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Mol Ther Methods Clin Dev. 2015 Apr 1;2:14061. doi: 10.1038/mtm.2014.61. eCollection 2015.

High-throughput monitoring of integration site clonality in preclinical and clinical gene therapy studies.

Author information

1
Department of Radiation Oncology, Universitätsmedizin Mannheim, Medical Faculty Mannheim, Heidelberg University , Mannheim, Germany.
2
Department of Translational Oncology, National Center for Tumor Diseases and German Cancer Research Center (DKFZ) , Heidelberg, Germany ; CLC bio , Aarhus, Denmark.
3
Department of Translational Oncology, National Center for Tumor Diseases and German Cancer Research Center (DKFZ) , Heidelberg, Germany.
4
Institute for Medical Informatics and Biometry, Faculty of Medicine Carl Gustav Carus, Technische Universität , Dresden, Germany.
5
Institute for Biomedical Research, Georg-Speyer-Haus , Frankfurt, Germany.

Abstract

Gene transfer to hematopoietic stem cells with integrating vectors not only allows sustained correction of monogenic diseases but also tracking of individual clones in vivo. Quantitative real-time PCR (qPCR) has been shown to be an accurate method to quantify individual stem cell clones, yet due to frequently limited amounts of target material (especially in clinical studies), it is not useful for large-scale analyses. To explore whether vector integration site (IS) recovery techniques may be suitable to describe clonal contributions if combined with next-generation sequencing techniques, we designed artificial ISs of different sizes which were mixed to simulate defined clonal situations in clinical settings. We subjected all mixes to either linear amplification-mediated PCR (LAM-PCR) or nonrestrictive LAM-PCR (nrLAM-PCR), both combined with 454 sequencing. We showed that nrLAM-PCR/454-detected clonality allows estimating qPCR-detected clonality in vitro. We then followed the kinetics of two clones detected in a patient enrolled in a clinical gene therapy trial using both, nrLAM-PCR/454 and qPCR and also saw nrLAM-PCR/454 to correlate to qPCR-measured clonal contributions. The method presented here displays a feasible high-throughput strategy to monitor clonality in clinical gene therapy trials is at hand.

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