Understanding Treatment Response Patterns And Therapy Resistance In IDH-Mutant AML

了解 IDH 突变 AML 的治疗反应模式和治疗耐药性

• 批准号: 10652588
• 负责人: Ann-Kathrin Eisfeld
• 金额: $ 63.79万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10652588
• 关键词: Address; Adult Acute Myeloblastic Leukemia; Age; Automobile Driving; Biological; Cancer Center; Cell Differentiation process; Cells; Characteristics; Chemotherapy-Oncologic Procedure; Clinical; Clinical Trials; Clonal Evolution; Collaborations; Collection; Combined Modality Therapy; Complement; Correlative Study; Cytotoxic Chemotherapy; DNA; Data; Data Analyses; Decision Making; Diagnosis; Disease; Disease Progression; Disease remission; Dissection; Drug resistance; Enzymes; Epigenetic Process; Evolution; FDA approved; Future; Gene Expression; Gene Mutation; Genetic; Genetic Anticipation; Genetic Complementation Test; Genome; Genomics; Genotype; Goals; Hematopoietic; Histones; Hypermethylation; Impairment; Induction of Apoptosis; Investigation; Mediating; Methylation; Modality; Modeling; Modernization; Molecular; Molecular Abnormality; Molecular Profiling; Mutate; Mutation; Neoadjuvant Therapy; Newly Diagnosed; Oncology; Outcome; Outcome Assessment; Outcome Study; Pathway interactions; Patients; Pattern; Prediction of Response to Therapy; Production; Prognosis; Prospective cohort; Regimen; Relapse; Research Personnel; Residual Neoplasm; Resistance; Retrospective cohort; Role; Sampling; Therapeutic; Treatment Efficacy; Treatment Failure; Treatment Protocols; Treatment outcome; analytical method; biomarker identification; chemotherapy; clinical practice; clinically relevant; cohort; compare effectiveness; cytotoxic; design; drug mechanism; epigenome; exome sequencing; experience; head-to-head comparison; human old age (65+); improved outcome; in vivo; individual patient; individualized medicine; inhibitor; insight; leukemia; leukemia treatment; liquid biopsy; mouse model; mutant; novel; personalized medicine; precision medicine; predicting response; programs; response; risk stratification; sample collection; skills; small molecule; small molecule inhibitor; targeted agent; targeted treatment; therapy resistant; transcriptome sequencing; translational study; treatment choice; treatment response

ABSTRACT The discovery of IDH1 and IDH2 mutations in AML, and the accompanying functional implications of the resulting neomorphic activity of these mutated enzymes, has resulted in FDA approved targeted therapies. Similarly, the changes brought about in methylation due to IDH mutations in the AML genome have ushered in treatment regimens combining venetoclax with hypomethylating agents. In this setting, where traditional chemotherapy regimens also are applied for treatment of primary diagnoses, the available outcomes data for all three therapeutic approaches should now provide clear metrics of predicted response, given the correct analytical methods. However, given a lack of direct comparison studies, no guidance exists as to which treatment choice will provide best response in IDH-mutated patients. Furthermore, emerging data about the importance of the biologic context on the response to different agents, including co-existing gene mutations and patient age, pose additional questions that need to be systematically addressed in order to provide patients with the best treatment. In order to address this imminent question, and provide data-driven treatment decision support for the ~20% of AML patients harboring IDH mutations, we are proposing a carefully designed, translational study: To directly compare the response of IDH-directed and non-IDH directed targeted therapy, we designed the first head-to-head comparison trial for older and unfit IDH-mutated patients. This long overdue study will provide information about treatment response, as well as first insights into the optimal sequence of treatments, with respect to co-existing molecular features. The trial will be complemented by correlative studies that aim to assess the utility of clonal outgrowth tracking and residual disease assessment for possible dynamic treatment adjustments (iDATA trial, Aim 1). Utilizing the AML patient collection from the Alliance for Clinical Trials in Oncology, as well as our newly established multicenter collaboration between six major US Cancer Centers, we have assembled the thus far largest cohort of 930 IDH-mutated adult AML patients, treated with standard cytotoxic chemotherapy, hypomethylating agents or IDH-directed or non-directed targeted inhibitors. Following our experience in genomic risk stratification models, we are equipped to identify markers predictive of treatment response based on treatment type and genomic context (Aim 2). Lastly, to better understand resistance and escape mechanisms to targeted and non-targeted therapies, we will leverage our large longitudinal specimen collections provide a comprehensive molecular characterization of the leukemic clones during different disease and treatment stages; including clonal and subclonal evolution, identification of clone-specific altered cellular pathways and epigenetic changes at each stage (Aim 3). We are confident that this comprehensive approach, executed by a skilled investigator team will shift current clinical practice paradigms towards data-driven and personalized treatment approaches.

抽象的 AML 中 IDH1 和 IDH2 突变的发现，以及由此产生的伴随功能意义 这些突变酶的新形态活性导致了 FDA 批准的靶向治疗。同样， AML基因组中IDH突变引起的甲基化变化带来了治疗 维奈托克与低甲基化药物相结合的治疗方案。在这种情况下，传统化疗 治疗方案也适用于初级诊断的治疗，所有三个的可用结果数据 考虑到正确的分析，治疗方法现在应该提供预测反应的明确指标 方法。然而，由于缺乏直接比较研究，没有关于哪种治疗选择的指导 将为 IDH 突变患者提供最佳反应。此外，有关重要性的新数据 对不同药物反应的生物学背景，包括共存的基因突变和患者年龄，构成 需要系统解决的其他问题，以便为患者提供最佳治疗。 为了解决这个迫在眉睫的问题，并为约 20% 的患者提供数据驱动的治疗决策支持 携带 IDH 突变的 AML 患者，我们提出一项精心设计的转化研究： 为了直接比较 IDH 定向和非 IDH 定向靶向治疗的反应，我们设计了第一个 针对老年和不健康的 IDH 突变患者的头对头比较试验。这项姗姗来迟的研究将提供 有关治疗反应的信息，以及对最佳治疗顺序的初步见解， 尊重共存的分子特征。该试验将得到相关研究的补充，旨在评估 克隆生长追踪和残留疾病评估在可能的动态治疗中的应用 调整（iDATA 试验，目标 1）。利用来自临床试验联盟的 AML 患者集合 肿瘤学以及我们在美国六大主要癌症中心之间新建立的多中心合作，我们 汇集了迄今为止最大的 930 名 IDH 突变成人 AML 患者队列，并接受标准治疗 细胞毒性化疗、低甲基化药物或 IDH 定向或非定向靶向抑制剂。下列的 凭借我们在基因组风险分层模型方面的经验，我们有能力识别预测治疗的标记物 基于治疗类型和基因组背景的反应（目标 2）。最后，为了更好地理解阻力和 靶向和非靶向治疗的逃避机制，我们将利用我们的大型纵向样本 集合提供了不同疾病期间白血病克隆的全面分子特征 和治疗阶段；包括克隆和亚克隆进化、克隆特异性改变细胞的鉴定 每个阶段的途径和表观遗传变化（目标 3）。 我们相信，由熟练的调查团队执行的这种综合方法将改变当前的情况 数据驱动和个性化治疗方法的临床实践范例。