(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

基本信息

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
项目类别：
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

项目摘要

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。 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）。我们提出，假定驱动因素的亚克隆突变的存在表明有效进化过程。现在，我们寻求确定建立亚克隆突变对CLL生物学，疾病复发和临床结果的影响。这将通过对参加II期和III期临床试验的患者收集的连续样品的克隆结构（因此经过统一治疗）来实现。特别是，我们将对接受基于氟达拉滨的标准第一线的患者的样本进行详细的遗传分析（AIM 1）。同时，我们将检查暴露于伊布鲁替尼的患者样本，这是布鲁顿的酪氨酸激酶的一种非常有前途的不可逆抑制剂，我预计我将成为未来CLL疗法的基石（AIM 2）。暴露于这两种类型的疗法的样品的分析将包括表征下克隆结构以及评估动态表型变化（通过单细胞RNA测序检测到的）以验证突变分析并确定药物耐药细胞的转录网络，以揭示潜在的新颖和有效的治疗组合。为了将推定驱动因素和治疗对CLL克隆进化的影响联系起来，我们将生成一个体内模型，以研究治疗环境中的克隆动力学（AIM 3）。我们将使用变革性的基因组编辑技术来产生模拟具有代表性CLL驱动突变的白血病亚群的细胞系，从而机械地剖析单个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，我们将有潜力更有效地评估Nove Therapeutics对克隆选择的影响。总的来说，这些研究旨在建立一个框架，以理解CLL动态进化景观对当前无法治愈的疾病的诊断，预后和治疗的作用。