EPCO-48. DECIPHERING THE EPIGENETIC LANDSCAPE OF GLIOBLASTOMA THROUGH MULTIOMIC SINGLE-CELL AND SPATIAL PROFILING

Abstract Glioblastoma has a complex regulatory landscape that drives its cellular heterogeneity, plasticity, and resistance to therapy—features not explained by genetics alone. Chromatin profiling is essential for uncovering the epigenetic mechanisms underlying these behaviors and for identifying potential vulnerabilities that could be targeted therapeutically. Combinations of histone marks govern the activity of their associated DNA, including functional genomic elements such as enhancers or promoters. Single-cell technologies have only recently been adapted to the study of epigenetic cell states and significant technical challenges have limited their widespread adoption, especially in complex tissues. Here, we employ our recently optimized method for performing simultaneous single-cell epigenetic and transcriptomic analyses in multiple frozen glioblastoma (GBM) samples. Our objective was to implement our recently optimized single cell multi-omic sequencing method (“mscCUT&TAG”) and integrate with additional single cell modalities to evaluate epigenetic heterogeneity in primary glioblastoma samples. Glioblastoma (IDH WT, MGMT unmethylated) samples were collected from primary surgical resection in two patients. We applied our previously developed multi-omic single cell cleavage-under-target and tagmentation (“mscCUT&TAG”), 10X single-cell RNA-seq, 10X Multiome (RNA+ATAC-seq) and whole transcriptome Spatial Enhanced Resolution Omics-sequencing (Stereo-seq) to these samples. We comprehensively characterized 72,000 cells at single-cell resolution by integrating joint chromatin accessibility, transcriptional profiles, and five histone modification chromatin states associated with active (H3K27ac, H3K4me3), poised (H3K4me1) and repressive marks (H3K27me3, H3K9me3), We then combined this data with whole transcriptome Stereo-seq of these tumors, and generated a spatially resolved blueprint of epigenomic regulation in GBM. We identified specific tumor cell populations, cell-type specific coordinated epigenetic and transcriptional changes, and defined functional regulatory elements.We performed a comprehensive analysis of epigenetic heterogeneity in GBM at single-cell and spatially resolved resolution. We anticipate that further extension of this work will provide a greater understanding of fundamental biology and therapeutic avenues in GBM.