Non-invasive determination of the O6-methylguanine-DNA-methyltransferase (MGMT) promoter methylation status in glioblastoma (GBM) using magnetic resonance imaging (MRI).

2018 ◽  
Vol 36 (15_suppl) ◽  
pp. 2051-2051 ◽  
Author(s):  
Saima Rathore ◽  
Spyridon Bakas ◽  
MacLean P Nasrallah ◽  
Stephen Joseph Bagley ◽  
Hamed Akbari ◽  
...  
Keyword(s):  
Dna Methyltransferase ◽  
Methylation Status ◽  
Mgmt Promoter Methylation ◽  
Resonance Imaging ◽  
Methylguanine Dna Methyltransferase ◽  
Non Invasive ◽  
Mgmt Promoter ◽  
Magnetic Resonance Imaging Mri ◽  
Mgmt Promoter Methylation Status

scholarly journals TMOD-40. IN VIVO EVALUATION OF O6-METHYLGUANINE-DNA-METHYLTRANSFERASE (MGMT) PROMOTER METHYLATION STATUS FOR DE NOVO GLIOBLASTOMA PATIENTS USING DEEP LEARNING FEATURES

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi271-vi272
Author(s):  
Saima Rathore ◽  
MacLean Nasrallah ◽  
Hamed Akbari ◽  
Gaurav Shukla ◽  
Stephen Bagley ◽  
...  
Keyword(s):  
Machine Learning ◽  
Transfer Learning ◽  
Dna Methyltransferase ◽  
Methylation Status ◽  
Mgmt Promoter Methylation ◽  
Methylguanine Dna Methyltransferase ◽  
Non Invasive ◽  
Mgmt Promoter ◽  
Deep Learning Features ◽  
Mgmt Promoter Methylation Status

Abstract BACKGROUND High expression of O6-methylguanine-DNA methyltransferase (MGMT) in glioblastoma is associated with resistance to temozolomide, as tumor cells lacking MGMT activity are significantly more sensitive to the cytotoxic effects of temozolomide. The MGMT promoter methylation status (MGMTpms) is typically determined as MGMT-methylated or MGMT-unmethylated. Some single-center studies have reported results ranging from 70–95% detection rates using MRI. We aim to further validate these findings using a multi-institutional data set. We hypothesize that transfer learning based features when integrated via machine learning may lead to non-invasive determination of MGMTpms. METHODS A total of 270 patients were included across the 3 institutions (Hospital of the University of Pennsylvania (HUP), Jefferson University Hospital (JUH); the TCIA). JUH and TCIA datasets comprised conventional modalities (T1,T2,T2-FLAIR,T1-Gd), whereas HUP dataset had additional modalities (DSC,DTI) as well. We used transfer learning and adapted a convolutional neural network (CNN) model pre-trained on 1.2 million 3-channel images of the ImageNet to extract deep learning features from the given images. A support vector machine multivariately integrated these features towards a non-invasive marker of MGMTpms. RESULTS The cross-validated accuracy of our MGMT marker in classifying the mutation status in individual patients was 86.95%, 81.56%, and 82.43%, respectively, in HUP, JUH, and TCIA. Our marker revealed MGMT-methylated tumors with lower neovascularization and cell density, when compared with MGMT-unmethylated tumors. MGMT-unmethylated tumors were found to be more lateralized to the right hemisphere, when compared with MGMT-methylated tumors. CONCLUSION Our findings suggest that transfer learning features when integrated via machine learning allow robust prediction of MGMTpms on mpMRI acquired within multiple institutions. The proposed non-invasive MGMT marker may contribute to (i) MGMTpms determination for patients with inadequate tissue/inoperable tumors, (ii) stratification of patients into clinical trials, (iii) patient selection for targeted therapy, and (iv) personalized treatment planning.

scholarly journals NCOG-29. O6-METHYLGUANINE DNA METHYLTRANSFERASE (MGMT) PROMOTER METHYLATION STATUS AND THE INCIDENCE OF TEMOZOLOMIDE-INDUCED HEMATOLOGIC TOXICITY: AN ASSOCIATION STUDY

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii135-ii135
Author(s):  
Alyssa Strohbusch ◽  
Heather Pound ◽  
Patrick Regis ◽  
Robert Cavaliere
Keyword(s):  
Promoter Methylation ◽  
Dna Methyltransferase ◽  
Statistical Difference ◽  
Methylation Status ◽  
Mgmt Promoter Methylation ◽  
Hematologic Toxicity ◽  
Methylguanine Dna Methyltransferase ◽  
Mgmt Promoter ◽  
Grade 3 ◽  
Mgmt Promoter Methylation Status

Abstract BACKGROUND Despite the growing body of evidence demonstrating an increased clinical benefit of alkylating agents in glioblastoma patients with O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation, little is known regarding the effect of MGMT status on toxicity. The purpose of this investigation is to provide insight into the potential association between MGMT promoter methylation and the development of Grade 3/4 hematologic toxicities in patients receiving temozolomide. METHODS A total of 63 patients with documented glioblastoma or anaplastic astrocytoma diagnoses were evaluated retrospectively. A chi-square test of independence was utilized to evaluate the incidence of hematologic toxicities and patient overall survival was determined by univariate analysis estimated through use of Kaplan-Meier curves. Relative frequencies of treatment discontinuation secondary to myelosuppression were also compared. RESULTS At the time of study completion, 71.4% of patients with MGMT promoter hypermethylation had survived compared with 50% of patients with hypomethylation (HR 0.86; 95% CI 0.71 to 1.05; P>0.05). The percentage of patients who experienced Grade 3/4 hematologic toxicities during concurrent treatment was 20% and 5.1% within the hypermethylated and hypomethylated groups, respectively, and 26.7% and 17.9% throughout standard therapy. While a statistical difference was not found between the cumulative incidences of Grade 3/4 hematologic toxicity events throughout both phases of treatment, a statistical difference was noted in the incidence of Grade 4 occurrences with ten events occurring in the hypermethylated group and zero in those with hypomethylated promoter regions (P< 0.01). Furthermore, use of temozolomide in hypermethylated patients resulted in fewer completed cycles of standard therapy and higher rates of treatment delays and drug discontinuation. CONCLUSIONS This study showed marked differences in the frequency of temozolomide-induced hematologic toxicities and treatment discontinuation based on tumor MGMT promoter methylation status. Further research is warranted in larger patient populations to both validate and determine the clinical significance of these findings.

