Radiation Biodosimetry Using Gene Expression Signatures

到目前为止，我们的研究已经为应用基因表达生物剂量学奠定了基础，重点是 全身高剂量率体外光子曝光的标志性开发。其他类型的辐射 暴露，包括部分身体暴露、内部发射体、低剂量率和中子暴露，也将 影响分诊需求，并可能产生不同的响应，或者已经在剂量学签名中产生变化 已确认身份。由于对剂量的估计只提供了预期的辐射损伤的大致概念 对于人口，开发签名也将是重要的，这些签名可以提供更准确的预测 以个人为基础的辐射损伤反应和结果。 项目2将使用功能基因组学方法来开发精炼的基因表达签名 辐射暴露和剂量涉及两个主要的更新主题：第一，不同辐射的影响 方式(部分身体照射、内部发射体、低剂量率和中子照射)，第二， 个体辐射敏感性的预测。基因芯片分析将应用于人类和小鼠 基于我们在这笔赠款的第一个资助期开发的预测性签名的样本 并更好地使它们适应现实的辐射暴露情景。鼠标模型还将用于 研究预测辐射剂量和辐射剂量的基因表达特征的机制基础 敏感度。 项目2将通过辐射核心(核心C)与项目1和项目3紧密结合 信息学核心(核心E)，并通过使用人类血液辐照前的样本共享方法 活体和活体照射小鼠。这种样本共享方法还将有助于通过 涵盖所有三个项目的综合分析方法的信息学核心，并使用来自 MicroRNA、信使核糖核酸、代谢和细胞水平。这种综合方法将有助于提供 对转录组和代谢组签名基础的机械论洞察，以及 建议将高通量生物剂量测定的最佳组合应用于特定的实际情况 场景。

Our studies to date have laid the groundwork for applied gene expression biodosimetry, focusing on signature development for whole-body high dose rate external photon exposure. Other types of radiation exposures, including partial-body exposure, internal emitters, low dose rate, and neutron exposure, will also impact triage needs, and may produce distinct responses, or variations in the dosimetric signatures already identified. As estimates of dose provide only a general idea ofthe radiation injury expected across a population, it will also be important to develop signatures that may provide a more accurate prediction of radiation injury response and outcome on an individual basis. Project 2 will use a functional genomics approach to develop refined gene expression signatures of radiation exposure and dose addressing the two main renewal themes: first, the impact of different radiation modalities (partial-body exposure, internal emitters, low dose rate, and neutron exposure), and second, prediction of individual radiation sensitivity. Microarray analysis will be applied to human and murine samples to build upon the predictive signatures we have developed in the first funding period of this grant and to better adapt them to realistic radiation exposure scenarios. Mouse models will also be used to nvestigate the mechanistic underpinnings ofthe gene expression signatures that predict radiation dose and sensitivity. Project 2 will be tightly integrated with Projects 1 and 3 through the Irradiation Core (Core C), the Informatics Core (Core E), and through a sample sharing approach using both human blood irradiated ex vivo and in vivo irradiated mice. This sample sharing approach will also help to enable development by the Informatics Core of integrative analysis approaches spanning all three Projects and using data from the microRNA, mRNA, metabolomic, and cellular levels. Such an integrative approach will help provide mechanistic insight into the underpinnings of both transcriptomic and metabolomic signatures, as well as suggesting the best combinations of high-throughput biodosimetry assays to apply in specific practical scenarios.