(PQD1) lmpact of cytotoxic and targeted therapy on clonal evolution of CLL

(PQD1) 细胞毒和靶向治疗对 CLL 克隆进化的影响

• 批准号: 8857313
• 负责人: Catherine Ju-Ying Wu
• 金额: $ 55.37万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-06-01 至 2018-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8857313
• 关键词: Address; Adoptive Transfer; Agammaglobulinaemia tyrosine kinase; Animal Model; Back; Biological Models; Biology; Blood; Cancer Relapse; Caring; Cell Line; Cells; Characteristics; Chronic Lymphocytic Leukemia; Clinical; Clinical Trials; Clonal Evolution; Clonality; Code; Combination Drug Therapy; Computer Analysis; Cross-Sectional Studies; Cyclophosphamide; Cytotoxic Chemotherapy; Data; Development; Diagnosis; Disease; Disease Progression; Drug Exposure; Drug resistance; Enrollment; Event; Exposure to; Extinction (Psychology); Flow Cytometry; Frequencies; Future; Gene Expression Profile; Gene Mutation; Genes; Genetic; German population; Health; Hematopoietic Neoplasms; Individual; Indolent; Institutes; Lead; Lesion; Link; Malignant Neoplasms; Measures; Modeling; Mutation; Mutation Analysis; National Heart, Lung, and Blood Institute; Oral; Outcome; Pathway interactions; Patients; Phase; Phase III Clinical Trials; Phenotype; Population; Process; RNA Sequences; Recurrent disease; Relapse; Relative (related person); Research Design; Residual Tumors; Resistance; Risk Factors; Roche brand of rituximab; Role; Sampling; Series; Signal Transduction; Somatic Mutation; Structure; TP53 gene; Techniques; Testing; Therapeutic; Time; Tyrosine Kinase Inhibitor; University of Texas M D Anderson Cancer Center; Variant; Veins; base; cancer cell; cancer genome; cancer therapy; chemotherapy; cohort; del(11q); drug sensitivity; effective therapy; exome sequencing; fitness; fludarabine; genetic analysis; genome editing; improved; in vivo; in vivo Model; inhibitor/antagonist; insight; leukemia; leukemia treatment; longitudinal analysis; lymph nodes; novel; novel therapeutics; outcome forecast; pre-clinical; response; targeted treatment; tool; transcriptome sequencing; treatment strategy; tumor; tumor progression

DESCRIPTION (provided by applicant): Clonal evolution is a key feature of cancer progression and relapse. Our recent study, which utilized a newly developed pipeline that estimates the fraction of cancer cells harboring each somatic mutation within a tumor through integration of whole-exome sequencing and local copy number data, linked the presence of subclones harboring putative driver mutations with adverse clinical outcome in chronic lymphocytic leukemia (CLL) and suggested that CLL therapy may accelerate the process of clonal evolution (Landau et al., Cell 2013). We propose that presence of subclonal mutations that are putative drivers are indicative of an active evolutionary process. We now seek to definitively establish the impact of subclonal mutations on CLL biology, the development of disease relapse and clinical outcome. This will be achieved by longitudinal analysis of clonal structure of serial samples collected from patients enrolled on phase II and phase III clinical trials (and hence uniformly treated) that address the treatment landscape of CLL. In particular, we will perform detailed genetic analysis of samples from patients receiving standard-of-care first line fludarabine-based chemotherapy (Aim 1). In parallel, we will examine patient samples exposed to ibrutinib, a highly promising irreversible inhibitor of Bruton's tyrosine kinase which i anticipated to be a cornerstone of future CLL therapy (Aim 2). Analysis of samples exposed to both these types of therapies will include characterization of subclonal structure as well as assessment of the dynamic phenotypic changes (detected by single cell RNA-sequencing) to validate mutation analysis and determine the transcriptional networks of drug resistant cells in order to reveal potential novel and effective treatment combinations. To causally link the impact of putative drivers and therapy on CLL clonal evolution, we will generate an in vivo model to study interclonal dynamics in the setting of therapy (Aim 3). We will use transformative genome-editing techniques to generate cell lines that model leukemic subpopulations bearing representative CLL driver mutations and thereby mechanistically dissect the contribution of individual genetic lesions to the evolutionary landscape. By creating an animal model of clonal evolution, we will have the potential to more effectively evaluate preclinically the impact of nove therapeutics on clonal selection. In total, these studies are designed to establish a framework for understanding the role of the dynamic evolutionary landscape of CLL on the diagnosis, prognosis and treatment of this currently incurable disease.

描述（由申请人提供）：克隆进化是癌症进展和复发的关键特征。我们最近的研究利用了一种新开发的管道，通过整合全外显子组测序和局部拷贝数数据来估计肿瘤中携带每种体细胞突变的癌细胞的比例，将携带假定驱动突变的亚克隆的存在与慢性淋巴细胞白血病（CLL）的不良临床结果联系起来，并表明CLL治疗可能加速克隆进化的过程（Landau等人，Cell 2013）。我们提出亚克隆突变的存在是假定的驱动因素，表明一个积极的进化过程。我们现在寻求确定亚克隆突变对CLL生物学、疾病复发的发展和临床结果的影响。这将通过纵向分析从II期和III期临床试验（因此统一治疗）的患者收集的系列样本的克隆结构来实现，这些样本涉及CLL的治疗前景。特别是，我们将对接受标准护理一线氟达拉滨化疗的患者样本进行详细的遗传分析（目的1）。与此同时，我们将检查暴露于ibrutinib的患者样本，ibrutinib是一种非常有前途的布鲁顿酪氨酸激酶不可逆抑制剂，我预计它将成为未来CLL治疗的基石（Aim 2）。对暴露于这两种类型治疗的样品的分析将包括亚克隆结构的表征以及动态表型变化的评估（通过单细胞rna测序检测），以验证突变分析并确定耐药细胞的转录网络，以揭示潜在的新颖有效的治疗组合。为了将假定的驱动因素和治疗对CLL克隆进化的影响因果联系起来，我们将创建一个体内模型来研究治疗背景下的克隆间动力学（目的3）。我们将使用变革性基因组编辑技术来生成细胞系，这些细胞系可以模拟具有代表性CLL驱动突变的白血病亚群，从而从机制上剖析个体遗传病变对进化景观的贡献。通过创建克隆进化的动物模型，我们将有可能更有效地评估新疗法对克隆选择的临床前影响。总的来说，这些研究旨在建立一个框架，以了解CLL的动态进化景观对这种目前无法治愈的疾病的诊断、预后和治疗的作用。