups from the O6-position of guanine and the expression of MGMT is therefore thought to inhibit the cytotoxic effect of TMZ [5, 6]. Even though the first studies suggesting that MGMT promoter hypermethylation was an important molecular marker in high-grade gliomas were published almost a decade ago [8–10], the extent of its positive prognostic and predictive value in the different grades of gliomas remains to be determined . Further, though several studies indicate that MGMT promoter methylation is a prognostic marker , there is no clear consensus as to which detection method should be preferred or what constitutes optimal threshold values for scoring samples as methylation positive. As a result, a wide range of reported glioma MGMT methylation frequencies can be seen (Additional file 1: Tables S1 and S2) . We have used two independent quantitative methylation detection methods, quantitative methylation specific polymerase chain reaction (qMSP) and pyrosequencing, to analyze a large series of gliomas. We also analyzed the gene expression level of MGMT in the majority of these samples. To illustrate the variability in methylation frequencies and methylation detection methods, we systemized publications reporting MGMT promoter methylation in a tabular overview (Additional file 1: Tables S1 and S2).
Materials and methods
Patients and samples
Tumor samples from 134 glioma patients (diffuse astrocytoma WHO grade II (n = 10), oligodendroglioma WHO grade II (n = 6), oligoastrocytoma WHO grade II (n = 17), low-grade neuroepithelial tumour not otherwise specified (n = 2), anaplastic astrocytoma WHO grade III (n = 4), anaplastic oligodendroglioma WHO grade III (n = 6), anaplastic oligoastrocytoma WHO grade III (n = 3), glioblastoma WHO grade IV (n = 86)) and four meningioma patients who underwent surgery at the Department of Neurosurgery (Oslo University Hospital) between January 2005 and January 2009 were included in this study. The meningioma samples served as MGMT promoter methylation negative controls . Histological diagnoses were reviewed by an expert neuropathologist (author D.S.). Patients alive were included following written, informed consent whereas permission to include deceased patients was obtained from The National Health Authorities. The study was approved by the Regional Ethics Committee (S-06046) as well as the Institutional Study Board.
DNA isolation and bisulfite conversion
DNA was extracted from fresh frozen tissue using a standard phenol-chloroform procedure and its quantity and quality was measured using a NanoDrop ND-1000 Spectrophotometer (Thermo Fisher Scientific). Unmethylated cytosine residues were converted to uracil by bisulfite treatment of 1.3 μg DNA using the EpiTect Bisulfite Kit (Qiagen) according to the manufacturers' protocol. After conversion, DNA was eluted in buffer (Qiagen) to a final concentration of 30 ng/μl.
Quantitative methylation specific polymerase chain reaction
Primers and probes used for quantitative methylation-specific polymerase chain reaction (qMSP)
MGMT qMSP a
MGMT_1 qMSP b
ALU qMSP c
Samples with a Ct-value above 35 were censored (resulting in a quantity of 0). The percentage of methylated reference (PMR) was calculated for each sample from the median quantity value from the triplicates by dividing the MGMT/ALU quantity ratio in the target by the MGMT/ALU quantity ratio in the methylated control, and multiplying by 100. A threshold value for scoring methylation positive samples was defined based on the qMSP result of four meningiomas, which all had PMR values of zero in both qMSP assays. Only samples with a PMR value above zero in both assays were scored as methylation positive. Representative PCR products from both reactions were sequenced in order to verify the fragment identity.
Five CpG sites in the MGMT promoter were analyzed by pyrosequencing using the PyroMark MD System (Qiagen). Bisulfite treated DNA was amplified in a PCR reaction using primers from the PyroMark Q96 CpG MGMT kit (part number 972032, Qiagen). In addition to the samples, each run included a non-template control (water), an unmethylated control (bisulfite treated normal leukocyte DNA), and a methylated control (bisulfite converted in vitro methylated human DNA). The amplification was carried out in 96-well plates and the PCR reaction and cycling conditions were according to the kit manual. Subsequent sample preparation and pyrosequencing was performed as described in the PyroMark MD Sample Prep Guidelines. In brief, the double stranded PCR products were denatured in NaOH and washed before a sequencing primer was annealed. The pyrosequencing reaction starts from the 3'-end of the sequencing primer. Nucleotides (A, T, C, and G) were dispensed into each sample well, one at a time. Whenever a base complementary to the base in the PCR product is added, it is incorporated into the growing DNA strand, resulting in an enzymatic cascade and production of light. The light intensity is measured at each dispensation and presented graphically in a pyrogram. The dispensation order was generated automatically by the Pyromark CpG Software 1.0.11 and modified according to recommendations by the provider (two dispensations added). The dispensation order was GTCGC TTAGTCTGTTCGT ATCAGTCGTCA (extra dispensations in bold). The extra C dispensation in the beginning of the sequence served as a bisulfite control. The additional T dispensation was included to remove background noise in the following CpG site, thus the peak was excluded as a reference peak in data analysis. The minimal signal value was set to 100 as recommended in the Pyromark CpG Software user manual. Apart from these changes, the results were analyzed using default software settings.
