Deciphering the 3D genome of pediatric brain tumors

破译儿童脑肿瘤的 3D 基因组

基本信息

批准号：
10585741
负责人：
Nadia Dahmane
金额：
$ 39.12万
依托单位：
WEILL MEDICAL COLL OF CORNELL UNIV
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-09-20 至 2024-09-19
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10585741
关键词：
3-Dimensional Abnormal Cell Affect Age-Months Architecture Biology Brain Brain Neoplasms Cell Differentiation process Cell Line Cells Cerebellum Child Childhood Childhood Brain Neoplasm Childhood Malignant Brain Tumor Chromatin Code Computing Methodologies DNA Sequence Data Data Set Defect Development Developmental Process Disease Embryonic Development Ependymoma Epigenetic Process Etiology Event Frequencies Funding Future Gene Expression Gene Expression Regulation Genetic Genome Genomics Genotype Glioma Institutes Lead Link Malignant - descriptor Malignant Childhood Neoplasm Malignant Neoplasms Maps Medicine Modeling Morbidity - disease rate Neurologic Effect Normal tissue morphology Output Pathogenesis Patients Pediatric Hospitals Pediatric Neoplasm Philadelphia Pilot Projects Play Proteins Publishing Recurrence Refractory Research Rhabdoid Tumor Role SHH gene SMARCA4 gene SMARCB1 gene Sampling Single Nucleotide Polymorphism Solid Neoplasm Testing Therapeutic Tissues Training Untranslated RNA Variant aggressive therapy bioinformatics pipeline cohort data integration deep learning deep learning model experimental study genetic variant innovation insertion/deletion mutation interest medulloblastoma multidisciplinary nerve stem cell new therapeutic target novel postnatal development programs promoter prototype single-cell RNA sequencing smoothened signaling pathway stem cells tool transcriptome tumor tumorigenesis whole genome

项目摘要

Project Summary Pediatric brain tumors are the most frequent cause of morbidity in children with solid tumors. Importantly, the aggressive therapeutic regiments often lead to debilitating neurological effects. The realization that developmental processes critical to brain development are also deregulated in cancer has provided new hope for understanding and treating brain tumors. Indeed, single cell-RNAseq analyses have further demonstrated the role of defects in lineage determination for pediatric brain tumors. To discover novel drivers of tumorigenesis, we will focus on the function of three-dimensional (3D) genome folding in pediatric brain tumors. Indeed, 3D chromatin interactions are involved in gene expression regulation, and changes in genome folding are linked to cell identity acquisition during development. While there is increasing interest in elucidating the function of 3D genome architecture during developmental processes and in cancer, how the 3D genome is organized in different pediatric brain tumors and its roles in tumor formation and progression are unknown. We hypothesize that disrupted 3D genome folding during embryonic or postnatal development alters gene expression leading to abnormal cell differentiation and tumorigenesis in the developing brain. To test our hypothesis, we will comprehensively interrogate the genomes of pediatric brain tumors for non-coding variants that may affect 3D genome folding. We will use a deep-learning model called Akita that predicts 3D chromatin interaction frequencies from genome sequence alone. Because Akita only requires DNA sequence as input, we can predict the effect of any variant within a single framework that accommodates single-nucleotide variants (SNVs), insertion/deletions (indels), and structural variation (SVs). Akita will be used with pediatric brain whole genome sequences (WGS) from Gabriella Miller Kids First (KF) plus chromatin capture, epigenetic, and expression data from the 4D Nucleome (4DN) and Genotype-Tissue Expression (GTEx) programs in the following aims: 1) Determine the 3D genome architecture of Atypical teratoid/rhabdoid tumor AT/RT tumors. We have initiated our study using AT/RT, tumors thought to be due to defects in early development11 and the most common brain tumor in children less than six months of age. 1.A. We will develop a bioinformatics pipeline that uses Akita to quantify how much a genetic variant is predicted to disrupt 3D chromatin interactions in AT/RT tumors. 1.B. We will validate and determine the functional relevance of 3D genomic folding disruptions observed in AT/RT tumors. 2) Determine the 3D genome architecture of malignant pediatric tumors. We will extend our analyses with Akita to additional malignant pediatric brain tumors, focusing for this pilot project on the most malignant and treatment refractory tumors. This innovative project, using a new deep-learning tool Akita, will lead to, novel research hypotheses and will accelerate the discovery of additional regulators of pediatric cancer tumorigenesis and thus to potential therapeutic strategies for these devastating diseases.

项目概要儿童脑肿瘤是实体瘤儿童发病的最常见原因。重要的是，积极的治疗方案常常会导致神经系统衰弱。认识到对大脑发育至关重要的发育过程在癌症中也被解除管制，这提供了新的希望用于了解和治疗脑肿瘤。事实上，单细胞 RNAseq 分析进一步证明缺陷在儿童脑肿瘤谱系测定中的作用。为了发现肿瘤发生的新驱动因素，我们将重点关注三维（3D）基因组折叠在儿科脑肿瘤中的功能。确实，3D 染色质相互作用涉及基因表达调控，基因组折叠的变化与发育过程中细胞身份的获取。尽管人们对阐明 3D 功能越来越感兴趣发育过程和癌症中的基因组结构，3D 基因组如何组织不同的儿童脑肿瘤及其在肿瘤形成和进展中的作用尚不清楚。我们假设在胚胎或出生后发育过程中破坏 3D 基因组折叠，改变基因表达，导致发育中大脑中的异常细胞分化和肿瘤发生。为了检验我们的假设，我们将全面询问儿童脑肿瘤的基因组中可能影响 3D 的非编码变异基因组折叠。我们将使用名为 Akita 的深度学习模型来预测 3D 染色质相互作用仅来自基因组序列的频率。因为秋田只需要 DNA 序列作为输入，我们就可以预测容纳单核苷酸变体（SNV）的单一框架内任何变体的影响，插入/删除 (indel) 和结构变异 (SV)。秋田将用于儿科大脑全基因组来自 Gabriella Miller Kids First (KF) 的序列 (WGS) 以及染色质捕获、表观遗传和表达数据来自 4D 核组 (4DN) 和基因型组织表达 (GTEx) 计划，目标如下：1) 确定非典型畸胎瘤样/横纹肌样瘤 AT/RT 肿瘤的 3D 基因组结构。我们已经启动了我们的使用 AT/RT 进行的研究中，肿瘤被认为是由于早期发育缺陷11和最常见的大脑六个月以下儿童的肿瘤。 1.A.我们将开发一个生物信息学管道，利用秋田量化预测遗传变异在 AT/RT 肿瘤中破坏 3D 染色质相互作用的程度。 1.B.我们将验证并确定在 AT/RT 肿瘤中观察到的 3D 基因组折叠破坏的功能相关性。 2) 确定儿科恶性肿瘤的3D基因组结构。我们将扩展对秋田的分析到其他恶性儿科脑肿瘤，该试点项目的重点是最恶性的和治疗难治性肿瘤。这个创新项目使用新的深度学习工具 Akita，将带来新颖的研究假设并将加速发现儿科癌症肿瘤发生的其他调节因子，从而这些破坏性疾病的潜在治疗策略。