Massively Parallel Analysis of Integration in Therapeutic Gene Transfer

描述(申请人提供)：通过治疗性基因转移治疗遗传病，通常需要将治疗性基因整合到宿主细胞的染色体中。然而，这导致了接受SCID-X1基因治疗的患者的临床不良事件，在这些患者中，逆转录病毒载体的整合激活了细胞原癌基因，导致了基因校正细胞的转化。因此，基因治疗界已经非常关注基因转移载体在人类基因组中的整合位置的问题。FDA甚至要求对整合部位进行分析，作为监测可能的不良事件的一个步骤。布什曼实验室已经建立了一套独特的技术，用于基于DNA条码、焦磷酸测序和定制的生物信息工具来分析整合位点种群。使用这些高通量方法，整合位点序列的群体可以在一天的运行中产生多达105个碱基的序列。在一项已发表的研究中，我们生成并分析了40,000个HIV DNA整合到人类基因组中的独特位置。在这里，我们建议将这些方法应用于来自法国SCID-X1试验的患者的系统分析。我们已经开始对一些法国SCID-X1患者的纵向DNA样本进行大规模平行测序研究，目的是了解转导细胞的进化、生态和最终命运。到目前为止，我们已经从80例患者样本中产生了约12.8万个整合位点序列读数，总共有~3300万个碱基的DNA序列。第一次，我们可以开始估计对基因校正的细胞库做出贡献的转导细胞克隆的数量。我们可以问，基因校正细胞的数量是如何随着时间的推移而变化的。在初步研究中，我们发现两名研究最深入的患者的克隆多样性出现了令人不安的下降，这表明克隆已经耗尽。我们可以问，即使在没有临床不良事件的情况下，参与生长控制的基因的插入激活是否会导致克隆的生长。对于那些发生不良事件并随后接受化疗的患者，我们将询问化疗如何影响经基因校正的细胞池的大小、多样性和动态。我们还将分析动物模型中的不良事件，以及新临床试验中产生的整合部位。我们建议与法国SCID-X1团队密切合作，以完成以下具体目标：目的1.确定SCID-X1患者样本中存在的整合位点总数。目的2.确定SCID-X1患者整合位点的数量和分布是如何随时间变化的。目的3.在临床前模型和新的临床试验中确定整合位点的位置及其与遗传毒性的关系。 公共卫生相关性：人类对SCID-X1的基因治疗已取得成功，但原癌基因插入激活和白血病引起的不良事件已造成严重挫折。在这里，我们建议将大规模并行焦磷酸测序应用于分析历史性的SCID-X1试验样本中的载体整合。

DESCRIPTION (provided by applicant): To treat genetic diseases by therapeutic gene transfer, it is usually necessary to integrated the therapeutic gene into a chromosome of the host cell. However, this has led to clinical adverse events in patients receiving gene therapy for SCID-X1, in which integration of retroviral vectors activated cellular proto-oncogenes, leading to transformation of gene-corrected cells. Thus the gene therapy community has become intensely focused on the question of where gene transfer vectors integrate in the human genome. The FDA has even mandated that integration sites be analyzed as a step in monitoring for possible adverse events. The Bushman laboratory has established a unique collection of technologies for analyzing integration site populations based on DNA bar coding, pyrosequencing, and custom bioinformatic tools. Using these high throughput methods, populations of integration site sequences can be generated of up to 105 bases of sequence in a single one day run. In one published study, we generated and analyzed the placement of 40,000 unique sites of HIV DNA integration in the human genome. Here we propose to apply these methods to systematic analysis of patients from the French SCID-X1 trial. We have initiated massively parallel sequencing studies of longitudinal DNA samples from some of the French SCID-X1 patients, with the goal of understanding the evolution, ecology, and ultimate fate of transduced cells. So far, we have generated ~128,000 integration site sequence reads from 80 patient samples for a total of ~33,000,000 bases of DNA sequence. For the first time, we can begin to estimate the numbers of transduced cell clones contributing to the gene-corrected cell pool. We can ask how populations of gene corrected cells change over time. In preliminary studies, we find a troubling decline in clone diversity in our two best-studied patients, suggesting "clone burn out". We can ask whether insertional activation of genes involved in growth control leads to outgrowth of clones even in the absence of clinical adverse events. For those patients who suffered adverse events and were subsequently treated by chemotherapy, we will ask how the chemotherapeutic treatment affected the size, diversity and dynamics of the gene-corrected cell pools. We will also analyze adverse events in animal models and, longer term, integration sites generated in new clinical trials. We propose to work in close collaboration with the French SCID-X1 team to complete the following Specific Aims: Aim 1. Determine the total numbers of integration sites present in samples from SCID-X1 patients. Aim 2. Determine how the number and distribution of integration sites changes over time in SCID-X1 patients. Aim 3. Determine integration site locations and relationship to genotoxicity in preclinical models and new clinical trials. PUBLIC HEALTH RELEVANCE: Success has been achieved with human gene therapy for SCID-X1, but adverse events due to insertional activation of proto-oncogenes and leukemia have caused severe setbacks. Here we propose to apply massively parallel pyrosequencing to analyzing vector integration in samples from the historic SCID-X1 trial.