Translating genomic discoveries to improved outcomes for high risk acute leukemia

摘要 急性淋巴细胞白血病（ALL）是儿童癌症死亡的主要原因。我研究的目的是 使用整合的基因组和表观基因组分析来定义基因组改变， 白血病发生和治疗失败的ALL，并利用这些信息来开发小鼠模型， 将这些发现转化为创新的治疗方法。我的研究计划已经修正了分子 ALL的分类，确定了定义ALL亚型的基因突变星座，已经解剖了 克隆进化的遗传基础，确定了治疗干预的新靶点，特别是酪氨酸激酶 抑制剂，并建立了几个新的高风险B祖细胞ALL的工程模型。最近 这些进展包括确定ALL复发时表观遗传调节因子的高频率突变， 这表明特定的基因组改变扰乱了白血病细胞与肿瘤细胞的相互作用， 微环境，导致对治疗的抵抗。这项研究计划将确定 诊断时存在的遗传病变或复发时富集的遗传病变决定对治疗的抗性的基础， 并将其用于治疗干预。研究目标是：（1）确定基因组的星座， 和表观基因组改变，这些改变表征了整个年龄谱中ALL的每种亚型， 这些改变会导致治疗失败。这涉及基因组和转录组测序， 儿童和成人ALL，以及整合的全基因组、全基因组亚硫酸氢盐、转录组和染色质 对100例ALL病例的队列进行标记测序，包括诊断和复发时获得的匹配样本 和相应的异种移植物。这对于识别所有驱动疾病的编码和非编码突变至关重要， 系统地检查遗传改变对染色质重塑的影响，并指导 ALL小鼠模型的开发和解释。(2)执行多路复用功能丧失筛查 利用发现致癌融合的表达，加上RNA干扰和基因组编辑， 白血病发生中多基因变异的相互作用。(3)使用基因特异性和功能丧失 筛查以检查表观基因组改变在ALL复发中的作用。其中包括详细的特征描述 Crebbp敲入ALL模型，以及靶向超过700种染色质修饰剂的RNAi/CRISPR/Cas9筛选 B-ALL白血病模型中的基因。富集命中，以及它们对染色质建模和转录的影响 调控将与来自人类白血病细胞的数据进行比较;并将由此产生的模型用于测试效果 表观遗传修饰剂对调节耐药性的作用。(4)使用B-ALL小鼠模型解剖 细胞错误定位和“劫持”骨髓小生境的作用，以及这种现象在 耐药性总之，这些方法提供了一个全面的战略，以充分界定基因组 在ALL中驱动治疗失败的改变，并在逻辑实验中机械地验证这些改变， 指导进一步药物开发方法的系统。

ABSTRACT Acute lymphoblastic leukemia (ALL) is a leading cause of cancer death in children. The goal of my research is to use integrated genomic and epigenomic profiling to define the genomic alterations that drive leukemogenesis and treatment failure in ALL, and to use this information to develop mouse models to translate these discoveries to innovative therapeutic approaches. My research program has revised the molecular taxonomy of ALL, identified constellations of genetic mutations that define subtypes of ALL, has dissected the genetic basis of clonal evolution, identified new targets for therapeutic intervention, notably with tyrosine kinase inhibitors, and has established several new engineered models of high-risk B-progenitor ALL. Recent advances include identification of a high frequency of mutations in epigenetic regulators at relapse in ALL, and demonstrating that specific genomic alterations perturb the interaction of leukemic cells with the microenvironment, resulting in resistance to therapy. This research proposal will determine the mechanistic basis by which genetic lesions present at diagnosis, or enriched at relapse, determine resistance to therapy, and exploit these for therapeutic intervention. Research goals are (1) to identify the constellations of genomic and epigenomic alterations that characterize each subtype of ALL across the age spectrum, and identifying those alterations that cause treatment failure. This involves genome and transcriptome sequencing of childhood and adult ALL, and integrated whole genome, whole genome bisulfite, transcriptome and chromatin mark sequencing of a cohort of 100 ALL cases, including matched samples obtained at diagnosis and relapse and corresponding xenografts. This is essential to identify all coding and non-coding mutations driving disease, to systematically examine the effect of genetic alterations on chromatin remodeling, and to guide the development and interpretation of mouse models of ALL. (2) To perform multiplexed loss-of-function screens using expression of founding oncogenic fusions, coupled with RNA interference and genome editing to dissect the interaction of polygenic alterations in leukemogenesis. (3) To use gene-specific and loss-of-function screens to examine the role of epigenomic alterations in ALL relapse. These include detailed characterization of Crebbp knockin models of ALL, and RNAi/CRISPR/Cas9 screens targeting over 700 chromatin modifier genes in B-ALL leukemia models. Enriched hits, and their effects on chromatin modeling and transcriptional regulation will be compared to data from human leukemic cells; and the resulting models used to test the effect of epigenetic modifying agents on modulating drug resistance. (4) To use mouse models of B-ALL to dissect the role of cellular mislocalization and “hijacking” of the bone marrow niche and the role of this phenomenon in drug resistance. Together, these approaches provide a comprehensive strategy to fully define the genomic alterations driving treatment failure in ALL, and to mechanistically validate these in logical experimental systems to guide further drug development approaches.