BioProject

Single cell RNA-sequencing revealed extensive transcriptional cell state diversity in cancer, often observed independently from genetic heterogeneity, raising the central question of how malignant cell states are encoded epigenetically. More...

Single cell RNA-sequencing revealed extensive transcriptional cell state diversity in cancer, often observed independently from genetic heterogeneity, raising the central question of how malignant cell states are encoded epigenetically. To address this, we performed multi-omics single-cell profiling – integrating DNA methylation, transcriptome, and genotyping 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 measure cell state heritability and transition dynamics based on high resolution lineage trees directly in human samples. We demonstrated heritability of malignant cell states, with key differences in hierarchal vs. plastic cell state architectures in IDH-mutant glioma vs. IDH-wildtype glioblastoma, respectively. This work provides a framework anchoring transcriptional cancer cell states in their epigenetic encoding, inheritance and transition dynamics. Overall design: We profiled CD45- enriched, viable cells from GBM (n = 7) and IDH-MUT (n = 7) primary samples with multi-modality single-cell sequencing of scDNAme (by reduced representation bisulfite sequencing [RRBS]) and scRNAseq (Smart-seq2). *** Raw data access can be requested through the Data Use Oversight System (DUOS) Dataset Catalog with dataset ID DUOS-000133 as well as the European Genome phenome Archive (EGA) with dataset ID EGAS00001005472. *** Less...