Evolutionary Heterogeneity of High Grade Glioma

项目摘要/摘要 癌症是一系列精心策划的基因组改变的结果，这些改变共同推动了 不受控制的细胞生长。将这些变化的时间和空间关联剖析为 不同的时间点将提供启动、进展、转移和/或 对某些治疗方案的抵抗。阐明这些里程碑可以提供无价的 在治疗的不同阶段的背景下的生物标记物，并将有助于定制个性化 基于基因组信息的治疗。我们将开发一个模型来推断可能的排序 通过第一次识别从纵向、多区域、转录和单细胞数据进行改变 重大变更的总数和最有可能使用严格的 基因组学方法。接下来，我们将使用以下方法推断每个患者的潜在进化动作 以进化生物学为基础的统计方法的连续样本。第三，我们会 为患者队列构建一个进化网络，该网络将描述和排序重要的 基因组改变的途径。

PROJECT SUMMARY/ABSTRACT Cancer is the result of an orchestrated set of genomic alterations that conspire to drive uncontrolled cell growth. Dissecting temporal and spatial association of these alterations into varying time points will provide milestones into initiation, progression, metastasis and/or resistance to certain therapeutic regimens. Elucidating these milestones could provide invaluable biomarkers in the context of different stages for treatments and would help to tailor personalized therapies based on genomic information. We will develop a model to infer a possible ordering of alterations from longitudinal, multi-region, transcriptomic and single cell data by first discerning the totality of significant alterations and most likely contributors to progression using a rigorous genomic approach. Next we will infer potential evolutionary moves of each patient using sequential samples with a statistical approach rooted in evolutionary biology. Third we will construct an evolutionary network for the cohort of patients that will delineate and order significant routes of genomic alteration.