Architecture and Trajectory of Acquired Resistance to Therapy in AML

AML 获得性治疗耐药的结构和轨迹

• 批准号: 10684101
• 负责人: BRIAN J DRUKER
• 金额: $ 130.9万
• 依托单位: OREGON HEALTH & SCIENCE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-09-30 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10684101
• 关键词: Acute Myelocytic Leukemia; Address; Architecture; Atlases; Biological; Biological Assay; Biology; Bone Marrow; CRISPR screen; Cell Communication; Cell Line; Cells; Clinic; Clinical; Clinical Trials; Clustered Regularly Interspaced Short Palindromic Repeats; Coculture Techniques; Collaborations; Complement; Complex; Computer Models; Data; Data Set; Data Sources; Deposition; Development; Disease; Disease remission; Drug Combinations; Drug Exposure; Drug Sensitization; Drug resistance; Engineering; Environment; Epigenetic Process; Evaluation; Evolution; Exhibits; Feedback; Funding; Genetic; Goals; Immune; Intrinsic factor; Knowledge; Longitudinal Studies; Maps; Mediating; Modeling; New Drug Approvals; Outcome; Pathway interactions; Patient-Focused Outcomes; Patients; Pharmaceutical Preparations; Phenotype; Primary Neoplasm; Publications; Recurrent disease; Refractory; Refractory Disease; Regimen; Research Personnel; Resistance; Resource Sharing; Sampling; Series; Signal Transduction; Specimen; Standardization; Stress; Stromal Cells; Survival Rate; Testing; Therapeutic; Time; Translating; Translations; Work; acquired drug resistance; acute myeloid leukemia cell; anti-tumor immune response; biobank; catalyst; cohort; data integration; data sharing; deep sequencing; detection method; epigenomics; functional genomics; genome wide screen; genome-wide; genomic data; human model; improved; improved outcome; large datasets; leukemia; monocyte; neoplastic cell; next generation; novel; novel drug combination; novel therapeutic intervention; participant enrollment; pressure; prevent; progenitor; programs; public repository; relapse prevention; resistance mechanism; response; single cell analysis; targeted biomarker; targeted treatment; therapy resistant; translational approach; tumor; tumor-immune system interactions; Acute Myelocytic Leukemia; Address; Architecture; Atlases; Biological; Biological Assay; Biology; Bone Marrow; CRISPR screen; Cell Communication; Cell Line; Cells; Clinic; Clinical; Clinical Trials; Clustered Regularly Interspaced Short Palindromic Repeats; Coculture Techniques; Collaborations; Complement; Complex; Computer Models; Data; Data Set; Data Sources; Deposition; Development; Disease; Disease remission; Drug Combinations; Drug Exposure; Drug Sensitization; Drug resistance; Engineering; Environment; Epigenetic Process; Evaluation; Evolution; Exhibits; Feedback; Funding; Genetic; Goals; Immune; Intrinsic factor; Knowledge; Longitudinal Studies; Maps; Mediating; Modeling; New Drug Approvals; Outcome; Pathway interactions; Patient-Focused Outcomes; Patients; Pharmaceutical Preparations; Phenotype; Primary Neoplasm; Publications; Recurrent disease; Refractory; Refractory Disease; Regimen; Research Personnel; Resistance; Resource Sharing; Sampling; Series; Signal Transduction; Specimen; Standardization; Stress; Stromal Cells; Survival Rate; Testing; Therapeutic; Time; Translating; Translations; Work; acquired drug resistance; acute myeloid leukemia cell; anti-tumor immune response; biobank; catalyst; cohort; data integration; data sharing; deep sequencing; detection method; epigenomics; functional genomics; genome wide screen; genome-wide; genomic data; human model; improved; improved outcome; large datasets; leukemia; monocyte; neoplastic cell; next generation; novel; novel drug combination; novel therapeutic intervention; participant enrollment; pressure; prevent; progenitor; programs; public repository; relapse prevention; resistance mechanism; response; single cell analysis; targeted biomarker; targeted treatment; therapy resistant; translational approach; tumor; tumor-immune system interactions

