Single-Cell RNA Sequencing of Cardiac Organoids to Determine the Genetic Basis for Cell-Specific Responses to Anticancer Drugs

项目摘要 抗癌药物诱导的心血管毒性（CT）是许多接受化疗的患者的主要副作用。 肿瘤疾病的治疗。CT症状在个体之间差异很大，无论是在表现还是在 至发作时间CT的风险使治疗方案复杂化，并使癌症患者受到额外的胁迫。 遗传背景被广泛理解为CT易感性的组成部分，但特定的变体和 其机制在很大程度上仍然未知。为了了解药物诱导CT的遗传基础，我们需要 了解抗癌药物如何刺激多种心血管细胞类型的转录组反应， 不同遗传背景的个体。对抗癌药物反应的个体间差异是 由以药物依赖性方式影响基因调控的遗传变异介导（响应eQTL）。在 换句话说，遗传变异通过调节特定基因的活性对抗癌药物作出反应。值得注意的是， 不同的细胞类型在它们对抗癌药物的响应eQTL方面可以不同。我建议确定基因 对抗癌药物阿霉素（DOX）、5-氟尿嘧啶（5-FU）和 贝伐珠单抗（BVC）在多种心脏细胞类型的遗传多样性小组的70个人。 CT相关响应eQTL的鉴定需要高通量模型系统，其包括 多种心脏细胞类型。对于我的建议的目标1，我已经建立了一个文化环境， 分化方案有助于心脏谱系和支持细胞类型。该程序可重复 将诱导多能干细胞（iPSC）衍生的胚状体（EB）转化为心脏类器官。 初步数据表明，心脏类器官含有心肌细胞，成纤维细胞，血管内皮细胞， 内皮细胞和其它中胚层细胞类型。在目标2中，我将进行单细胞RNA测序 在对照和药物处理的条件下培养的70个心脏类器官的小组上进行scRNA-seq。重复 这个在多个个体中进行的实验将使我能够确定调节反应的eQTL， 不同的心血管细胞类型对每种药物有反应。在目标3中，我将量化基因表达水平， 鉴定心血管细胞中调节对每种抗癌药物转录变化的响应eQTL 类型响应eQTL（由基因型锚定）提供了一个基因座目录， 或间接与治疗有关。这些响应eQTL可以揭示特定的基因和途径， 心血管功能正常阐明CT风险背后的遗传结构将提供以下直觉 心脏毒性机制和相关基因，并为未来旨在对个体患者进行分类的研究提供信息 易感性

PROJECT SUMMARY Anticancer drug-induced cardiovascular toxicity (CT) is a major side effect for many patients undergoing treatment for oncological disorders. CT symptoms vary widely across individuals, both in presentation and in time to onset. Risk of CT complicates treatment protocols and places cancer patients under additional duress. Genetic background is broadly understood to be a component of CT susceptibility, but specific variants and mechanisms remain largely unknown. To understand the genetic basis for drug-induced CT, we need to understand how anticancer drugs stimulate transcriptomic responses in multiple cardiovascular cell types from individuals of different genetic backgrounds. Inter-individual variability in response to anticancer drugs is mediated by genetic variants that affect gene regulation in a drug-dependent manner (response eQTLs). In other words, genetic variants respond to anticancer drugs by regulating the activity of specific genes. Notably, different cell types can vary in their response eQTLs to anticancer drugs. I propose to determine the genetic basis for transcriptomic responses to the anticancer drugs doxorubicin (DOX), 5-fluorouracil (5-FU), and bevacizumab (BVC) in multiple cardiac cell types from a genetically diverse panel of 70 individuals. Identification of CT-associated response eQTLs necessitates a high-throughput model system comprised of multiple cardiac cell types. For Aim 1 of my proposal, I have developed a culture environment and guided differentiation protocol conducive to cardiac lineage and supporting cell types. This procedure reproducibly transforms induced pluripotent stem cell (iPSC)-derived embryoid bodies (EBs) into cardiac organoids. Preliminary data demonstrate that the cardiac organoids harbor cardiomyocytes, fibroblasts, vascular endothelial cells, and other mesodermal cell types. In Aim 2, I will perform single-cell RNA sequencing (scRNA-seq) on a panel of 70 cardiac organoids cultured in control and drug-treated conditions. Repeating this experiment across multiple individuals will allow me to identify the response eQTLs that regulate how different cardiovascular cell types respond to each drug. In Aim 3, I will quantify gene expression levels and identify response eQTLs that regulate transcriptional changes to each anticancer drug in cardiovascular cell types. Response eQTLs (which are anchored by genotype) provide a catalog of loci that interact either directly or indirectly with the treatment. These response eQTLs may reveal specific genes and pathways important for normal cardiovascular function. Elucidating the genetic architecture underlying CT risk will provide intuition on cardiotoxic mechanisms and associated genes and inform future studies that aim to classify individual patient susceptibility.