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: 10209063
• 负责人: Mohammad Fallahi-Sichani
• 金额: $ 37.54万
• 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/10209063
• 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; Therapeutic; 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/antagonist; 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.

项目概要 我们的长期目标是建立对遗传、 决定 MAP 激酶 (MAPK) 通路依赖状态的表观遗传和信号机制 肿瘤细胞。这种理解对于我们预测并最终提高响应能力的能力至关重要 肿瘤细胞对 MAPK 信号传导抑制剂的治疗作用。在本应用中，我们的重点是 BRAFV600 突变的癌症，特别是黑色素瘤，其中 MAPK 信号的过度激活激发了临床研究 MAPK 靶向疗法的评估，但它们通常会导致不同的反应，并且在大多数情况下无法持久治愈 患者。虽然遗传改变与晚期耐药相关，但表观遗传异质性与 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动态 BRAF/MAPK 依赖性状态，从而降低 MAPK 抑制剂的治疗效果。在这里，我们 提出一种系统药理学方法来检验 MAPK 状态下的异质性假设 依赖性可能是由异质性肿瘤细胞的关键表观遗传变异的子集造成的。 微分状态。为了识别此类变异的调节因子，我们筛选了 276 个小分子表观遗传因子 调节剂单独或与黑色素瘤细胞系中的 BRAF/MEK 激酶抑制剂联合使用 代表了广泛的分化状态。将多重单细胞分析与多变量相结合 通过统计模型和遗传实验，我们确定了三类抑制剂，它们的目标似乎是 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 (KDM1A) 依赖性状态相关 未分化 (AXLHigh)、MAPK 抑制剂抗性 (p-ERKHigh) 细胞，(2) Jumonji 组蛋白去甲基酶 与神经嵴样 (NGFRHigh/AXLLow) 细胞相关的 (Jmj-KDM) 依赖性状态，以及 (3) 诱导的状态 通过 NGFRHigh 细胞中的 BET 溴结构域抑制剂，显着增强其对 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， 强调遗传多样性黑色素瘤细胞群之间相互的表观遗传脆弱性。在这个 建议，我们的目标是：（1）检查已识别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）确定预测因子 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 克服体外和体内 MAPK 抑制剂耐受细胞异质群体的策略。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、蛋白质组测量和网络级计算建模。我们将使用这些 工具作为测量、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来提高临床效益和耐久性 黑色素瘤和其他潜在 BRAF 突变癌症患者的治疗反应。