scholarly journals NIMG-38. NON-INVASIVE PREDICTION OF MGMT PROMOTER METHYLATION USING COMBINED FET PET/MRI RADIOMICS

2020 ◽  
Vol 22 (Supplement_2) ◽  
pp. ii156-ii156
Author(s):  
Philipp Lohmann ◽  
Anna-Katharina Meissner ◽  
Jan-Michael Werner ◽  
Gabriele Stoffels ◽  
Martin Kocher ◽  
...  
Keyword(s):  
Promoter Methylation ◽  
Methylation Status ◽  
Mgmt Promoter Methylation ◽  
Test Dataset ◽  
Fet Pet ◽  
Promoter Methylation Status ◽  
Non Invasive ◽  
Mgmt Promoter ◽  
Amino Acid Pet ◽  
Mgmt Promoter Methylation Status

Abstract BACKGROUND Recently, the Response Assessment in Neuro-Oncology (RANO) Working Group emphasized the additional diagnostic value of amino acid PET in addition to MRI. However, the number of studies using amino acid PET/MRI radiomics is still low. We investigated the potential of combined O-(2-[18F]fluoroethyl)-L-tyrosine (FET) PET/MRI radiomics for the non-invasive prediction of the O6-methylguanine-DNA methyl-transferase (MGMT) promoter methylation status in glioma patients. METHODS Seventy-one patients with newly diagnosed glioma (predominantly WHO grade III and IV glioma, 82%) underwent a hybrid FET PET/MRI scan. Forty-six patients (65%) had a methylated MGMT promoter. The tumor and tumor subregions were manually segmented on conventional MRI. In total, 199 standardized features were obtained from FET PET, contrast-enhanced T1-weighted, T2-weighted, and fluid attenuated inversion recovery (FLAIR) MRI. After feature extraction and data normalization, patients were randomly assigned to a training and a test dataset for final model evaluation in a ratio of 70/30, with a balanced distribution of the MGMT promoter methylation status. Feature selection was performed by recursive feature elimination using random forest regressors. For the final model generation, the number of features was limited to seven to avoid data overfitting. Different algorithms for model generation were compared, and the model performance in the training data was assessed by 5-fold cross-validation. Finally, the best performing models were applied to the test dataset to evaluate the robustness of the models. RESULTS In the test dataset, the best radiomics signatures obtained from MRI or FET PET alone achieved diagnostic accuracies for the prediction of the MGMT promoter methylation of 64% and 70%, respectively. In contrast, the highest diagnostic accuracy of 83% was obtained by combining FET PET and MRI features. CONCLUSION Combined FET PET/MRI radiomics allows the non-invasive prediction of the MGMT promoter methylation status in patients with gliomas, providing more diagnostic information than either modality alone.

scholarly journals Recycling drug screen repurposes hydroxyurea as a sensitizer of glioblastomas to temozolomide targeting de novo DNA synthesis, irrespective of molecular subtype

2017 ◽  
Vol 20 (5) ◽  
pp. 642-654 ◽  
Author(s):  
Jian Teng ◽  
Seyedali Hejazi ◽  
Lotte Hiddingh ◽  
Litia Carvalho ◽  
Mark C de Gooijer ◽  
...  
Keyword(s):  
Promoter Methylation ◽  
Dna Methyltransferase ◽  
Methylation Status ◽  
Primary Cultures ◽  
Mgmt Promoter Methylation ◽  
In Vivo Models ◽  
Promoter Methylation Status ◽  
Mgmt Promoter ◽  
Mgmt Promoter Methylation Status

Abstract Background Glioblastoma (GBM) is the most common and most aggressive primary malignant brain tumor. Standard-of-care treatment involves maximal surgical resection of the tumor followed by radiation and chemotherapy (temozolomide [TMZ]). The 5-year survival rate of patients with GBM is <10%, a colossal failure that has been partially attributed to intrinsic and/or acquired resistance to TMZ through O6-methylguanine DNA methyltransferase (MGMT) promoter methylation status in the tumor. Methods A drug screening aimed at evaluating the potential recycling and repurposing of known drugs was conducted in TMZ-resistant GBM cell lines and primary cultures of newly diagnosed GBM with different MGMT promoter methylation status, phenotypic/genotypic background and subtype, and validated with sphere formation, cell migration assays, and quantitative invasive orthotopic in vivo models. Results We identified hydroxyurea (HU) to synergize with TMZ in GBM cells in culture and in vivo, irrespective of MGMT promoter methylation status, subtype, and/or stemness. HU acts specifically on the S-phase of the cell cycle by inhibiting the M2 unit of enzyme ribonucleotide reductase. Knockdown of this enzyme using RNA interference and other known chemical inhibitors exerted a similar effect to HU in combination with TMZ both in culture and in vivo. Conclusions We demonstrate preclinical efficacy of repurposing hydroxyurea in combination with TMZ for adjuvant GBM therapy. This combination benefit is of direct clinical interest given the extensive use of TMZ and the associated problems with TMZ-related resistance and treatment failure.

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