AIMC Topic: DNA Modification Methylases

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Fused deep learning paradigm for the prediction of o6-methylguanine-DNA methyltransferase genotype in glioblastoma patients: A neuro-oncological investigation.

Computers in biology and medicine Jan 4, 2023
BACKGROUND: The O6-methylguanine-DNA methyltransferase (MGMT) is a deoxyribonucleic acid (DNA) repairing enzyme that has been established as an essential clinical brain tumor biomarker for Glioblastoma Multiforme (GBM). Knowing the status of MGMT met...
Magnetic Resonance Imaging DNA Methylation Glioblastoma DNA DNA Modification Methylases Methyltransferases Humans Biomarkers Brain Neoplasms Deep Learning
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Predicting glioblastoma molecular subtypes and prognosis with a multimodal model integrating convolutional neural network, radiomics, and semantics.

Journal of neurosurgery Dec 2, 2022
OBJECTIVE: The aim of this study was to build a convolutional neural network (CNN)-based prediction model of glioblastoma (GBM) molecular subtype diagnosis and prognosis with multimodal features.
Glioblastoma Mutation DNA Modification Methylases DNA Repair Enzymes Tumor Suppressor Proteins Semantics Radiomics Brain Neoplasms Male Middle Aged Deep Learning Magnetic Resonance Imaging Humans Neural Networks, Computer Prognosis Isocitrate Dehydrogenase Female X-linked Nuclear Protein Aged Adult
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The role of deep learning-based survival model in improving survival prediction of patients with glioblastoma.

Cancer medicine Aug 28, 2021
This retrospective study has been conducted to validate the performance of deep learning-based survival models in glioblastoma (GBM) patients alongside the Cox proportional hazards model (CoxPH) and the random survival forest (RSF). Furthermore, the ...
Humans Retrospective Studies Female Aged Adult Tumor Suppressor Proteins Proportional Hazards Models Chemoradiotherapy Radiotherapy Isocitrate Dehydrogenase Karnofsky Performance Status Glioblastoma Brain Neoplasms Male Bayes Theorem Middle Aged Sex Factors Deep Learning Survival Analysis Age Factors DNA Modification Methylases Predictive Value of Tests DNA Repair Enzymes
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MRI-Based Deep-Learning Method for Determining Glioma Promoter Methylation Status.

AJNR. American journal of neuroradiology Mar 4, 2021
BACKGROUND AND PURPOSE: () promoter methylation confers an improved prognosis and treatment response in gliomas. We developed a deep learning network for determining promoter methylation status using T2 weighted Images (T2WI) only.
Sensitivity and Specificity Brain Neoplasms Male Middle Aged Deep Learning Glioma Humans Neural Networks, Computer Reproducibility of Results Aged Adult Promoter Regions, Genetic Magnetic Resonance Imaging DNA Methylation Area Under Curve DNA Modification Methylases DNA Repair Enzymes Tumor Suppressor Proteins
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Machine learning-based radiomic, clinical and semantic feature analysis for predicting overall survival and MGMT promoter methylation status in patients with glioblastoma.

Magnetic resonance imaging Sep 25, 2020
INTRODUCTION: Survival varies in patients with glioblastoma due to intratumoral heterogeneity and radiomics/imaging biomarkers have potential to demonstrate heterogeneity. The objective was to combine radiomic, semantic and clinical features to impro...
Promoter Regions, Genetic Brain Neoplasms Male Middle Aged Image Processing, Computer-Assisted Magnetic Resonance Imaging DNA Methylation Glioblastoma Survival Analysis Humans DNA Modification Methylases Machine Learning DNA Repair Enzymes Retrospective Studies Tumor Suppressor Proteins Female Semantics Aged Adult
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Automatic Prediction of MGMT Status in Glioblastoma via Deep Learning-Based MR Image Analysis.

BioMed research international Sep 23, 2020
Methylation of the O-methylguanine methyltransferase (MGMT) gene promoter is correlated with the effectiveness of the current standard of care in glioblastoma patients. In this study, a deep learning pipeline is designed for automatic prediction of M...
Humans Brain Brain Neoplasms Deep Learning ROC Curve Magnetic Resonance Imaging DNA Methylation Glioblastoma Image Interpretation, Computer-Assisted DNA Modification Methylases DNA Repair Enzymes Tumor Suppressor Proteins Promoter Regions, Genetic Imaging Genomics
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Applications of radiomics and machine learning for radiotherapy of malignant brain tumors.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] May 11, 2020
BACKGROUND: Magnetic resonance imaging (MRI) and amino acid positron-emission tomography (PET) of the brain contain a vast amount of structural and functional information that can be analyzed by machine learning algorithms and radiomics for the use o...
Neuroimaging Diagnosis, Differential Radiosurgery Deep Learning Promoter Regions, Genetic Neoplasm Proteins Image Processing, Computer-Assisted Isocitrate Dehydrogenase Glioblastoma Computational Biology Imaging Genomics Radiation Oncology Glioma Neoplasm Grading Magnetic Resonance Imaging Progression-Free Survival Neoplasm Recurrence, Local DNA Methylation Humans Positron-Emission Tomography Sensitivity and Specificity Radiotherapy Planning, Computer-Assisted Brain Neoplasms DNA Modification Methylases DNA Repair Enzymes Tumor Suppressor Proteins
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Novel approaches for glioblastoma treatment: Focus on tumor heterogeneity, treatment resistance, and computational tools.

Cancer reports (Hoboken, N.J.) Nov 11, 2019
BACKGROUND: Glioblastoma (GBM) is a highly aggressive primary brain tumor. Currently, the suggested line of action is the surgical resection followed by radiotherapy and treatment with the adjuvant temozolomide, a DNA alkylating agent. However, the a...
Tumor Suppressor Proteins Antineoplastic Combined Chemotherapy Protocols Glioblastoma Mutation Tumor Microenvironment Genetic Heterogeneity DNA Modification Methylases Brain Neoplasms Chemoradiotherapy, Adjuvant DNA Mutational Analysis Immune Checkpoint Inhibitors Humans Clonal Evolution DNA Repair Enzymes Computational Biology Machine Learning Drug Resistance, Neoplasm Cancer Vaccines Brain Microtubules Models, Genetic Tumor Suppressor Protein p53 Precision Medicine Prognosis
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Deep-Learning Convolutional Neural Networks Accurately Classify Genetic Mutations in Gliomas.

AJNR. American journal of neuroradiology May 10, 2018
BACKGROUND AND PURPOSE: The World Health Organization has recently placed new emphasis on the integration of genetic information for gliomas. While tissue sampling remains the criterion standard, noninvasive imaging techniques may provide complimenta...
Isocitrate Dehydrogenase Glioma Mutation DNA Modification Methylases DNA Repair Enzymes Adult Humans Tumor Suppressor Proteins Brain Neoplasms Retrospective Studies Promoter Regions, Genetic Male Female Middle Aged Deep Learning
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Multi-label Inductive Matrix Completion for Joint MGMT and IDH1 Status Prediction for Glioma Patients.

Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention Sep 4, 2017
MGMT promoter methylation and IDH1 mutation in high-grade gliomas (HGG) have proven to be the two important molecular indicators associated with better prognosis. Traditionally, the statuses of MGMT and IDH1 are obtained via surgical biopsy, which is...
Aged Young Adult Adult Sensitivity and Specificity Middle Aged Tumor Suppressor Proteins Humans Brain Neoplasms Connectome Glioma Algorithms Isocitrate Dehydrogenase DNA Methylation Prognosis Male Mutation Female DNA Modification Methylases Reproducibility of Results DNA Repair Enzymes
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