(PQB5) Epigenetic Drivers of Hematopoietic Stem Cell Transformation

描述(由申请人提供)：本申请针对PQB-5：突变或表观遗传学改变发生的顺序如何改变癌症表型或影响靶向治疗的疗效？癌症基因组图谱(TCGA)最近公布的急性髓系白血病(AML)基因组测序数据表明，80%的AML克隆至少包含两个突变，44%的AML克隆包含DNA甲基化相关基因突变，支持表观遗传调控在AML发展中发挥关键作用。目前还完全不清楚这些突变或表观遗传学变化的获得顺序如何影响AML的表型和对靶向治疗的反应。研究直接在人类中获得突变的组合是具有挑战性的，因为有必要对肿瘤进行连续采样，并对肿瘤形成前细胞群体进行前瞻性识别。为了应对这一挑战，我们设计了一个基于体外的建模系统，以准确地描述AML突变的顺序获取的后果。使用这个系统，我们将顺序和组合地诱导DNA甲基化机制中常见的、反复发生的突变(DNMT3A和TET2)以及经常关联的Flt3激活突变(Flt3-ITD)。我们将确定DNMT3A、TET2和Flt3突变的获取顺序如何改变白血病表型，并建立可预测起始突变身份的增强子活性特征。我们将检验我们的假设，即活跃的增强子区域可以作为识别AML启动突变的关键生物标记物，并且这些生物标记物预测对靶向DNA甲基化抑制剂地西他滨(DAC)的反应。我们的结果将直接证明突变的获得顺序(1)改变癌症表型，(2)可以通过表观遗传生物标记物预测，以及(3)是治疗决策的关键因素，从而对癌症研究产生广泛影响。

DESCRIPTION (provided by applicant): This application addresses PQB-5: How does the order in which mutations or epigenetic changes occur alter cancer phenotypes or affect the efficacy of targeted therapies? Recently published genome sequencing data for acute myeloid leukemia (AML) from The Cancer Genome Atlas (TCGA) has demonstrated that >80% of AML clones contain at least two mutations, and 44% include mutations in DNA-methylation-related genes, supporting that epigenetic regulation plays a key role in AML development. It currently remains completely unknown how the order of acquisition of these mutations or epigenetic changes impacts AML phenotype and response to targeted therapy. Studying combinatorial acquisition of mutations directly in humans is challenging due to the necessity of sequential sampling of tumors and prospective identification of pre-tumorigenic cell populations. To meet this challenge, we have devised an in vitro-based modeling system to accurately depict the consequences of sequential acquisition of mutations in AML. Using this system, we will sequentially and combinatorially induce common, recurrent mutations in the DNA methylation machinery (DNMT3A and TET2) and a frequently associated activating mutation in FLT3 (FLT3-ITD). We will determine how the order of acquisition of mutations in DNMT3A, TET2 and FLT3 alters leukemia phenotype, and establish signatures of enhancer activity that are predictive of the identity of the initiating mutation. We will test our hypothesis that active enhancer regions can serve as key biomarkers for the identification of initiating mutations in AML and that these predict response to the targeted DNA methylation inhibitor decitabine (DAC). Our results will have broad impact on cancer research by direct demonstration that the order of acquisition of mutations (1) alters cancer phenotype, (2) can be predicted by epigenetic biomarkers, and (3) is a key factor for therapeutic decisions.