Pyrosequencing for MGMT promoter methylation analysis validated for use in clinical practice

Pyrosequencing is reported as the ideal method for MGMT methylation analysis, and is validated for use in clinical practice.

Methylation of the O6-methylguanine- DNA-methyltranferase (MGMT) promoter region is associated with several cancer types, including colorectal cancer, lung cancer, lymphoma and glioblastoma. MGMT promoter methylation is a powerful predictive biomarker of positive response to temozolomide, a chemotherapy in the standard care protocol for glioblastoma patients, and is also used to stratify or select patients for clinical trials (1, 2). Further, the European Association for Neuro-Oncology (EANO) guidelines recommend MGMT testing as a standard practice to help clinicians select appropriate treatment for elderly patients (3). To support more routine clinical testing of MGMT, Quillien et al. conducted a prospective mulitcenter trial which validates a technique for MGMT promoter methylation analysis in routine clinical practice (4).

The study by Quillien et al. aimed to determine the most appropriate method for MGMT promoter methylation analysis in clinics, based on high repeatability and reproducibility. Another goal was to validate cut-off points used to classify samples as ‘methylated’ vs. ‘unmethylated’, in effort to overcome certain challenges in determining these thresholds. The ideal cut-off would be the lowest MGMT methylation able to suppress MGMT expression, determined by comparing levels of MGMT methylation and expression in cell lines. However this biological cut-off does not take into account the complexity of glioblastoma samples that may contain a variable number of non-neoplastic cells whose “unmethylated” MGMT DNA is extracted along with DNA of tumor cells, and could potentially lead to underestimation of the level of MGMT methylation in the tumor cells (6). Macrodissection of samples ensures a high percentage of tumor cells, and can help to overcome this. However, accurate assessment of an area rich in tumor cells is challenging (7, 8), and in glioblastoma samples, non-tumor and tumor cells are often closely intermingled. As a compromise, the authors aimed to establish on outcome-based cutoff which is validated in a prospective study using multiple cohorts of patients.

Using pyrosequencing (PSQ) and a semi-quantitative methylation-specific PCR (sqMS-PCR) method to analyze both frozen and formalin-fixed paraffin-embedded (FFPE) samples, Quillien et al. interrogated the MGMT status of 139 glioblastoma patients who had received standard first line treatment. Eight local centers performed the analysis, including external quality controls. The study reported a strong correlation between results from FFPE and frozen samples, as well as identical sample classification using PSQ and sqMS-PCR (98% and 91%, respectively) when cut-offs of 12% and 13% were used.

A QIAGEN pyrosequencing kit was used to perform the pyrosequencing analysis, which enables quantification of the level of MGMT gene methylation. The authors previously demonstrated that pyrosequencing was the best technique among five that were tested for MGMT promoter methylation analysis (methylation-specific polymerase chain reaction (MS-PCR), MethyLight, pyrosequencing, methylation-sensitive high-resolution melting and immunohistochemistry) (5). Later in the validation study, they extended their analysis to a prospective study, using only PSQ and sqMS-PCR methods. They confirm that pyrosequencing is the ideal method, based on robustness, strong inter-laboratory reproducibility, increased sensitivity and threshold agreement across independent studies. The authors conclude that MGMT methylation status can be reliably determined in local laboratories, and that pyrosequencing using QIAGEN’s pyrosequencing kit is the optimal method for analysis.

The prospective study by Quillien et al. validates a cut-off of 8% to predict poor response to TMZ treatment, and indicates that “methylated” patients may significantly benefit from new second-line treatments versus “unmethylated” patients. The authors noted that higher thresholds performed better when analyzing FFPE samples using PSQ, and propose 12% as a second cutoff value, which showed excellent concordance between FFPE and frozen samples. Patients above 12% could be considered as “methylated”, while patients slightly below this (9-12%) may be considered to have moderate/low methylation.

QIAGEN offers multiple solutions for oncology research and diagnostics, including methylation analysis. Find out more here about QIAGEN’S pyrosequencing technology and platform portfolio, including the PyroMark solutions. QIAGEN’s Personalized Healthcare and Oncology solutions offer many benefits, including convenient biomarker testing, reliable, efficient and cost effective workflows, and secure systems with experienced services and support. Find out more about QIAGEN’s technologies for various applications, including pyrosequencing.



  1. 1. Wick, W., et al. (2014) MGMT testing—the challenges for biomarker-based glioma treatment. Nat Rev Neurol. 10:372–385. Link
  2. 2. Weller, M., et al. (2010) MGMT promoter methylation in malignant gliomas: ready for personalized medicine? Nat Rev Neurol. 6:39–51. Link
  3. 3. Weller, M., et al. (2014) EANO guideline for the diagnosis and treatment of anaplastic gliomas and glioblastoma. Lancet Oncol. 15:e395–403. Link
  4. 4. Quillien, V., et al. (2016) Validation of the high-performance of pyrosequencing for clinical MGMT testing on a cohort of glioblastoma patients from a prospective dedicated multicentric trial. Oncotarget 7(38): 61916–61929. Link
  5. 5. Quillien, V., et al. (2012) Comparative assessment of 5 methods (methylation-specific polymerase chain reaction, MethyLight, pyrosequencing, methylation-sensitive high-resolution melting, and immunohistochemistry) to analyze O6-methylguanine- DNA-methyltranferase in a series of 100 glioblastoma patients. Cancer 118: 4201–4211. Link
  6. 6. Sasai, K., et al. (2008) Careful exclusion of non-neoplastic brain components is required for an appropriate evaluation of O6-methylguanine-DNA methyltransferase status in glioma: relationship between immunohistochemistry and methylation analysis. Am J Surg Pathol. 32:1220–1227. Link
  7. 7. Viray, H., et al. (2013) A prospective,multi-institutional diagnostic trial to determine pathologist accuracy in estimation of percentage of malignant cells. Arch Pathol Lab Med. 2013; 137:1545–1549. Link
  8. 8. Smits, A.J., et al. (2014) The estimation of tumor cell percentage for molecular testing by pathologists is not accurate. Mod Pathol. 27:168–174. Link

Kathryn Collinet, PhD, is a Technical and Marketing Writer for Personalized Healthcare and Oncology at QIAGEN. She trained as a molecular biologist at the University of Barcelona and the Institute for Research in Biomedicine, where she studied DNA and protein modifications and their influence on chromatin conformation and gene expression. Since 2011 Kathryn has been working in marketing communications for the scientific information and molecular diagnostics industries. Kathryn has a passion for delivering knowledge and insights about molecular and clinical technologies, and their power to impact research and healthcare.

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