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

基本信息

批准号：
10598570
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
项目类别：
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/10598570
关键词：
BRAF gene Bromodomain Bromodomains and extra-terminal domain inhibitor Cell Differentiation process Cell Line Cell Survival Cells Clinical Computer Models Data Dependence Development Drug Tolerance Drug resistance Epigenetic Process Experimental Genetics Frequencies Genetic Goals Heterogeneity Histones Human In Vitro Individual KDM1A gene 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 Undifferentiated Variant Work cell growth cell type cellular imaging combinatorial epigenetic variation 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

项目摘要

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网络级别和单细胞的理解，对遗传之间的相互作用，确定MAP激酶（MAPK）途径依赖性状态的表观遗传和信号传导机制肿瘤细胞。这种理解将是我们预测和最终提高响应能力能力的关键肿瘤细胞对MAPK信号传导的治疗抑制剂的抑制剂。在此应用程序中，我们的重点是BRAFV600 突变的癌症，尤其是黑色素瘤，其中MAPK信号过度激活促进了临床对MAPK靶向疗法的评估，但它们通常会导致可变反应，并且在大多数情况下没有持久的治疗方法患者。遗传改变与晚期抗性有关，而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自适应可塑性会影响动态 BRAF/MAPK依赖性状态，从而降低了MAPK抑制剂的治疗功效。在这里，我们提出了一种系统药理学方法，以检验MAPK状态的异质性的假设依赖性可能是由于异质性肿瘤细胞之间关键表观遗传变异的子集引起的分化状态。为了识别这种变化的调节剂，我们筛选了276个小分子表观遗传调节剂单独或与黑色素瘤细胞系中的BRAF/MEK激酶抑制剂结合代表广泛的分化状态。将多路复用单细胞分析与多元分析集成统计建模和遗传实验，我们确定了三类靶向靶向的抑制剂黑色素瘤细胞中不同的表观遗传态：（1）赖氨酸脱甲基酶1a（KDM1A）依赖性状态相关状态与未分化的（Axlhigh），MAPK抑制剂耐药（P-Erkhigh）细胞，（2）Jumonji组蛋白脱甲基酶（JMJ-KDM）依赖性状态与神经Crest样（NGFRHIGH/AXLLOW）细胞相关，（3）诱导的状态通过BET NGFRHIGH细胞中的BET溴结构域抑制剂，这大大提高了其对MAPK的需求信号。单细胞分析表明，这些状态可能以不同的组合和频率共存，突出了遗传多样的黑色素瘤细胞群体中的相互表观遗传脆弱性。在这个提案，我们的目的是：（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的表观遗传态的机制，（2）确定 BRAF突变的细胞系和患者衍生的肿瘤中的表观遗传转换，以及（3）测试新表观遗传学克服MAPK抑制剂耐耐药细胞在体外和体内的异质种群的策略。这会通过系统药理学方法来实现遗传实验，高通量单细胞成像，蛋白质组学测量和网络级计算建模。我们将使用这些工具作为测量，模型，调节和最终克服药物异质种群的一种手段 - 耐受细胞。期望我们的工作提供合理的方法来提高临床利益和耐用性黑色素瘤患者和其他BRAF突变癌症患者的治疗反应。