Extending experimental evolutionary game theory in cancer in vivo to enable clinical translation: integrating spatio-temporal dynamics using mathematical modeling

扩展癌症体内实验进化博弈论以实现临床转化：使用数学建模整合时空动力学

• 批准号: 10662098
• 负责人: Andriy Marusyk
• 金额: $ 55.8万
• 依托单位: CLEVELAND CLINIC LERNER COM-CWRU
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2028-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10662098
• 关键词: 3-Dimensional; Address; Antibiotic Resistance; Automobile Driving; Biological; Biological Assay; Biological Process; Biology; Cancer Model; Clinic; Clinical; Clinical Medicine; Clinical Trials; Code; Communities; Complex; Computer Models; Data; Disease; Ecosystem; Epidermal Growth Factor Receptor; Evolution; Exhibits; Extinction; Favorable Clinical Outcome; Fisheries; Game Theory; Generations; Genes; Glean; Grain; Growth; Heterogeneity; In Vitro; Intuition; Life; Literature; Malignant Neoplasms; Malignant neoplasm of prostate; Mathematics; Measurement; Measures; Methods; Modeling; Mutation; New Agents; Non-Small-Cell Lung Carcinoma; Patients; Pesticides; Pharmaceutical Preparations; Phase II Clinical Trials; Phenotype; Population; Population Heterogeneity; Pre-Clinical Model; Process; Protein Tyrosine Kinase; Proteins; Qualitative Methods; Race; Refractory; Relapse; Research; Resistance; Role; System; Testing; Theoretical Studies; Theoretical model; Therapeutic; Therapeutic Intervention; Time; Translating; Tyrosine Kinase Inhibitor; Work; abiraterone; actionable mutation; anticancer research; cancer therapy; clinical translation; clinically relevant; design; experience; in silico; in vitro Model; in vivo; inhibitor; insight; interdisciplinary approach; invention; mathematical model; multi-scale modeling; mutant; neoplastic cell; next generation; novel; pathogen; physical science; pressure; response; spatiotemporal; success; targeted cancer therapy; targeted treatment; theories; therapy design; tool; trial design; tumor; two-dimensional

ABSTRACT Targeted cancer therapy, in the form of tyrosine kinase inhibitors, has been a game changer for patients with cancers driven by activating mutations in genes encoding these proteins. Yet, while we are seeing overall survival benefits unlike with any new agents in over a decade, cures remain elusive, or non-existent, as resistance to these agents reliably emerges. The process driving this resistance is the same process that drives invasive pests' resistance to pesticides, pathogens' resistance to antibiotics and many other phenomena in life: Darwinian evolution. While this is being increasingly recognized, it has yet to change the paradigm in cancer research where most projects are centered on a hunt for actionable mutations conferring resistance. While these secondary mutations are often druggable themselves, we submit that this is a never-ending race that evolution will always win. We hypothesize that an approach centered instead on studying the evolutionary process itself can help break this cycle. While there is a robust theoretical literature modeling cancer evolution with mathematics, there is a relative paucity of research connecting this theory to empirical biology or clinical medicine. To address this shortcoming, we have worked for the past three years to develop a first-in-class evolutionary game assay to directly measure the eco-evolutionary interactions driving the emergence of resistance in vitro. This assay allows us to directly parameterize an evolutionary game theoretic model with empiric studies in any system. Here, we propose to extend our initial observations revealing a vast heterogeneity in evolutionary dynamics under different agents in vitro to allow for clinical translation by extend ouring assay to an in vivo system. We posit that the new methods and understanding we will gain during this proposal will benefit the cancer research community as a whole, as well as provide novel opportunities for therapeutic interventions aimed at disrupting and altering the evolutionary mechanisms driving resistance.

摘要 酪氨酸激酶抑制剂形式的靶向癌症治疗已经改变了患者的游戏规则， 由编码这些蛋白质的基因中的激活突变驱动的癌症。然而，当我们看到整体生存率 与十多年来的任何新药物不同，治疗方法仍然难以捉摸，或者不存在，因为对 这些代理可靠地出现。驱动这种耐药性的过程与驱动侵入性 害虫对杀虫剂的抗药性，病原体对抗生素的抗药性以及生命中的许多其他现象：达尔文主义 进化虽然这一点越来越被认识到，但它尚未改变癌症研究的范式， 大多数项目都集中在寻找赋予耐药性的可行突变上。虽然这些次要 突变本身往往是药物，我们认为这是一个永无止境的比赛，进化将永远 赢了我们假设，以研究进化过程本身为中心的方法可能会有所帮助。 打破这个循环。虽然有一个强大的理论文献用数学建模癌症演变， 将这一理论与经验生物学或临床医学联系起来的研究相对较少。为了解决这个 在过去的三年里，我们一直致力于开发一流的进化游戏分析， 直接测量推动体外抗性出现的生态进化相互作用。该测定允许 我们直接参数化的进化博弈论模型的经验研究，在任何系统。这里我们 我建议扩展我们最初的观察，揭示在不同的环境下进化动力学的巨大异质性。 通过将OUR测定扩展到体内系统，允许临床转化。我们认为， 我们在这项提案中获得的方法和理解将使癌症研究界受益， 整体，以及提供新的机会，治疗干预，旨在破坏和改变 进化机制驱动阻力。