The pyrosequencing threshold was determined from the mean methylation value in the five analyzed CpG sites and the mean standard deviation (X + 2SD) in the four meningiomas. Glioma samples were scored as methylation positive by pyrosequencing if all five CpG sites had methylation values higher than the resulting threshold of 2.68%.
MGMT expression analysis by real-time reverse transcriptase PCR
Total RNA was extracted from 81 of the 134 glioma samples. The tissue samples were stored frozen in RNAlater and total RNA was extracted using a standard TRIzol protocol. RNA quantity and integrity were examined using a NanoDrop ND-1000 Spectrophotometer (Thermo Fisher Scientific) and an Agilent BioAnalyzer 2100 (Agilent Technologies), respectively. Total RNA was reverse transcribed using cDNA by random hexamer primers and the High Capacity cDNA Reverse Transcription Kit (Applied Biosystems, Life Technologies) according to the manufacturers' protocol. The real-time PCR was carried out in triplicates in 384 well plates using the 7900HT Fast-Real time PCR machine (Applied Biosystems, Life Technologies). The total reaction volume was 20 μl and contained 20 ng cDNA, 1× TaqMan Universal PCR Mastermix (Applied Biosystems, Life Technologies), and 1× TaqMan Gene Expression assay (Applied Biosystems, Life Technologies; see below). The PCR was run at 50°C for 2 min, 95°C for 10 min, and 40 cycles of 95°C for 15 s and 60°C for 60 s. Each sample was analyzed with two different TaqMan Gene Expression Assays for MGMT (Hs01037698_m1 and Hs00172470_m1; part number 4331182, Applied Biosystems, Life Technologies) as well as two endogenous controls (ACTB; part number 4352935E, and GUSB part number 4333767 F, Applied Biosystems, Life Technologies). The median result in each triplicate was used for data analysis.
Each plate included several non-template controls and a standard curve generated by a serial dilution of total cDNA reverse transcribed from Universal Human Reference RNA (Stratagene, Agilent Technologies). Ct-values were determined automatically with the default settings in the software SDS 2.2.2 (Applied Biosystems, Life Technologies) and converted to quantity using the standard curves. Samples with a Ct-value above 35 were censored. The quantity was normalized by dividing the quantity of MGMT expression by the average quantity of ACTB and GUSB.
Statistical analyses were performed in SPSS 16.0. (SPSS Inc.). We used McNemar's chi-squared test for comparison of the two methylation detection methods and Kruskal-Wallis' rank sum test to determine potential differences in methylation level between high- and low-grade gliomas. Overall survival analysis was performed using the Kaplan-Meier procedure and included all primary glioblastoma patients who were treated with standard radiotherapy (2 Gy × 30) and concomitant, and in some cases adjuvant, TMZ (n = 58). Patients' date of death was collected from the National Population Register. Survival was calculated from date of first surgery. Log-rank test was based on 24 months overall survival. T-tests for independent samples were performed to compare average gene expression of MGMT in samples with versus samples without a methylated MGMT promoter. All P-values < 0.05 were considered statistically significant.
MGMT promoter methylation status
MGMT methylation frequencies and methylation level in methylated glioma samples
Median and IQR
Median and IQR
calculated from PMR
mean CpG methylation
WHO grade II
WHO grade II
WHO grade II
Low-grade neuroepithelial tumours
(not otherwise specified)
WHO grade III
WHO grade III
WHO grade III
WHO grade IV
Included in survival analysis a
All glioma samples
MGMT promoter methylation status and survival of primary glioblastoma patients
Patient characteristics and results of survival analysis for primary glioblastoma patients when stratified by MGMT methylation status
MGMT methylation status
2-years overall survival (%)
MGMT gene expression in samples with and without MGMT promoter methylation
Reported frequencies of MGMT promoter methylation in subgroups of gliomas vary considerably, as shown in Additional file 1: Tables S1 and S2. Various methylation detection methods and different primer sets and threshold values have been used. In the present study, we report MGMT promoter methylation frequencies in gliomas determined by qMSP (low-grade gliomas 26% and high-grade gliomas 37%) as well as by pyrosequencing (low-grade gliomas 97% and high-grade gliomas 55%). It should be noted that the CpG sites interrogated in the qMSP and pyrosequencing assays are only partially overlapping (Additional file 1: Figure S1), and caution should therefore be made when directly comparing the results. The MGMT promoter is typically reported methylated in 30-60% of glioblastomas  and in 30-90% of low-grade gliomas [12, 18]. Compared to these reports, our qMSP methylation frequencies are in the lower range whereas the pyrosequencing methylation frequencies are in the upper range.
