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Molecular Therapy: Methods & Clinical Development
Article . 2015 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
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PubMed Central
Article . 2015
License: CC BY NC ND
Data sources: PubMed Central
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High-throughput monitoring of integration site clonality in preclinical and clinical gene therapy studies

Authors: Frank A Giordano; Jens-Uwe Appelt; Barbara Link; Sebastian Gerdes; Christina Lehrer; Simone Scholz; Anna Paruzynski; +7 Authors

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

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.

Keywords

QH573-671, Genetics, QH426-470, Cytology, Article

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    12
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
12
Top 10%
Average
Average
Green
gold