Analyzing the Number of Common Integration Sites of Viral Vectors – New Methods and Computer Programs

Vectors based on γ-retroviruses or lentiviruses have been shown to stably express therapeutical transgenes and effectively cure different hematological diseases. Molecular follow up of the insertional repertoire of gene corrected cells in patients and preclinical animal models revealed different integration preferences in the host genome including clusters of integrations in small genomic areas (CIS; common integrations sites). In the majority, these CIS were found in or near genes, with the potential to influence the clonal fate of the affected cell. To determine whether the observed degree of clustering is statistically compatible with an assumed standard model of spatial distribution of integrants, we have developed various methods and computer programs for γ-retroviral and lentiviral integration site distribution. In particular, we have devised and implemented mathematical and statistical approaches for comparing two experimental samples with different numbers of integration sites with respect to the propensity to form CIS as well as for the analysis of coincidences of integration sites obtained from different blood compartments. The programs and statistical tools described here are available as workspaces in R code and allow the fast detection of excessive clustering of integration sites from any retrovirally transduced sample and thus contribute to the assessment of potential treatment-related risks in preclinical and clinical retroviral gene therapy studies.

基于γ-逆转录病毒（γ-retrovirus）或慢病毒（lentivirus）的载体已被证实可稳定表达治疗性转基因，并有效治愈多种血液系统疾病。对患者及临床前动物模型中基因校正细胞的整合位点谱进行分子追踪后，研究人员揭示宿主基因组存在多种整合偏好性，其中包括在小基因组区域内形成的整合簇——常见整合位点（common integrations sites，简称CIS）。大多数情况下，这类常见整合位点位于基因内部或基因邻近区域，有可能影响受影响细胞的克隆命运。为探明观测到的整合簇程度是否与假设的整合子空间分布标准模型在统计学上相符，我们针对γ-逆转录病毒及慢病毒的整合位点分布开发了多种方法与计算机程序。具体而言，我们设计并实现了数学与统计学方法，可用于比较两组具有不同整合位点数量的实验样本在形成常见整合位点方面的倾向，同时也可用于分析从不同血液亚室中获取的整合位点的重合情况。本文所述的程序与统计工具以R语言代码工作区的形式提供，可快速检测任意逆转录病毒转导样本中整合位点的过度聚集情况，从而有助于评估临床前及临床阶段逆转录病毒基因治疗研究中潜在的治疗相关风险。