ArticleBMC medicine2024
Radiogenomic profiling of global DNA methylation associated with molecular phenotypes and immune features in glioma.
Article in BMC medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- MGMT promoter methylation across glioma subtypes: biological relevance, treatment response, and survival outcomes.Molecular biology reports · 2026Review
- A functionally guided fusion Vision Transformer for predicting IDH status in gliomas: a multicenter study with external validation and incomplete multimodal evaluation.Radiologie (Heidelberg, Germany) · 2026Article
- Radiogenomic landscape of the hallmarks of cancer.Biomarker research · 2026Review
- Supervoxel-based multimodal MRI biomarkers reveal tumor heterogeneity in high-grade glioma for prognostic stratification and therapy response prediction.NPJ precision oncology · 2026Article
- Review
- Progress in the study of molecular markers in the prognosis assessment and recurrence patterns of glioblastoma.Cancer biology & therapy · 2025Review
- Radiogenomics: A Machine Learning Augmentation to MRI-Based Glioma Profiling.Asian journal of neurosurgery · 2025Article
- Development and validation of a delta ultrasomics model for predicting treatment response to neoadjuvant chemotherapy in breast cancer.Translational cancer research · 2025Article
- A Narrative Review of Theranostics in Neuro-Oncology: Advancing Brain Tumor Diagnosis and Treatment Through Nuclear Medicine and Artificial Intelligence.International journal of molecular sciences · 2025Review
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Authors and funding
14 authors.
Funding
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Abstract
backgroundThe radiogenomic analysis has provided valuable imaging biomarkers with biological insights for gliomas. The radiogenomic markers for molecular profile such as DNA methylation remain to be uncovered to assist the molecular diagnosis and tumor treatment.
methodsWe apply the machine learning approaches to identify the magnetic resonance imaging (MRI) features that are associated with molecular profiles in 146 patients with gliomas, and the fitting models for each molecular feature (MoRad) are developed and validated. To provide radiological annotations for the molecular profiles, we devise two novel approaches called radiomic oncology (RO) and radiomic set enrichment analysis (RSEA).
resultsThe generated MoRad models perform well for profiling each molecular feature with radiomic features, including mutational, methylation, transcriptional, and protein profiles. Among them, the MoRad models have a remarkable performance in quantitatively mapping global DNA methylation. With RO and RSEA approaches, we find that global DNA methylation could be reflected by the heterogeneity in volumetric and textural features of enhanced regions in T2-weighted MRI. Finally, we demonstrate the associations of global DNA methylation with clinicopathological, molecular, and immunological features, including histological grade, mutations of IDH and ATRX, MGMT methylation, multiple methylation-high subtypes, tumor-infiltrating lymphocytes, and long-term survival outcomes.
conclusionsGlobal DNA methylation is highly associated with radiological profiles in glioma. Radiogenomic global methylation is an imaging-based quantitative molecular biomarker that is associated with specific consensus molecular subtypes and immune features.
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