Institute of Computer Science, Department of Systems Biology & Bioinformatics, University of Rostock, Rostock, Germany.
Int J Radiat Biol. 2012 Mar;88(3):267-76. doi: 10.3109/09553002.2012.638358.
A fast, radiation-specific and highly accurate prediction of the radiation dose of accidentally exposed individuals is essential for medical decision-making. The aim of the present study is to identify small gene signatures allowing the discrimination between low and medium dose exposure of low linear energy transfer (LET)-radiation.
We developed a framework for dose prediction using a frequency-based gene selection approach, based on a p-value and fold-change criterion applied to microarray expression data. A repeated cross-validated classification guarantees unbiased performance results. Human blood from six healthy donors was irradiated ex vivo with 0.5, 1, 2 and 4 Gy (Cs-137 γ-rays). Expression levels of isolated blood lymphocytes were measured at 6, 24 and 48 h after irradiation.
We identified radiation-responsive genes, most of them functionally linked to apoptosis, DNA-damage or cell-cycle regulation. We extracted small subsets of genes, with which 95.7% of all samples can be correctly predicted, regardless of the time post irradiation. Seven of these genes were used for validation by Quantitative Real-Time Polymerase Chain Reaction (qRT-PCR).
The genes identified are potential robust biomarkers, which are particularly suitable for dose level discrimination at a window of time that would be appropriate for life-saving medical triage.
对于医疗决策而言，快速、针对辐射且能高度准确地预测偶然暴露于辐射下的个体的辐射剂量至关重要。本研究旨在确定能够区分低线性能量转移（LET）辐射的低剂量和中剂量暴露的小基因特征。
我们使用基于频率的基因选择方法开发了一种剂量预测框架，该方法基于应用于微阵列表达数据的 p 值和倍数变化标准。重复交叉验证分类保证了无偏的性能结果。从六名健康供体中离体采集血液，并用 0.5、1、2 和 4 Gy（Cs-137 γ 射线）辐照。在辐照后 6、24 和 48 小时测量分离的血淋巴细胞的表达水平。
我们鉴定了辐射反应基因，其中大多数与细胞凋亡、DNA 损伤或细胞周期调控功能相关。我们提取了小部分基因，这些基因可以正确预测所有样本的 95.7%，而不管辐照后的时间如何。其中 7 个基因用于通过定量实时聚合酶链反应（qRT-PCR）进行验证。
所鉴定的基因是潜在的稳健生物标志物，它们特别适合在适合拯救生命的医疗分诊的时间窗口中进行剂量水平区分。
