Understanding and predicting relapse in acute myeloid leukemia

项目摘要/摘要 复发仍然是白血病治愈的主要障碍。为什么一些患者复发，而另一些患者被治愈？ 预测反应的能力，以及在坦率复发之前使用替代疗法进行干预的能力，可以 潜在地优化治疗，并潜在地改变特定患者疾病的自然病史。我们会 以急性髓系白血病为模型疾病展示可测量残留病(MRD)检测的能力 基因表达特征在预测治疗反应中的作用。对于这些研究，我们将使用档案和 来自美国组间研究的预期样本，以便我们可以准确地将基因变化与 临床特点和转归。在目标1中，我们将开发和测试一种新的测序方法--双链测序 测序，可以在一百万个野生动物的背景中以一个突变等位基因的频率检测突变 等位基因类型。在目标2中，我们将测试三个基因表达特征在预测短期和长期- 长期治疗应答，并发现应答组中可能成为未来靶点的不同途径 药物治疗。在目标3中，我们将把上述基因测试应用于异基因移植环境，以预测 非清髓性移植后复发(因此，直接流产治疗)。我们实验室已经有了 在慢性粒细胞白血病和ALL中使用类似工具相当成功，实际上，在这些疾病中检测MRD具有 在临床试验中演变成结果的替代品。我们同样相信，在反洗钱中，这些目标最终将 允许我们在治疗前预测结果，根据导致预测结果的可能途径选择治疗方案 不良反应，然后监测MRD，如果MRD清除动力学为 不太理想。

PROJECT SUMMARY/ABSTRACT Relapse remains the major obstacle to cure in leukemia. Why do some patients relapse, while others are cured? The ability to predict response, and intervene with alternative therapies before frank relapse occurs, can potentially optimize therapy, and potentially change the natural history of a particular patient’s disease. We will use AML as a model disease to demonstrate the power of the detection of measurable residual disease (MRD) and gene expression signatures in predicting treatment response. For these studies we will use archival and prospective samples from U.S. Intergroup studies so that we can accurately associate genetic changes with clinical characteristics and outcomes. In Aim 1 we will develop and test a new sequencing method, duplex sequencing, which can detect a mutation at a frequency of one mutant allele in a background of a million wild type alleles. In Aim 2, we will test three gene expression signatures head to head in predicting short and long- term treatment response, and discover pathways different in the response groups that may be future targets of drug therapy. In Aim 3, we will apply the above genetic tests to the allogeneic transplant setting, to predict relapse following non-myeloablative transplantation (and hence, direct abortive therapy). Our lab has had considerable success in using similar tools in CML and ALL, and indeed, MRD detection in these diseases have evolved to a surrogate for outcome in clinical trials. We likewise believe that in AML these aims will eventually allow us to predict outcome prior to therapy, pick therapies based on likely pathways responsible for the predicted unfavorable response, then monitor MRD, changing therapy early if the kinetics of MRD clearance are suboptimal.