CLL clonal evolution and the development of therapy-driven resistance

CLL 克隆进化和治疗驱动耐药性的发展

• 批准号: 10005158
• 负责人: Catherine Ju-Ying Wu
• 金额: $ 36.08万
• 依托单位: DANA-FARBER CANCER INST
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-09-01 至 2021-09-16
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10005158
• 关键词: Address; Agammaglobulinaemia tyrosine kinase; Animals; B-Lymphocytes; BCL2 gene; Blood; CRISPR/Cas technology; Cell Line; Cells; Cessation of life; Chronic Lymphocytic Leukemia; Clinical; Clinical Management; Clinical Trials; Clonal Evolution; Clustered Regularly Interspaced Short Palindromic Repeats; Combination Drug Therapy; Cyclophosphamide; DNA sequencing; Data; Data Set; Death Rate; Detection; Development; Disease; Disease Progression; Dissection; Epigenetic Process; Evolution; Exposure to; Genetic; Genetic Heterogeneity; Genome; Genomics; Genotype; Goals; Growth; Immunodeficient Mouse; Immunotherapy; In Vitro; Individual; Kinetics; Knowledge; Lesion; Leukemic Cell; Malignant - descriptor; Malignant Neoplasms; Maps; Mature B-Lymphocyte; Measurement; Measures; Methods; Modeling; Molecular; Mus; Mutate; Mutation; Nature; Pathway interactions; Patient-Focused Outcomes; Patients; Pattern; Phenotype; Population; Process; Receptor Signaling; Receptors, Antigen, B-Cell; Relapse; Resistance; Resistance development; Sampling; Series; Signal Transduction; Specimen; System; Technology; Testing; Therapeutic; Therapeutic Agents; Time; anti-PD1 antibodies; base; cancer cell; cancer heterogeneity; cancer therapy; chemotherapy; cohort; curative treatments; design; droplet sequencing; exome; fitness; fludarabine; genetic profiling; genome editing; genome-wide; genomic locus; improved; in vivo; in vivo Model; individual patient; inhibitor/antagonist; leukemia; mathematical model; next generation sequencing; novel; novel therapeutics; personalized medicine; phenome; resistance gene; resistance mechanism; resistance mutation; response; rituximab; standard of care; success; targeted agent; therapy development; therapy resistant; tool; transcriptome sequencing; treatment response

Project Summary The ability of cancer cells to evolve and adapt to therapy is a challenge that limits treatment success and durability of responses. This is certainly the case in chronic lymphocytic leukemia (CLL), a malignancy of mature B cells that remains incurable, despite the potent cytolytic effects of both existing standard-of-care fludarabine-based combination chemotherapy, and newly developed targeted inhibitors such as ibrutinib and ABT199. We focus on a series of informative well-characterized clinical cohorts of patients that have relapsed following CLL therapy, ranging from conventional chemotherapy to novel agents (ibrutinib, ABT199, anti-PD1 antibody). Through integrated whole-exome and RNA-sequencing of these cohorts, we will characterize the extent of clonal evolution following exposure to these agents, and identify if there are consistent genetic loci associated with therapeutic resistance or progression (Aim 1). Mathematical modeling together with frequent serial analysis of the clonal composition of leukemias in relationship to treatment response and relapse can inform us regarding the clone-specific decline/growth kinetics as they occur in individual patients, and thereby enable dissection of the mechanisms of relapse or progression. Through this process, we will further estimate the sizes of clones with rare resistance mutations at the start of treatment; understand whether distinct relapse- associated genetic lesions result in accelerated clonal growth, or rather, in insensitivity to therapy; and validate the size of the resistant population in the starting population using novel single cell droplet sequencing technology (Aim 2). Finally, we will use CRISPR/Cas technology to model the novel resistance mutations in B cell lines and introduce these lines in combination with other mutated cell lines both in vitro and in vivo into immunodeficient mice, in order to test their fitness both prior to and during therapy (Aim 3). Altogether, the proposed analyses serve to provide an analytic framework for gaining vital information regarding the fitness of different genetic lesions with and without therapy, which may be immensely beneficial to the design of the next generation of therapeutic approaches to overcome the evolutionary capacity of cancer.

项目摘要 癌细胞进化和适应治疗的能力是限制治疗成功和 回答的耐久性。慢性淋巴细胞白血病(CLL)就是这种情况，它是一种 成熟的B细胞仍然无法治愈，尽管现有的标准护理措施具有强大的细胞溶解作用 以氟达拉滨为基础的联合化疗，以及新开发的靶向抑制剂，如伊布鲁替尼和 ABT199。我们专注于一系列信息丰富、特征明确的复发患者的临床队列。 CLL治疗后，从常规化疗到新药(伊布鲁替尼、ABT199、抗PD1) 抗体)。通过整合整个外显子组和这些队列的RNA测序，我们将表征 暴露于这些制剂后的克隆进化程度，并确定是否存在一致的遗传位点 与治疗抵抗或进展有关(目标1)。数学建模与频繁化 白血病克隆性成分与治疗反应和复发关系的系列分析 告知我们在个别患者中发生的克隆特异性下降/生长动力学，从而 使人们能够剖析复发或进展的机制。通过这一过程，我们将进一步估计 治疗开始时具有罕见耐药突变的克隆的大小；了解明显的复发- 相关的遗传损伤导致克隆生长加速，或者更确切地说，导致对治疗不敏感；并验证 用新的单细胞液滴测序法测定起始种群中抗性种群的大小 技术(目标2)。最后，我们将使用CRISPR/CAS技术来模拟B 并将这些细胞系与其他体外和体内突变的细胞系相结合，导入 免疫缺陷小鼠，以测试其在治疗前和治疗期间的健康状况(目标3)。总而言之， 建议的分析提供了一个分析框架，用于获得关于以下方面的重要信息 不同的基因损伤有没有治疗，这可能对下一步的设计非常有益 产生治疗方法，以克服癌症的进化能力。