The vast majority of previous studies of MGMT promoter methylation in gliomas have used gel based methylation-specific PCR (MSP), which is a qualitative and time-consuming method. The manual methylation scoring based on interpretation of gel band intensities will vary in stringency level between labs, which, in addition to the use of different primers, may in part explain some of the observed difference in results observed from MSP based studies. This is exemplified by two works using the same primer sets but reporting very different methylation frequencies of 23% and 44% in newly diagnosed glioblastoma samples [19, 20]. In contrast to MSP, qMSP is a quantitative, standardized, high-throughput method which is easy to perform and the results are easy to evaluate. Thus, the method is more suitable for use in routine testing. To detect methylation by amplification of methylated alleles in MSP and qMSP, all CpG sites on the same DNA strand covered by the primers have to be methylated. Compared with traditional MSP, qMSP is even more conservative as it includes a methylation-specific probe and thereby typically covers more CpG sites that all have to be methylated. This may lower the sensitivity of the assay, but more importantly, increases the specificity, as underscored by Parella et al. who analyzed MGMT promoter methylation using both MSP and qMSP assays. In glioma samples the two methods showed good concordance, whereas the results from normal brain samples demonstrated that MSP may hold a higher risk of false positive results . In the present study, we used two overlapping qMSP assays and only scored samples as methylated if they had a positive PMR value in both assays. The results from the two assays were generally overlapping. Of the 134 analyzed gliomas samples only 16 of them had conflicting methylation status from the qMSP assays. The PMR-values seemed to be somewhat higher in one of the qMSP assays. This is probably a result of the inclusion of different CpG sites in the two assays (Additional file 1: Figure S1). The conservative nature of the qMSP assay may explain why our qMSP methylation frequencies are in the lower range of previously reported MSP results [11, 12, 18]. One of the primer/probe sets used in the present study corresponds to the assay used by Parrella and coworkers [13, 21]. The second qMSP assay is modified after a recent publication by Rivera et al.  who found MGMT promoter methylation in 24% of GBM patients, which is similar to the methylation frequency found by us.
As expected, the MGMT promoter methylation frequencies as measured by pyrosequencing were found to be in the upper range compared to previous MSP based findings. In contrast to MSP and qMSP, the pyrosequencing technique is able to detect low levels of methylation because methylation in each CpG site is measured independently of the methylation status in surrounding CpG sites. Indeed, our methylation frequency in high-grade gliomas (55%) is highly concordant with the GBM methylation frequency recently determined in a pyrosequencing work by Dunn et al. (53%) .
Choice of threshold values for scoring samples as methylation positive or not may also explain some of the differences observed in reported methylation frequencies. Ideally, the threshold value should be determined using a test series of a large number of normal tissue samples as well as tumor samples. The threshold value can thereafter be chosen to give a high sensitivity (with the risk of producing false positives) or a high specificity (with the risk of failing to identify all positive cases as such). We have used high-quality DNA extracted from fresh frozen tissue for all methylation analyses. In some neurooncology centers sampling of fresh frozen tissue is not a standard procedure, hence formalin-fixed paraffin embedded (FFPE) tissue is a frequently used DNA source. All MGMT promoter fragments amplified in the present study are short (qMSPs 83-119 bp and pyrosequencing ~100 bp) and will most likely be amplifiable also in DNA extracted from FFPE tissue. Lacking access to normal brain tissue, we used four benign meningioma samples to set the threshold values for scoring samples as methylation positive. The threshold values were determined so that all the meningiomas were scored as methylation negative. These benign tumors showed little (pyrosequencing, mean methylation range 1.39-1.55%) to no (qMSP, PMR 0% in both assays) MGMT promoter methylation, resulting in low threshold values, thus supporting the assumption that meningiomas are suitable alternatives to normal tissue samples for threshold determination. However, this should be confirmed by validation studies in independent sample series. Brain tissue from surgery in epileptic patients is an alternative to the meningioma tissue for establishing cutoff values.
