1. Epigenetic encoding, heritability and plasticity of glioma transcriptional cell states.
- Author
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Chaligne R, Gaiti F, Silverbush D, Schiffman JS, Weisman HR, Kluegel L, Gritsch S, Deochand SD, Gonzalez Castro LN, Richman AR, Klughammer J, Biancalani T, Muus C, Sheridan C, Alonso A, Izzo F, Park J, Rozenblatt-Rosen O, Regev A, Suvà ML, and Landau DA
- Subjects
- Cell Line, Tumor, CpG Islands genetics, DNA Copy Number Variations genetics, DNA Methylation genetics, Humans, Isocitrate Dehydrogenase genetics, Phylogeny, Polycomb Repressive Complex 2 metabolism, Promoter Regions, Genetic genetics, Single-Cell Analysis, Transcriptome genetics, Brain Neoplasms genetics, Brain Neoplasms pathology, Cell Plasticity genetics, Epigenesis, Genetic, Glioma genetics, Glioma pathology, Inheritance Patterns genetics, Transcription, Genetic
- Abstract
Single-cell RNA sequencing has revealed extensive transcriptional cell state diversity in cancer, often observed independently of genetic heterogeneity, raising the central question of how malignant cell states are encoded epigenetically. To address this, here we performed multiomics single-cell profiling-integrating DNA methylation, transcriptome and genotype within the same cells-of diffuse gliomas, tumors characterized by defined transcriptional cell state diversity. Direct comparison of the epigenetic profiles of distinct cell states revealed key switches for state transitions recapitulating neurodevelopmental trajectories and highlighted dysregulated epigenetic mechanisms underlying gliomagenesis. We further developed a quantitative framework to directly measure cell state heritability and transition dynamics based on high-resolution lineage trees in human samples. We demonstrated heritability of malignant cell states, with key differences in hierarchal and plastic cell state architectures in IDH-mutant glioma versus IDH-wild-type glioblastoma, respectively. This work provides a framework anchoring transcriptional cancer cell states in their epigenetic encoding, inheritance and transition dynamics., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)
- Published
- 2021
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