Integration in Gene Therapy: How to Model Integration Events Distribution

Genetic therapy represents a form of molecular medicine which has the potential to handlethe most severe genetic diseases by replacing a defective gene responsible for the pathology with afunctional one. The basic concept of gene therapy is simple: introduce a piece of genetic material intocells via a viral vector. The virus integrates with the cell DNA and thus delivers the genetic materialinto the cell nucleus. In the past literature (see Hematti et al, 2004; Wu et al., 2003) the integrationevents of retrovirus were believed to be random and the chance of accidentally activating a gene wasconsidered remote. Recently it has suspected that if the virus integrates in certain gene regions (close tothe starting point of the transcription), deregulation of the gene transcription may induce cancer. Thisprocess is called “insertional mutagenesis”. It is therefore clear that understanding “where” and “how”the retrovirus integrates in the genome becomes crucial in evaluating gene therapy. In this presentationwe provide a new statistical approach to the problem of evaluation of “integration events” position.We search for a precise statistical definition of the hypothesis of “random distribution” of integrationand for the alternative hypothesis. Then we model the exact distribution of the integration distance,regardless to gene length by using a Beta distributions. Maximum likelihood estimation method as wellas moments method can then be compared. We show how this is appropriate and how this allows us toevaluate some crucial aspects in these data, such as different gene orientation, different gene length anddifferent gene density areas.