Linking Genetic, Epigenetic and Signaling Mechanisms of Oncogene Addiction

将癌基因成瘾的遗传、表观遗传和信号机制联系起来

• 批准号: 10392471
• 负责人: Mohammad Fallahi-Sichani
• 金额: $ 34.77万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-05-01 至 2026-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10392471
• 关键词: BRAF gene; Bromodomain; Cell Differentiation process; Cell Line; Cell Survival; Cells; Clinical; Computer Models; Consequentialism; Data; Dependence; Development; Drug Tolerance; Drug resistance; Epigenetic Process; Frequencies; Genetic; Goals; Heterogeneity; Histones; Human; In Vitro; Individual; KDM1A gene; Lead; Link; Lysine; MAP3K1 gene; MEKs; Malignant Neoplasms; Measurement; Measures; Mediating; Melanoma Cell; Mitogen-Activated Protein Kinases; Modeling; Molecular; Mutate; Mutation; Neural Crest; Oncogenes; Pathway interactions; Patients; Pattern; Pharmaceutical Preparations; Pharmacology; Phenotype; Population; Population Heterogeneity; Post-Translational Protein Processing; Proteins; Proteomics; Proto-Oncogene Proteins B-raf; Reader; Resistance; Role; Signal Transduction; Specificity; Statistical Models; System; Testing; Tissues; Treatment Efficacy; Tumor-Derived; Undifferentiated; Variant; Work; base; cell growth; cell type; cellular imaging; combinatorial; epigenetic variation; experimental study; histone demethylase; improved; in vivo; inhibitor; inhibitor therapy; kinase inhibitor; melanoma; neoplastic cell; oncogene addiction; patient derived xenograft model; predictive tools; prevent; research clinical testing; response; single cell analysis; small molecule; small molecule inhibitor; targeted cancer therapy; targeted treatment; tool; treatment response; treatment strategy; tumor; tumor xenograft

PROJECT SUMMARY Our long-term goal is to build a network-level and single-cell understanding of the interplay between genetic, epigenetic and signaling mechanisms that determine the state of MAP kinase (MAPK) pathway dependency in tumor cells. Such understanding will be key to our ability to predict and ultimately improve the responsiveness of tumor cells to therapeutic inhibitors of MAPK signaling. Our focus, in this application, is on BRAFV600 mutated cancers, particularly melanomas, where hyperactivation of MAPK signaling has motivated the clinical evaluation of MAPK-targeted therapies, but they often lead to variable responses and no durable cure in most patients. While genetic alterations are associated with late resistance, epigenetic heterogeneity associated with tumor differentiation state or tissue lineage and its adaptive plasticity within a tumor influence the dynamic state of BRAF/MAPK dependency, thereby diminishing the therapeutic efficacy of MAPK inhibitors. Here, we propose a systems pharmacology approach to test the hypothesis that heterogeneity in the state of MAPK dependency may result from a subset of key epigenetic variations across tumor cells of heterogeneous differentiation states. To identify regulator of such variations, we screened 276 small-molecule epigenetic modulators individually or in combination with BRAF/MEK kinase inhibitors in melanoma cell lines that represent a wide spectrum of differentiation states. Integrating multiplexed single-cell analysis with multivariate statistical modeling and genetic experiments, we identified three classes of inhibitors that target seemingly distinct epigenetic states in melanoma cells: (1) a lysine demethylase 1A (KDM1A)-dependent state associated with undifferentiated (AXLHigh), MAPK inhibitor-resistant (p-ERKHigh) cells, (2) a Jumonji histone demethylase (Jmj-KDM)-dependent state associated with neural crest-like (NGFRHigh/AXLLow) cells, and (3) a state induced by BET bromodomain inhibitors in NGFRHigh cells, which substantially enhances their requirement for MAPK signaling. Single-cell analysis shows that these states might co-exist in different combinations and frequencies, highlighting mutual epigenetic vulnerabilities among genetically diverse melanoma cell populations. In this proposal, we aim to: (1) examine the molecular specificity of the identified small molecule inhibitors as well as mechanisms that govern each of the phenotypically consequential epigenetic states, (2) identify predictors of epigenetic switching in BRAF-mutated cell lines and patient-derived tumors, and (3) test new epigenetic strategies to overcome heterogeneous populations of MAPK inhibitor-tolerant cells in vitro and in vivo. This will be achieved through a systems pharmacology approach, combining genetic experiments, high-throughput single-cell imaging, proteomic measurements, and network-level computational modeling. We will use these tools as a means to measure, model, modulate and ultimately overcome heterogeneous populations of drug- tolerant cells. Our work is expected to provide rational approaches to improve the clinical benefit and durability of treatment response in patients with melanoma and potentially other BRAF-mutated cancers.

项目摘要 我们的长期目标是建立一个网络水平和单细胞的理解之间的相互作用遗传， 表观遗传和信号机制，决定MAP激酶（MAPK）通路依赖性的状态， 肿瘤细胞这种理解将是我们预测并最终提高响应能力的关键 MAPK信号传导的治疗性抑制剂。在此应用中，我们的重点是BRAFV 600 突变的癌症，特别是黑色素瘤，其中MAPK信号传导的过度活化已经促使临床治疗。 MAPK-targeted疗法的评估，但他们往往导致可变的反应，并没有持久的治愈，在大多数 患者虽然遗传改变与晚期抗性相关，但与 肿瘤分化状态或组织谱系及其在肿瘤内的适应性可塑性影响肿瘤细胞的动态分化。 BRAF/MAPK依赖性状态，从而降低MAPK抑制剂的治疗功效。这里我们 提出了一种系统药理学的方法来测试的假设，在MAPK状态的异质性 依赖性可能是由异质性肿瘤细胞之间的关键表观遗传变异的子集引起的。 分化国家。为了确定这种变异的调节因子，我们筛选了276个小分子表观遗传学基因， 在黑素瘤细胞系中单独或与BRAF/MEK激酶抑制剂组合使用BRAF/MEK激酶抑制剂， 代表了一个广泛的分化状态。将多重单细胞分析与多变量 通过统计建模和遗传实验，我们确定了三类抑制剂， 黑色素瘤细胞中不同的表观遗传状态：（1）赖氨酸脱甲基酶1A（KDM 1A）依赖性状态， 用未分化的（AXLHigh）、MAPK抑制剂抗性（p-ERK High）细胞，（2）Jumonji组蛋白去甲基化酶 与神经嵴样（NGFR高/AXLlow）细胞相关的（Jmj-KDM）依赖性状态，和（3）诱导的状态 通过BET布罗莫结构域抑制剂在NGFRHigh细胞中，这大大提高了它们对MAPK的需求 发信号。单细胞分析表明，这些状态可能以不同的组合和频率共存， 突出了遗传多样性黑色素瘤细胞群体之间的相互表观遗传脆弱性。在这 我们的目标是：（1）检查已鉴定的小分子抑制剂的分子特异性，以及 控制每个表型结果表观遗传状态的机制，（2）确定 BRAF突变细胞系和患者来源的肿瘤中的表观遗传转换，以及（3）测试新的表观遗传转换。 在体外和体内克服MAPK受体耐受细胞的异质群体的策略。这将 通过系统药理学方法，结合遗传实验，高通量 单细胞成像、蛋白质组学测量和网络级计算建模。我们将会用这些 工具作为衡量、建模、调节并最终克服药物异质群体的手段， 耐受细胞我们的工作有望提供合理的方法，以提高临床效益和耐久性 黑色素瘤和其他BRAF突变癌症患者的治疗反应。