Spatial Epigenomic Profiling of Immune Cell Signatures at Subcellular Resolution in Health and Disease

健康和疾病中免疫细胞特征的亚细胞分辨率空间表观基因组分析

• 批准号: 10201436
• 负责人: Ahmet F. Coskun
• 金额: $ 10.79万
• 依托单位: GEORGIA INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-02 至 2023-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10201436
• 关键词: 3-Dimensional; Acute Lymphocytic Leukemia; Address; Aspirate substance; Attention; B-Cell Development; B-Lymphocyte Subsets; B-Lymphocytes; Biological; Biological Assay; Bone Marrow; Cancer Patient; Catalogs; Cell Communication; Cell Culture Techniques; Cell Line; Cells; Child; Childhood Hematopoietic Neoplasm; Chromatin; Chromosomes; Coculture Techniques; Collaborations; Computational Technique; Computer Analysis; Cytometry; DNA; Data; Development; Disease; Enzymes; Epigenetic Process; Event; Exhibits; Four-dimensional; Future; Genetic Transcription; Genomic Segment; Genomics; Health; Hematopoietic Neoplasms; Heterogeneity; Histone Deacetylase Inhibitor; Human; Imaging technology; Immune; Immunotherapy; In Vitro; Individual; Leukemic Cell; Libraries; Ligation; Light; Machine Learning; Malignant Childhood Neoplasm; Maps; Measurement; Medicine; Mentorship; Methods; Modeling; Multiplexed Ion Beam Imaging; Newly Diagnosed; Patients; Pattern; Pharmaceutical Preparations; Proteins; Proteomics; Relapse; Research; Resistance; Resolution; Role; Sampling; Signal Transduction; Site; Specificity; Stem cell transplant; Stromal Cells; System; Technology; Toxic effect; Transcriptional Regulation; Variant; Visualization; acute lymphoblastic leukemia cell; base; cancer cell; cancer therapy; chemotherapy; chromatin remodeling; design; epigenetic drug; epigenetic therapy; epigenetic variation; epigenomics; experimental study; human subject; imaging approach; imaging biomarker; imaging capabilities; lymphoblast; mathematical analysis; multiplexed imaging; nanometer; next generation; novel; novel therapeutics; pediatric patients; progenitor; public health relevance; sample fixation; shape analysis; single cell analysis; success; technology development; therapy design; therapy resistant; treatment response

SPATIAL EPIGENOMIC PROFILING OF IMMUNE CELL SIGNATURES AT SUBCELLULAR RESOLUTION IN HEALTH AND DISEASE More than ten percent of childhood cancers are still incurable and need novel therapies. Epigenetic treatments deserve special attention with their specificity and reduced toxicity. Here I plan to explore epigenetic profiles of immune and cancer cells in normal development and blood cancer patients under the mentorship of Garry Nolan for single cell proteomics technology development, in collaboration with Howard Chang for implementation of epigenomic methods such as chromosome accessibility assays, and with Kara Davis for epigenetics studies of treatment resistant B cell subtypes in acute lymphoblastic leukemia (ALL). Epigenetic measurements have been limited to bulk level sequencing and ligation assays or limited number of imaging markers. To address these limitations, I will use an emerging three dimensional (3D) proteomic imaging technology in individual cells, termed as 3D Multiplexed ion beam imaging (MIBI) or 3D MIBI. Epigenetics research by 3D MIBI benefits from high degree multiplexing (up to 100 markers) and super resolution imaging capability (20 nm x-y; 5 nm z resolution), providing exciting opportunities to study genomic sites, methylated DNA, protein factors, and chromosome accessibility, all within the same experiments in single immune and aberrant (leukemic) cells. To systematically determine epigenetic states, I plan to utilize clonal B cell lines to decipher variability of epigenetic components including chromatin states, protein factors and modifiers by a fifty-marker 3D MIBI panel (Aim 1). These experiments will show distribution of epigenetic factors (linear or log-scale) in their expression levels and spatial variations (global or local) in the chromatin states. I will then perform experiments with primary B cells isolated from six different bone marrow aspirates of normal human subjects (Aim 2). I will correlate epigenetic signatures of each B cell subtype to corresponding development state (progenitor, pre, post, or mature). I will then perform an ex vivo co-culture of primary B cells on OP9 stromal cells over 1-6 weeks of culturing, which will be followed by fixation and profiling by 3D MIBI. These perturbation experiments will show how signaling events from neighboring cells drive necessary epigenetic conditions that are required for reaching a B cell subset. Finally, I will turn to primary B cells that are isolated from twenty newly diagnosed ALL patients (Aim 3). I will dissect differentiation and spatial epigenomic remodeling of responder B cell subsets and treatment resistant B cell subtypes from bone marrow aspirates using the OP9 co-culture. These will show how treatment resistance arises from a single epigenetic state or multiple distinct epigenetic signatures. I will then screen Histone deacetylase inhibitors (HDACi) on the same co-culture of B cell subtypes from ALL and stromal cells. By varying concentration and duration of inhibition conditions, I will dissect the role of epigenetic drugs in spatial chromatin remodeling toward development of epigenetic therapies in ALL. Together, these experiments will shed light on the role of epigenetic programming for cancer treatment applications from immune cell signatures in normal subjects and blood cancer patients.

