ArticleJournal of neuro-oncology2021
Low MGMT digital expression is associated with a better outcome of IDH1 wildtype glioblastomas treated with temozolomide.
Article in Journal of neuro-oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
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Who cites it
14 citing papers in PubMed, 26 citations in OpenAlex.
- Quantitative DNA melting analysis with hybridization probes (qDMA-HP) as a novel approach to assess MGMT promoter methylation in malignant glioma.Journal of neuro-oncology · 2026Article
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- Diffuse gliomas: insights into clinical and histopathological features and survival rates from two centers in a middle-income country.Frontiers in oncology · 2025Article
- OncoProExp: An interactive shiny web application for comprehensive cancer proteomics and phosphoproteomics analysis.Computational and structural biotechnology journal · 2025Article
- WD repeat domain 76 predicts poor prognosis in lower grade glioma and provides an original target for immunotherapy.European journal of medical research · 2024Article
- Glioblastoma with high O6-methyl-guanine DNA methyltransferase expression are more immunologically active than tumors with lowFrontiers in immunology · 2024Article
- Article
- High frequency of WNT-activated medulloblastomas withFrontiers in oncology · 2023Article
- Digital expression profile of immune checkpoint genes in medulloblastomas identifies CD24 and CD276 as putative immunotherapy targets.Frontiers in immunology · 2023Article
- Prognostic significance of TERT promoter mutations in adult-type diffuse gliomas.Brain tumor pathology · 2022Review
- Cancer immune profiling unveils biomarkers, immunological pathways, and cell type score associated with glioblastoma patients' survival.Therapeutic advances in medical oncology · 2022Article
- A 4-Gene Signature Associated With Recurrence in Low- and Intermediate-Risk Endometrial Cancer.Frontiers in oncology · 2021Article
- Favorable prognostic impact ofNeuro-oncology advancesArticle
- Unsupervised machine learning models reveal predictive clinical markers of glioblastoma patient survival using white blood cell counts prior to initiating chemoradiation.Neuro-oncology advancesArticle
Corrections and comments
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Authors and funding
10 authors at 1 institution in 2 countries.
Funding
Abstract
introductionGlioblastoma (GBM) is the deadliest primary brain tumor. The standard treatment consists of surgery, radiotherapy, and temozolomide (TMZ). TMZ response is heterogeneous, and MGMT promoter (MGMTp) methylation has been the major predictive biomarker. We aimed to describe the clinical and molecular data of GBMs treated with TMZ, compare MGMT methylation with MGMT expression, and further associate with patient's outcome.
methodsWe evaluate 112 FFPE adult GBM cases. IDH1 and ATRX expression was analyzed by immunohistochemistry, hotspot TERT promoter (TERTp) mutations were evaluated by Sanger or pyrosequencing, and MGMTp methylation was assessed by pyrosequencing and MGMT mRNA expression using the nCounter® Vantage 3D™ DNA damage and repair panel.
resultsOf the 112 GBMs, 96 were IDH1
conclusionsMGMT mRNA levels evaluated by digital expression were associated with the outcome of TMZ-treated GBM patients. The combination of MGMT methylation and mRNA expression may provide a more accurate prediction of TMZ response in GBM patients.
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