Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN 55455, USA.
Nucleic Acids Res. 2012 May;40(9):3822-33. doi: 10.1093/nar/gkr1295. Epub 2012 Jan 12.
Insertional mutagenesis screens in mice are used to identify individual genes that drive tumor formation. In these screens, candidate cancer genes are identified if their genomic location is proximal to a common insertion site (CIS) defined by high rates of transposon or retroviral insertions in a given genomic window. In this article, we describe a new method for defining CISs based on a Poisson distribution, the Poisson Regression Insertion Model, and show that this new method is an improvement over previously described methods. We also describe a modification of the method that can identify pairs and higher orders of co-occurring common insertion sites. We apply these methods to two data sets, one generated in a transposon-based screen for gastrointestinal tract cancer genes and another based on the set of retroviral insertions in the Retroviral Tagged Cancer Gene Database. We show that the new methods identify more relevant candidate genes and candidate gene pairs than found using previous methods. Identification of the biologically relevant set of mutations that occur in a single cell and cause tumor progression will aid in the rational design of single and combinatorial therapies in the upcoming age of personalized cancer therapy.
插入诱变筛选在小鼠中用于鉴定驱动肿瘤形成的个体基因。在这些筛选中，如果候选癌症基因的基因组位置靠近由特定基因组窗口中转座子或逆转录病毒插入率高定义的常见插入位点 (CIS)，则会鉴定出它们。在本文中，我们描述了一种基于泊松分布的新 CIS 定义方法，泊松回归插入模型，并表明这种新方法优于以前描述的方法。我们还描述了该方法的一种改进，可以识别成对和更高阶的共同插入位点。我们将这些方法应用于两个数据集，一个是基于转座子的胃肠道癌基因筛选生成的数据集，另一个是基于逆转录病毒标记癌症基因数据库中的逆转录病毒插入集。我们表明，新方法比使用以前的方法鉴定出更多相关的候选基因和候选基因对。鉴定单个细胞中发生的并导致肿瘤进展的生物学相关突变集将有助于在即将到来的个性化癌症治疗时代合理设计单药和联合治疗。
