Defining the role of metabolic heterogeneity in melanoma dissemination and therapy escape

定义代谢异质性在黑色素瘤传播和治疗逃避中的作用

• 批准号: 9505228
• 负责人: Inna Smalley
• 金额: $ 9.84万
• 依托单位: H. LEE MOFFITT CANCER CTR & RES INST
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-04-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9505228
• 关键词: Address; Affect; Appearance; Award; BRAF gene; Behavior; Bioinformatics; Biology; Biometry; Blood Circulation; Career Mobility; Cell Culture Techniques; Cell Line; Cells; Chronic; Computational Biology; Data Set; Dependence; Development; Distant Metastasis; Dose; Drug Exposure; Drug resistance; Educational workshop; Evolution; Failure; Gene Expression; Gene Expression Profile; Genotype; Glycolysis; Goals; Grant; Growth; Heterogeneity; Hypoxia; Immunofluorescence Immunologic; Impairment; In Vitro; Individual; Knowledge; MEKs; Malignant Neoplasms; Mass Spectrum Analysis; Melanoma Cell; Mentors; Metabolic; Metabolic Marker; Metabolism; Modeling; Nature; Neoplasm Metastasis; Oxidative Phosphorylation; Patients; Pharmaceutical Preparations; Pharmacology; Pharmacotherapy; Phase; Phenotype; Population; Research; Research Personnel; Resistance; Role; SLC2A1 gene; Schedule; Scientist; Shapes; Signal Transduction; Site; Specimen; System; Testing; Therapeutic; Time; Treatment Efficacy; Variant; Work; Xenograft Model; Xenograft procedure; base; drug sensitivity; fitness; glucose uptake; improved; in vivo; in vivo Model; inhibitor/antagonist; mRNA Expression; mathematical model; melanoma; metabolic phenotype; metabolomics; mutant; neoplastic cell; predictive modeling; programs; protein expression; resistance mechanism; response; skills; targeted agent; targeted treatment; transcriptome sequencing; treatment response; tumor; tumor heterogeneity

PROJECT SUMMARY/ ABSTRACT Despite promising initial responses, most BRAF-mutant melanoma patients eventually fail on BRAF inhibitor therapy. The task of understanding therapeutic escape and dissemination is complicated further by the countless number of resistance mechanisms identified so far and the realization that multiple cellular phenotypes may exists within a single genotype. The roles of intra-tumoral heterogeneity in progression and drug resistance are poorly understood, and we submit that strategies tackling this diversity are needed for durable therapeutic responses in patients. We hypothesize that: (i) drug-induced tumor cell phenotypic heterogeneity is driven by the development of inter-dependent and cooperative metabolic niches that promote tumor dissemination and affect the response to therapeutics; and (ii) therapeutic approaches that exploit intra- clonal metabolic competition will give more durable responses in melanoma patients. We will define the metabolic landscape of OXPHOS-dependent and glycolysis-dependent subpopulations in cell culture, xenografts, patient-derived xenografts (PDX) and patient specimens using single-cell RNAseq, global metabolomics and targeted expression panels. We will test how OXPHOS-dependent and glycolysis- dependent subpopulations cooperate to drive metastasis and define the drug sensitivities of the individual subpopulations in vitro and in xenografts and PDXs. We will test if disrupting either OXPHOS or glycolysis, pharmacologically or through gene expression targeting, shapes the metastatic potential or the emergence and heterogeneity of drug resistant subpopulations. We will devise a mathematical model to define optimal, evolutionary-informed dosing of BRAF/MEK plus metabolic inhibitor combinations that impair clonal cooperation and maximize duration of the therapeutic response. These models will be validated in vitro and in PDX models. The K99/R00 award would allow the candidate to conduct the proposed studies under the continued guidance of their primary mentor, Dr. John Cleveland, together with a panel of co-mentors who are renowned experts in melanoma biology, PDX modeling, cancer evolution, metabolism, and statistical and computational approaches to systems-wide large-scale data set analysis. During the K99 phase, the candidate will further develop their knowledge in melanoma metabolism and evolutionary biology, as well as their technical abilities in mass-spectrometry-based metabolomics, advanced computational biology, bioinformatics and biostatistics. With the help of their committee and various seminars, courses and workshops, the candidate will become a stronger scientist, manager, grant writer and mentor, all skills necessary to be an independent investigator. Overall, the proposed work will provide the rationale for therapeutic approaches that exploit intra-clonal metabolic competition to give more durable responses in melanoma patients, as well as a timely career transition for a candidate with strong potential to be a successful independent investigator.

项目总结/摘要 尽管最初的反应很有希望，但大多数BRAF突变的黑色素瘤患者最终都失败了BRAF抑制剂 疗法理解治疗逃避和传播的任务因以下因素而进一步复杂化： 到目前为止，已经确定了无数的耐药机制， 表型可以存在于单个基因型中。肿瘤内异质性在肿瘤进展中的作用， 我们对耐药性知之甚少，我们认为需要采取应对这种多样性的战略， 患者的持久治疗反应。我们假设：（i）药物诱导的肿瘤细胞表型 异质性是由相互依赖和合作的代谢生态位的发展驱动的， 肿瘤扩散并影响对治疗的反应;和（ii）利用内- 克隆代谢竞争将在黑素瘤患者中产生更持久的应答。我们将定义 细胞培养物中OXPHOS依赖性和糖酵解依赖性亚群的代谢景观， 使用单细胞RNAseq的异种移植物、患者源性异种移植物（PDX）和患者标本，全球 代谢组学和靶向表达组。我们将测试氧磷依赖和糖酵解- 依赖性亚群合作驱动转移并确定个体的药物敏感性 在体外和异种移植物和PDX中的亚群。我们将测试是否破坏OXPHOS或糖酵解， 通过基因表达靶向，塑造转移潜力或出现， 耐药亚群的异质性。我们将设计一个数学模型来定义最佳， BRAF/MEK加代谢抑制剂组合的进化信息给药， 合作和最大化治疗反应的持续时间。这些模型将在体外和体内进行验证。 PDX模型。 K99/R 00奖将允许候选人在持续的指导下进行拟议的研究 他们的主要导师，博士约翰克利夫兰，连同一个小组的共同导师谁是著名的专家， 黑色素瘤生物学，PDX建模，癌症演变，代谢，统计和计算 系统范围的大规模数据集分析方法。在K99阶段，候选人将进一步 发展他们在黑素瘤代谢和进化生物学方面的知识，以及他们的技术能力 在基于质谱的代谢组学，先进的计算生物学，生物信息学和生物统计学。 在他们的委员会和各种研讨会，课程和讲习班的帮助下，候选人将成为一个 更强的科学家，经理，授权作家和导师，所有必要的技能是一个独立的调查。 总体而言，拟议的工作将提供利用克隆内的治疗方法的基本原理。 代谢竞争，使黑色素瘤患者的反应更持久，以及及时的职业生涯 过渡的候选人有很大的潜力，成为一个成功的独立调查员。