Background: Genetic and epigenetic profiling of glioblastomas has provided a comprehensive list of altered cancer genes of which only O(6)-methylguanine-methyltransferase (MGMT) methylation is used thus far as a predictive marker in a clinical setting. We investigated the prognostic significance of genetic and epigenetic alterations in glioblastoma patients.
Methods: We screened 98 human glioblastoma samples for genetic and epigenetic alterations in 10 genes and chromosomal loci by PCR and multiplex ligation-dependent probe amplification (MLPA). We tested the association between these genetic and epigenetic alterations and glioblastoma patient survival. Subsequently, we developed a 2-gene survival predictor.
Results: Multivariate analyses revealed that mutations in isocitrate dehydrogenase 1 (IDH1), promoter methylation of MGMT, irradiation dosage, and Karnofsky Performance Status (KFS) were independent prognostic factors. A 2-gene predictor for glioblastoma survival was generated. Based on the genetic and epigenetic status of IDH1 and MGMT, glioblastoma patients were stratified into 3 clinically different genotypes: glioblastoma patients with IDH1mt/MGMTmet had the longest survival, followed by patients with IDH1mt/MGMTunmet or IDH1wt/MGMTmet, and patients with IDH1wt/MGMTunmet had the shortest survival. This 2-gene predictor was an independent prognostic factor and performed significantly better in predicting survival than either IDH1 mutations or MGMT methylation alone. The predictor was validated in 3 external datasets.
Discussion: The combination of IDH1 mutations and MGMT methylation outperforms either IDH1 mutations or MGMT methylation alone in predicting survival of glioblastoma patients. This information will help to increase our understanding of glioblastoma biology, and it may be helpful for baseline comparisons in future clinical trials.
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http://dx.doi.org/10.1093/neuonc/nou005 | DOI Listing |
Bioengineering (Basel)
December 2024
Department of Pathology, University of Yamanashi, Yamanashi 409-3898, Japan.
The latest World Health Organization (WHO) classification of central nervous system tumors (WHO2021/5th) has incorporated molecular information into the diagnosis of each brain tumor type including diffuse glioma. Therefore, an artificial intelligence (AI) framework for learning histological patterns and predicting important genetic events would be useful for future studies and applications. Using the concept of multiple-instance learning, we developed an AI framework named GLioma Image-level and Slide-level gene Predictor (GLISP) to predict nine genetic abnormalities in hematoxylin and eosin sections: , , mutations, promoter mutations, homozygous deletion (CHD), amplification (amp), 7 gain/10 loss (7+/10-), 1p/19q co-deletion, and promoter methylation.
View Article and Find Full Text PDFAJNR Am J Neuroradiol
January 2025
From the Department of Neuroradiology (G.B., N.H., F.D.v.D., A.B., Z.K.), University Hospital Zürich, Zürich, Switzerland.
Background And Purpose: Whether differences in the O-methylguanine-DNA methyltransferase () promoter methylation status of glioblastoma (GBM) are reflected in MRI markers remains largely unknown. In this work, we analyze the ADC in the perienhancing infiltration zone of GBM according to the corresponding status by using a novel distance-resolved 3D evaluation.
Materials And Methods: One hundred one patients with wild-type GBM were retrospectively analyzed.
Mol Biol Rep
January 2025
Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, 342005, India.
Background: Differential DNA methylation in the promoter region of tumour suppressor genes leads to gene function silencing.
Materials And Methods: In this study, we aimed to evaluate the salivary promoter methylation of EDNRB, MGMT and TIMP3 genes in H&NC patients (n = 100), premalignant lesions patients (n = 25) and healthy controls (n = 50). Blood and saliva samples were collected from all three groups and 20 concomitant tumour tissues were collected from the H&NC patients.
Strahlenther Onkol
January 2025
Department of Radiation Oncology, University Hospital of Muenster, Albert-Schweitzer-Campus 1, Building A1, 48149, Muenster, Germany.
Purpose: While glioblastoma is the most common malignant brain tumor in adults, extracerebral manifestations are very rare in this highly aggressive disease with poor prognosis.
Methods: We conducted a systematic literature review in the PubMed database and complemented the data by inclusion of a case treated in our clinic. In this context, we report on a 60-year-old woman with a right frontal glioblastoma, IDH wildtype, MGMT methylated.
Neuro Oncol
January 2025
Department of Neurology, University Hospital and University of Zurich, Switzerland.
Background: Diffuse hemispheric glioma, histone 3 (H3) G34-mutant, has been newly defined in the 2021 WHO classification of central nervous system tumors. Here we sought to define the prognostic roles of clinical, neuroimaging, pathological, and molecular features of these tumors.
Methods: We retrospectively assembled a cohort of 114 patients (median age 22 years) with diffuse hemispheric glioma, H3 G34-mutant, CNS WHO grade 4 and profiled the imaging, histological and molecular landscape of their tumors.
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