Ellen N Weinzapfel, Keith E. Maier, M. Marunde, V. U. 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
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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.\n 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]. 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引用次数: 0
摘要
染色质结构驱动着免疫细胞发育和癌症中的基因表达程序,使其成为精准医学发展的核心。事实上,染色质调控研究为效应细胞分化和功能、抗肿瘤免疫反应和治疗耐药性提供了宝贵的见解。表观基因组特征--如组蛋白翻译后修饰(PTM)和染色质相关蛋白--标志着不同的基因组区隔(如启动子、增强子),并调控染色质功能/基因表达。绘制这些物质的基因组分布图可能会发现新的生物标记物或药物靶点,并为探索免疫学提供丰富的背景。尽管表观基因组学受到广泛关注,但由于传统染色质图谱绘制技术(尤其是 ChIP-seq)的灵敏度低、背景高、通量低,表观基因组学在大规模免疫疗法和/或药物研究中的整合一直受到阻碍。相反,研究染色质动态特征的工作主要集中在 DNA 甲基化(亚硫酸氢盐-质谱)或染色质可及性(ATAC-质谱)上。然而,这些检测方法提供的染色质景观并不完整,限制了它们定义细胞分化途径或从机理上深入了解疾病病因学的能力。在这里,我们介绍了 autoCUT&RUN,这是一种从 FACS 分离的原代细胞或组织中快速、超灵敏地分析表观基因组特征的高通量检测方法。该工作流程每次反应可从约 10,000 个细胞中生成可靠的图谱,并有严格的优化策略、高质量抗体和定量尖峰对照支持。作为与免疫基因组联盟(Immunological Genome Consortium)多点合作的一部分,我们利用 autoCUT&RUN 平台建立了一个全面的小鼠原代免疫细胞表观基因组数据库,该数据库由来自 >100 种不同 FACS 分离免疫细胞类型的 >1,500 份表观基因组图谱组成。这些研究为在免疫疗法和精准医疗应用中利用高通量表观基因组学奠定了基础。引用格式: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、免疫基因组联盟。利用自动 CUT&RUN 对有限的原代免疫细胞进行表观基因组指纹分析 [摘要]。In:血癌发现研讨会论文集;2024 年 3 月 4-6 日;马萨诸塞州波士顿。费城(宾夕法尼亚州):AACR; Blood Cancer Discov 2024;5(2_Suppl):Abstract nr P17.
Abstract P17: Epigenomic fingerprinting of limited primary immune cells using automated CUT&RUN
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.
期刊介绍:
The journal Blood Cancer Discovery publishes high-quality Research Articles and Briefs that focus on major advances in basic, translational, and clinical research of leukemia, lymphoma, myeloma, and associated diseases. The topics covered include molecular and cellular features of pathogenesis, therapy response and relapse, transcriptional circuits, stem cells, differentiation, microenvironment, metabolism, immunity, mutagenesis, and clonal evolution. These subjects are investigated in both animal disease models and high-dimensional clinical data landscapes.
The journal also welcomes submissions on new pharmacological, biological, and living cell therapies, as well as new diagnostic tools. They are interested in prognostic, diagnostic, and pharmacodynamic biomarkers, and computational and machine learning approaches to personalized medicine. The scope of submissions ranges from preclinical proof of concept to clinical trials and real-world evidence.
Blood Cancer Discovery serves as a forum for diverse ideas that shape future research directions in hematooncology. In addition to Research Articles and Briefs, the journal also publishes Reviews, Perspectives, and Commentaries on topics of broad interest in the field.