亚细胞上免疫细胞特征的空间表观基因组分析 卫生和疾病解决 超过百分之十的童年癌症仍然无法治愈，需要新颖的疗法。表观遗传治疗 值得特别注意的特异性和降低的毒性。我计划在这里探索 在Garry的指导下，正常发育和血液癌患者的免疫和癌细胞 Nolan用于单细胞蛋白质组学技术开发，与Howard Chang合作 实施表观基因组方法，例如染色体可访问性测定法，并与Kara Davis一起 急性淋巴细胞白血病中耐药B细胞亚型的表观遗传学研究（ALL）。表观遗传学 measurements have been limited to bulk level sequencing and ligation assays or limited number of imaging 标记。为了解决这些限制，我将使用新出现的三维（3D）蛋白质组学成像 单个细胞中的技术，称为3D多路复用离子束成像（MIBI）或3D MIBI。表观遗传学 3D MIBI的研究受益于高度多路复用（最多100个标记）和超级分辨率成像 功能（20 nm x-y; 5 nm z分辨率），提供了研究基因组位点的令人兴奋的机会，甲基化的 在单个免疫和 异常（白血病）细胞。为了系统地确定表观遗传状态，我计划利用克隆B细胞系 表观遗传成分（包括染色质状态，蛋白质因子和修饰剂）的破译变异性 五十个标记3D MIBI面板（AIM 1）。这些实验将显示表观遗传因素的分布（线性或 对数尺度）在染色质状态中的表达水平和空间变化（全局或局部）中。然后我会 用从正常人的六个不同骨髓抽吸物中分离出的原代B细胞进行实验 受试者（目标2）。我将将每个B细胞亚型的表观遗传特征与相应的发展相关联 状态（祖先，预科，邮政或成熟）。然后，我将在OP9上执行原代B细胞的离体共文化 基质细胞在1-6周的培养中，然后由3D MIBI进行固定和分析。这些 扰动实验将显示来自相邻细胞的信号事件如何驱动必要的表观遗传 达到B细胞子集所需的条件。最后，我将转向隔离的主要B单元 从二十个新诊断出所有患者（AIM 3）。我将剖析分化和空间基因组学 响应者B细胞子集的重塑和抗治疗抗体B细胞亚型从骨髓抽吸物中 使用OP9共培养。这些将显示如何由单个表观遗传状态或 multiple distinct epigenetic signatures.然后，我将筛选组蛋白脱乙酰基酶抑制剂（HDACI） 来自所有和基质细胞的B细胞亚型的共培养。通过不同的浓度和抑制持续时间 条件，我将剖析表观遗传药物在空间染色质重塑中的作用 总共表观遗传疗法。这些实验将共同阐明表观遗传编程的作用 对于正常受试者和血液癌患者中免疫细胞特征的癌症治疗应用。