PROJECT SUMMARY: Overall The long-term goal of this Program is to define mechanisms of acquired drug resistance in acute myeloid leukemia (AML) so that novel drug combinations can be deployed to prevent disease relapse and improve patient outcomes. The overall five-year survival rate for AML remains 20%, an outcome that has not changed for several decades. Although seven new regimens have been approved for AML in recent years, the improved initial remission rates with these therapies do not lead to durable outcomes. Disease relapse is fueled by a complex cross-talk of tumor cells adapting with support from the bone marrow microenvironment. The investigators of this proposed ARTNet Center have collaborated for 15+ years, including as a Center in the DRSN consortium – the predecessor to ARTNet. Our prior work has involved development of the largest-to-date functional genomic dataset on AML patient samples, genome-wide CRISPR screens, broad studies of AML interactions with stromal and immune cells, and testing of diverse drug combinations. These studies have led to >150 collaborative publications, continuous collaborative funding for 15+ years, creation of numerous large datasets deposited into public repositories, and translation of findings into numerous clinical trials. Our overarching hypothesis is that the architecture of acquired drug resistance is governed by temporal extrinsic and intrinsic factors and elucidating this trajectory will allow for the identification of properly timed therapeutic strategies to stave off acquired resistance and stay ahead of tumor evolution and adaptation. This hypothesis will be tested through three well integrated Projects addressing the following questions: 1) How does AML tumor cell intrinsic biology adapt to evade therapeutic pressure? We will use genome-wide CRISPR platforms as well as long-term progenitor expansion of primary AML patient samples to understand feedback pathways and shifting epigenetic and cell state landscapes that can drive acquired drug resistance. 2) How does the stromal and immune microenvironment govern drug resistance? We will use co-culture and advanced bone marrow models to perform genome-wide screens and test the impact of single-agents on AML-microenvironment cross-talk. Through computational modeling, we will nominate targeting strategies to mitigate tumor extrinsic resistance signals and boost immune anti-tumor responses. 3) How can resistance signatures and drug combinations be effectively clinically translated? We will use high-throughput and advanced, engineered models of human bone marrow to test and prioritize drug combinations from targets in Projects 1 and 2. We will also study longitudinal specimens from patients enrolled on ongoing clinical trials. All of these data will inform and refine the work of Projects 1 and 2. Our Center will be supported by an Administrative Core and a Functional Phenotyping Core. Collectively, we will develop a comprehensive understanding of acquired drug resistance in AML and identify new regimens to treat patients at the earliest possible stage, prevent relapse, and achieve durable remissions.

项目摘要：总体 该程序的长期目标是定义急性髓样中获得的耐药性机制 白血病（AML），因此可以部署新型药物组合以防止疾病并改善患者 结果。 AML的总体五年生存率仍然20％，这一结果尚未发生变化 几十年。尽管近年来已批准了七个新方案，但最初的提高了 这些疗法的缓解率不会导致持久的结果。疾病继电器是由复合物助长的 肿瘤细胞的串扰在骨髓微环境的支持下适应。调查人员 拟议中的Artnet中心已经合作了15年以上，包括作为DRSN财团的中心 - Artnet的前身。我们先前的工作涉及开发最早的功能基因组 有关AML患者样品，全基因组CRISPR屏幕的数据集，与基质相互作用的广泛研究 和免疫细胞，并测试潜水员的药物组合。这些研究导致> 150个合作 出版物，连续合作资金超过15年，创建了许多存放在 公共存储库，并将发现转化为众多临床试验。我们的总体假设是 获得的药物抗性的结构受临时外部和内在因素和内在因素和 阐明这一轨迹将允许确定正确定时的治疗策略 取消获得的抵抗力，并保持领先于肿瘤的进化和适应性。该假设将进行检验 通过三个良好集成的项目解决以下问题：1）AML肿瘤细胞如何固有 生物学适应逃避治疗压力？我们将使用全基因组CRISPR平台以及长期 初级AML患者样品的祖细胞扩展，以了解反馈途径并转移表观遗传 和细胞状态景观，可以驱动获得的耐药性。 2）基质和免疫如何 微环境控制耐药性？我们将使用共培养和高级骨髓模型进行执行 全基因组筛选并测试单代药物对AML微环境交叉对话的影响。通过 计算建模，我们将提名针对策略来减轻肿瘤外部抗性信号和 增强免疫抗肿瘤反应。 3）如何有效地有效地签名和药物组合 临床翻译？我们将使用人骨髓的高通量和高级工程模型 测试和优先考虑项目1和2中目标的药物组合。我们还将研究纵向标本 来自正在进行的临床试验的患者。所有这些数据都将告知和完善项目1和项目的工作 2。我们的中心将得到行政核心和功能表型核心的支持。总的来说，我们 将对AML中获得的耐药性抗药性产生全面的理解，并确定新方案 尽早治疗患者，防止缓解并实现持久的减免。