Project 3 Topological mapping of chromatin architectures for hormone-independent gene transcription

项目 3 激素非依赖性基因转录染色质结构的拓扑图

基本信息

批准号：
9343416
负责人：
Victor Jin
金额：
$ 41.1万
依托单位：
UNIVERSITY OF TEXAS HLTH SCIENCE CENTER
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-05-15 至 2022-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9343416
关键词：
17q23 Advanced Development Advanced Malignant Neoplasm Agonist Androgens Architecture Bayesian Modeling Binding Breast Cancer Patient CRISPR/Cas technology Cancer Patient Cancer cell line Categories Cell Line Cells ChIP-seq Chromatin Chromatin Loop Chromosomes Complex Computational algorithm Computer Simulation Data Data Set Deposition Dimensions Disease-Free Survival Distal Enhancers Epigenetic Process Estrogen receptor positive Estrogens Gene Expression Regulation Gene Targeting Genes Genetic Transcription Genome Genomic Segment Genomics Goals Histones Hormones Individual Laboratories Location Malignant Neoplasms Malignant neoplasm of prostate Maps Methods Migration Assay Modeling Molecular Conformation Molecular Profiling Nucleosomes Peptides Play Population Primary Neoplasm Protocols documentation Regulation Research Personnel Resistance Role Stimulus Structure Subgroup Systems Analysis Testing The Cancer Genome Atlas Transcriptional Regulation Up-Regulation base cancer cell cell type chromosome conformation capture cohort density epigenomics genetic signature genome editing histone modification hormone resistance improved malignant breast neoplasm migration predictive of treatment response promoter prostate cancer cell response spatiotemporal transcription factor transcriptome sequencing tumor progression

项目摘要

ABSTRACT/SUMMARY - Project 3 Topological mapping of chromatin architectures for hormone-independent gene transcription Long-range chromatin interactions between ER/AR-bound enhancers and promoters are necessary for coordinated gene regulation in breast and prostate cancer cells. These interactions occur via the formation of 3D chromatin architecture that brings enhancers and transcription factor complexes into close contact with target genes. To decode this complex regulation, we and other investigators have previously used Hi-C to map topologically associated domains (TADs) in different cell types. In a further study, we have identified a cancer- specific TAD on chromosome 17q23 that can be partitioned into an ER-regulated transcription hub. Concordant up-regulation of its target genes is found to be associated with short disease-free survival in a subgroup of ER-positive breast cancer patients, irrespective of their anti-hormone treatments. Emerging evidence has also shown AR-specific TADs are present in the prostate cancer cell genome. Therefore, we hypothesize that 1) frequent hormone (i.e., estrogen or androgen) stimulation leads to the formation of ER/AR-related TADs that dynamically regulate transcription of multiple genes for aberrant proliferation of breast and prostate cancer cells and 2) in the presence of antagonists, a subset of these chromatin domains, herein termed transition TADs, continue to be exploited through chromatin redeployment for hormone- independent transcription. Whereas the majority of ER/AR-related TADs are functionally suppressed by antagonists, transition TADs may partially escape this blockade for constitutive regulation of gene transcription. To test these hypotheses, we will use a modified Hi-C method, called tethered conformation capture (TCC), to investigate dynamic changes of TAD structures in hormone-sensitive and -resistant cancer cell lines exposed to agonists or antagonists (Aim 1). ChIP-seq of repressive, active, and gene-body histone marks and CTCF insulator will also be conducted in this cell line panel. MNase-seq and MBDCap-seq datasets will be acquired to map euchromatinized and heterochromatinized TADs. To integrate omics-seq data, we will develop a computational model, PRAM3D, which applies a Poisson Random effect Architecture Model (PRAM) to recapitulate 3D chromatin architectures (Aim 2). A Bayesian hierarchical model will predict putative transition TADs that concordantly regulate hormone-independent transcription of target genes. Furthermore, we will use a nucleosome density method to classify transition TAD subdomains into different regulatory categories, i.e., active, repressive, or bivalent transcription hubs. CRISPR/Cas9 genome-editing of critical chromatin regions may functionally disassemble spatiotemporal organization of these TAD-associated hubs (Aim 3). Proliferation and invasion/migration assays will determine whether this genome editing partially re-sensitizes cancer cells to anti-hormone treatments. We will also interrogate mechanistic contribution of histone modifications and other epigenetic modulators for the establishment of transition TAD structures. In silico expression profiling and single-cell RNA seq will be conducted in primary tumors of TCGA cohorts and in cancer cell subpopulations, respectively, and determine whether concordant regulation of TAD-associated target genes is intrinsic predictors of hormone resistance in breast or prostate cancer.

摘要/总结 - 项目 3 激素非依赖性基因转录染色质结构的拓扑图 ERα/AR 结合增强子和启动子之间的长程染色质相互作用对于乳腺癌和前列腺癌细胞中的协调基因调控通过形成 3D 染色质结构使增强子和转录因子复合物紧密接触为了解码这种复杂的调控，我们和其他研究人员之前使用 Hi-C 来绘制图谱。在进一步的研究中，我们发现了不同细胞类型中的拓扑相关结构域（TAD）。染色体 17q23 上的特异性 TAD 可以被划分为 ERα 调节的转录中心。发现其靶基因的一致上调与动物的短期无病生存有关。 ERα 阳性乳腺癌患者亚组，无论其是否接受抗激素治疗。证据还表明，AR 特异性 TAD 存在于前列腺癌细胞基因组中。鼓励1）频繁的激素（即雌激素或雄激素）刺激导致形成 ERα/AR 相关的 TAD 动态调节多个基因的转录，从而导致异常增殖乳腺癌和前列腺癌细胞，2) 在存在拮抗剂（这些染色质结构域的子集）的情况下，本文中称为过渡 TAD，通过染色质重新部署继续用于激素- 除了大多数 ERα/AR 相关 TAD 受到功能性抑制外。拮抗剂、过渡 TAD 可能部分逃脱基因转录组成性调控的这种封锁。为了测试这些假设，我们将使用一种改进的 Hi-C 方法，称为系链构象捕获 (TCC)，研究暴露的激素敏感和耐药癌细胞系中 TAD 结构的动态变化激动剂或拮抗剂（目标 1）的抑制性、活性和基因体组蛋白标记和 CTCF 的 ChIP-seq。绝缘体也将在此细胞系面板中进行，并将获取 MNase-seq 和 MBDCap-seq 数据集。绘制常染色质化和异染色质化 TAD 的图谱为了整合 omics-seq 数据，我们将开发一个计算模型 PRAM3D，应用泊松随机效应架构模型 (PRAM) 概括 3D 染色质架构（目标 2）。贝叶斯分层模型将预测假定的转变。此外，我们将使用一致调节靶基因的激素非依赖性转录的 TAD。核小体密度方法将过渡 TAD 子域分类为不同的监管类别，即关键染色质区域的活性、抑制性或二价转录中心。可能会在功能上分解这些 TAD 相关中枢的时空组织（目标 3）。侵袭/迁移测定将确定这种基因组编辑是否使癌细胞部分重新敏感我们还将探讨组蛋白修饰和其他作用的机制贡献。用于建立过渡 TAD 结构的表观遗传调节剂和计算机表达谱。单细胞 RNA 测序将在 TCGA 队列的原发性肿瘤和癌细胞亚群中进行，分别确定 TAD 相关靶基因的一致调节是否是内在的乳腺癌或前列腺癌激素抵抗的预测因子。