In accordance with previous reports, our results show that the overall survival for patients with a methylated MGMT promoter is better than for patients with an unmethylated promoter [10, 20, 23, 24]. The observed difference at 24 months was significant based on the pyrosequencing results but only borderline significant based on the qMSP results. The log-rank test results indicate that both methylation detection methods are able to identify primary glioblastoma patients with a somewhat better prognosis. However, the survival curve differences are more distinct when using the pyrosequencing based methylation status, implying that this is the better method to use for estimating the prognosis. These results are in line with the observation that the patients with non-concordant methylation findings (unmethylated by qMSP and methylated by pyrosequencing) showed a trend towards better survival than patients with unmethylated MGMT promoter by both methods (Figure 1C). The last mentioned finding should, however, be validated in an independent sample set. Nevertheless, based on the observations done here, it could be argued that a primary glioblastoma should be regarded MGMT promoter methylated if the pyrosequencing result is positive. Because all glioblastoma patients receive TMZ as part of the Stupp regimen, the methylation status of the MGMT promoter does not change the therapeutic regime today. Nonetheless, it is a prognostic marker  of clinical interest and may be relevant for evaluation of pseudoprogression . It is also interesting that, independent of the method used, the methylation level (amount of methylation) observed in methylation positive low-grade gliomas is low compared to the level observed in methylation positive high-grade gliomas. This has not been reported previously and may in part explain the large difference in methylation frequency as assessed by qMSP and pyrosequencing in low-grade gliomas. The clinical relevance of this finding remains to be determined and the data should be validated in an independent data set. Nevertheless, the overall survival analysis, which includes GBM with a low methylation level, suggests that pyrosequencing is the better method for predicting prognosis in primary GBM patients. This may also suggest an advantage of a low methylation level in low-grade gliomas. There are not many studies reporting MGMT promoter methylation frequencies in large series of low-grade gliomas. However, two studies analyzing 68 and 185 low-grade gliomas report methylation frequencies of 93% and 81%, respectively, using the same MSP primers in a nested two-stage approach [18, 25]. These frequencies match our frequency (97%) detected by the sensitive pyrosequencing approach. However, other studies with smaller sample series report lower frequencies in the range 40-50% [26–29] when analyzed by conventional MSP.
We found a significant association between MGMT promoter methylation and reduced gene expression, regardless of methylation detection method and gene expression assay used. Based on this, one could suggest that the gene expression level might be analyzed instead of promoter methylation. However, the gene expression level in methylated and unmethylated samples shows considerable overlap (Figure 2) which may be due to lack of a linear relationship between the region analyzed for promoter methylation and gene expression. The most commonly analyzed region in the MGMT gene promoter covers 9 of the totally 97 CpG sites in the promoter, and it has been suggested that methylation in some specific CpG sites correlates better with reduction in gene expression level than analysis of the common MSP region (Additional file 1: Figure S1) . On the other hand, factors such as contamination with normal cells and loss of one MGMT allele may also influence the detected gene expression level. For a subset of the samples with gene expression data and methylation status, we had access to karyotypic and/or CGH data [16, 17] (author H-S. S. Dahlback, unpublished data). Figure 3 illustrates that the MGMT gene expression seemed to be affected by loss of the 10q26 chromosome band. Interestingly, but not unexpectedly, the loss of this chromosome band seemed to have a larger impact on gene expression in samples with a low methylation level (mean methylation by pyrosequencing < 20%) compared to highly methylated samples. However, these observations are based on results from small groups and should be tested in a larger dataset.
It is important to keep in mind that it is the MGMT protein that counteracts the effect of TMZ by removing methyl adducts at the O6-position of guanine. A recent study using human tumor cell lines derived from glioblastomas and other tumors concluded that the response to TMZ is better predicted by MGMT protein expression than by promoter methylation status . However, although cancer cell lines are useful models for the in vivo situation, findings should be validated in patient sample series, and so far immunohistochemical analyses of the MGMT protein level in human tumor samples have been inconclusive when correlated with patient outcome .
Taken together, our findings corroborate earlier conclusions that MGMT promoter methylation is of prognostic value for primary glioblastoma patients [9, 10, 20, 22, 33], and this status is of interest for the patients, their relatives, and treating physicians. Therefore, in our opinion determination of MGMT promoter methylation status should be incorporated into standard management programs for patients with GBM. There is currently no "gold standard" for which technique to use for assessing clinically meaningful MGMT promoter methylation. In this study pyrosequencing came across as a slightly better method than qMSP when looking at the prognostic value of MGMT promoter methylation status in primary glioblastomas. Both qMSP and pyrosequencing are easy to perform and high-throughput methods; the choice of method therefore becomes one based on utilitarian considerations.
This study is supported by grants from the Norwegian Cancer Society and has received additional funding from Oslo University Hospital and the University of Oslo. We thank Ingrid Louise Norman for technical assistance in the laboratory.
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