Mutations in IDH1 and IDH2 (encoding isocitrate dehydrogenase 1 and 2) drive the development of gliomas and other human malignancies. Mutant IDH1 induces epigenetic changes that promote tumorigenesis, but the scale and reversibility of these changes are unknown. Here, using human astrocyte and glioma tumorsphere systems, we generate a large-scale atlas of mutant-IDH1-induced epigenomic reprogramming. We characterize the reversibility of the alterations in DNA methylation, the histone landscape, and transcriptional reprogramming that occur following IDH1 mutation. We discover genome-wide coordinate changes in the localization and intensity of multiple histone marks and chromatin states. Mutant IDH1 establishes a CD24 population with a proliferative advantage and stem-like transcriptional features. Strikingly, prolonged exposure to mutant IDH1 results in irreversible genomic and epigenetic alterations. Together, these observations provide unprecedented high-resolution molecular portraits of mutant-IDH1-dependent epigenomic reprogramming. These findings have substantial implications for understanding of mutant IDH function and for optimizing therapeutic approaches to targeting IDH-mutant tumors.
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http://dx.doi.org/10.1038/s41588-017-0001-z | DOI Listing |
Nat Commun
January 2025
Department of Medical Oncology, Laboratory of Tumor Immunology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
Isocitrate dehydrogenase 1/2 mutant (IDHmt) astrocytoma is considered a T cell-deprived tumor, yet little is known regarding the phenotypes underlying T cell exclusion. Using bulk, single nucleus and spatial RNA and protein profiling, we demonstrate that a distinct spatial organization underlies T cell confinement to the perivascular space (T cell cuff) in IDHmt astrocytoma. T cell cuffs are uniquely characterized by a high abundance of gemistocytic tumor cells (GTC) in the surrounding stroma.
View Article and Find Full Text PDFLife Metab
April 2024
State Key Laboratory of Holistic Integrative Management of Gastrointestinal Cancers, Department of Pathology, Xijing Hospital and School of Basic Medicine, Fourth Military Medical University, Xi'an, Shaanxi 710032, China.
Isocitrate dehydrogenase (IDH) mutations frequently occur in lower-grade gliomas and secondary glioblastomas. Mutant IDHs exhibit a gain-of-function activity, leading to the production of D-2-hydroxyglutarate (D-2HG) by reducing α-ketoglutarate (α-KG), a central player in metabolism and epigenetic modifications. However, the role of α-KG homeostasis in IDH-mutated gliomagenesis remains elusive.
View Article and Find Full Text PDFActa Neuropathol Commun
January 2025
Department of Neuro-Oncology, Columbia University Irving Medical Center, 710 W. 168th Street, New York, NY, 10032, USA.
Glioblastoma (GBM) classification involves a combination of histological and molecular signatures including IDH1/2 mutation, TERT promoter mutation, and EGFR amplification. Non-canonical mutations such as BRAF, found in 1-2% of GBMs, activate the MEK-ERK signaling pathway. This mutation can be targeted by small molecule inhibitors, offering therapeutic potential for GBM.
View Article and Find Full Text PDFCurr Probl Cancer
January 2025
Department of Molecular Oncology, King Faisal Specialist Hospital and Research Centre, Riyadh 11211 Saudi Arabia; Department of Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh 11211 Saudi Arabia.
Programmed cell death protein 1 (PDCD1) and cluster of differentiation 274 (CD274) expression is implicated in escaping tumors from immune surveillance. Immune checkpoint inhibitors show promise in cancer therapy, yet their efficacy in glioblastomas, particularly with IDH1 mutations, remains unclear. This study analyzed two independent NGS datasets (n = 577 and n = 153) from TCGA to investigate the expression of PDCD1 and CD274 in glioblastomas and their relationship with IDH1 mutations.
View Article and Find Full Text PDFBioengineering (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.
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