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    • 3. 发明申请
    • NON-RANDOMNESS IN THE CLUSTERING OR GENOMIC EVENTS DETECTS INSERTIONAL MUTAGENESIS IN CLINICAL GENE THERAPY
    • 聚集或遗传事件中的非随机性检测临床基因治疗中的插入性突变
    • WO2008071682A2
    • 2008-06-19
    • PCT/EP2007/063666
    • 2007-12-11
    • DKFZ DEUTSCHES KREBSFORSCHUNGSZENTRUMRUPRECHT-KARLS-UNIVERSITÄT HEIDELBERGABEL, UlrichVON KALLE, ChristofSCHMIDT, Manfred
    • VON KALLE, ChristofSCHMIDT, Manfred
    • G01N33/50
    • G06F19/24
    • Features such as mutations or structural characteristics can be non-randomly distributed within a genomic DNA. As an example, insertional mutagenesis is of great importance in cancer research, preclinical and clinical retroviral vector gene therapy. Even when detectable side effects of vector integration are absent,the presence of insertions at higher than expected frequency at particular loci, termed common integration sites (CIS), is indicative of a biological of the integration at that site, and indicates a selective advantage of the affected cell clones based on their integration site (IS). So far, only computational simulations could assess whether the distribution of IS or other DNA features was significantly different compared to random. These simulations require extensive computational resources and fixed parameters of CIS definition. Here, we show that statistical inferences on the distribution of IS are possible using mathematical formulae to calculate the expected frequency of insertions based on genome size, number of sampled integration sites and CIS window size. P-values can be calculated based on the Poisson-distribution. Thus, for each individual problem a flexible CIS definition can be applied to most effectively identify non-random IS distribution mathematically. We here show that application of these calculations on clinical trials detect subtle, but substantial biological effects of insertion sites on clonal selection of hematopoiesis in humans.
    • 特征如突变或结构特征可以非随机分布在基因组DNA内。 作为一个例子,插入突变在癌症研究,临床前和临床逆转录病毒载体基因治疗中是非常重要的。 即使不存在可检测到的载体整合的副作用,在特定位点(称为共同整合位点(CIS))高于预期频率的插入的存在表明该位点整合的生物学,并且表明选择性优势 受影响的细胞克隆基于其整合位点(IS)。 到目前为止,只有计算模拟可以评估IS或其他DNA特征的分布是否与随机显着不同。 这些模拟需要广泛的计算资源和CIS定义的固定参数。 在这里,我们显示,使用数学公式可以使用基于基因组大小,抽样积分位点数和CIS窗口大小来计算插入的预期频率的IS分布统计学推断。 P值可以基于泊松分布计算。 因此,对于每个单独的问题,可以应用灵活的CIS定义以最有效地以数学方式识别非随机IS分布。 我们在这里表明,这些计算在临床试验中的应用检测到微小的,但是插入位点的重大生物效应对人造血细胞克隆选择的影响。