Abstract P17: Epigenomic fingerprinting of limited primary immune cells using automated CUT&RUN

Abstract

Abstract Chromatin structure drives gene expression programs during immune cell development and in cancer, making it central to the advancement of precision medicine. Indeed, the study of chromatin regulation has provided valuable insight on effector cell differentiation and function, anti-tumor immune responses, and therapeutic resistance. Epigenomic features – such as histone post-translational modifications (PTMs) and chromatin-associated proteins – mark distinct genomic compartments (e.g., promoters, enhancers) and regulate chromatin function/gene expression. Mapping the genomic distribution of these may uncover new biomarkers or drug targets and provides a rich context for exploring immunology. Despite widespread interest, integration of epigenomics in large-scale immunotherapy and/or drug research has been hampered by the poor sensitivity, high background, and low throughput of traditional chromatin mapping technologies, most notably ChIP-seq. Instead, efforts to characterize chromatin dynamics have focused on DNA methylation (bisulfite-seq) or chromatin accessibility (ATAC-seq). However, these assays provide an incomplete view of the chromatin landscape, limiting their ability to define cell differentiation pathways or derive mechanistic insight into disease etiology. Here, we present autoCUT&RUN, a high-throughput assay for rapid, ultra-sensitive profiling of epigenomic features from FACS-isolated primary cells or tissues. This workflow generates reliable profiles from ~10,000 cells per reaction, and is supported by a rigorous optimization strategy, high-quality antibodies, and quantitative spike-in controls. As part of a multi-site collaboration with the Immunological Genome Consortium, we used our autoCUT&RUN platform to build a comprehensive epigenomic database of primary mouse immune cells - composed of >1,500 epigenomic profiles from >100 different FACS-isolated immune cell types. These studies set the stage to leverage high-throughput epigenomics in immunotherapy and precision medicine applications. Citation Format: Ellen N. Weinzapfel, Keith E. Maier, Matthew R. Marunde, Vishnu U. Sunitha Kumary, Carolina P. Lin Windham, Danielle N Maryanski, Liz Albertorio-Saez, Dughan J. Ahimovic, Michael J. Bale, Juliana J. Lee, Bryan J. Venters, Michael-Christopher Keogh, Immunological Genome Consortium. Epigenomic fingerprinting of limited primary immune cells using automated CUT&RUN [abstract]. In: Proceedings of the Blood Cancer Discovery Symposium; 2024 Mar 4-6; Boston, MA. Philadelphia (PA): AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P17.