Evidence map›Paper›PMID 21249131›Full record

ArticlePloS one2011

Comprehensive analysis of MGMT promoter methylation: correlation with MGMT expression and clinical response in GBM.

Nameeta Shah, Biaoyang Lin, Zita Sibenaller, Timothy Ryken, Hwahyung Lee, Jae-Geun Yoon, Steven Rostad, Greg Foltz

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
63citing papers in PubMed, 3 pooled it
6.7field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

63 citing papers in PubMed, 3 syntheses or guidelines pooled it, 113 citations in OpenAlex.

  1. Pooled it
  2. Accuracy of Radiomics in PredictingRadiology. Artificial intelligence · 2024
    Pooled it
  3. Guideline
  4. Cancer genomics & proteomics
    Trial
  5. Article
  6. Article
  7. Biodegradable nanofibrous scaffolds enhance standard of care for glioblastoma via localized targeted therapy.Journal of controlled release : official journal of the Controlled Release Society · 2025
    Article
  8. Article
  9. Review
  10. Article
  11. Analysis of DNA Methylation in Gliomas: Assessment of Preanalytical Variables.Laboratory investigation; a journal of technical methods and pathology · 2024
    Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Prognostic and Predictive Biomarkers in Gliomas.International journal of molecular sciences · 2021
    Review
  19. Article
  20. Article

3 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors at 2 institutions in 1 country.

Nameeta ShahThe Ben and Catherine Ivy Center for Advanced Brain Tumor Treatment, Swedish Neuroscience Institute, Seattle, Washington, United States of America.
Biaoyang Lin
Zita Sibenaller
Timothy Ryken
Hwahyung Lee
Jae-Geun Yoon
Steven Rostad
Greg Foltz
Swedish Medical Center · USUniversity of Iowa · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

O⁶-methylguanine DNA-methyltransferase (MGMT) promoter methylation has been identified as a potential prognostic marker for glioblastoma patients. The relationship between the exact site of promoter methylation and its effect on gene silencing, and the patient's subsequent response to therapy, is still being defined. The aim of this study was to comprehensively characterize cytosine-guanine (CpG) dinucleotide methylation across the entire MGMT promoter and to correlate individual CpG site methylation patterns to mRNA expression, protein expression, and progression-free survival. To best identify the specific MGMT promoter region most predictive of gene silencing and response to therapy, we determined the methylation status of all 97 CpG sites in the MGMT promoter in tumor samples from 70 GBM patients using quantitative bisulfite sequencing. We next identified the CpG site specific and regional methylation patterns most predictive of gene silencing and improved progression-free survival. Using this data, we propose a new classification scheme utilizing methylation data from across the entire promoter and show that an analysis based on this approach, which we call 3R classification, is predictive of progression-free survival (HR  = 5.23, 95% CI [2.089-13.097], p<0.0001). To adapt this approach to the clinical setting, we used a methylation-specific multiplex ligation-dependent probe amplification (MS-MLPA) test based on the 3R classification and show that this test is both feasible in the clinical setting and predictive of progression free survival (HR  = 3.076, 95% CI [1.301-7.27], p = 0.007). We discuss the potential advantages of a test based on this promoter-wide analysis and compare it to the commonly used methylation-specific PCR test. Further prospective validation of these two methods in a large independent patient cohort will be needed to confirm the added value of promoter wide analysis of MGMT methylation in the clinical setting.

Indexed as

Base SequenceCpG IslandsDisease-Free SurvivalDNA MethylationDNA Modification MethylasesDNA Repair EnzymesGene SilencingGlioblastomaHumansPrognosisPromoter Regions, GeneticTreatment OutcomeTumor Suppressor ProteinsDNA Modification MethylasesDNA Repair EnzymesMGMT protein, humanTumor Suppressor Proteins

Identifiers

PMID21249131
PMCPMC3017549
OpenAlexW2094354684

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.