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Coherence analysis discriminates between retroviral integration patterns in CD34(+) cells transduced under differing clinical trial conditions
Unequivocal demonstration of the therapeutic utility of γ-retroviral vectors for gene therapy applications targeting the hematopoietic system was accompanied by instances of insertional mutagenesis. These events stimulated the ongoing development of putatively safer integrating vector systems and an...
Autores principales: | , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4445430/ https://www.ncbi.nlm.nih.gov/pubmed/26029726 http://dx.doi.org/10.1038/mtm.2015.15 |
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author | Hallwirth, Claus V Garg, Gagan Peters, Timothy J Kramer, Belinda A Malani, Nirav V Hyman, Jessica Ruan, Xiaoan Ginn, Samantha L Hetherington, Nicola A Veeravalli, Lavanya Shahab, Atif Ranganathan, Shoba Wei, Chia-Lin Liddle, Christopher Thrasher, Adrian J Bushman, Frederic D Buckley, Michael J Alexander, Ian E |
author_facet | Hallwirth, Claus V Garg, Gagan Peters, Timothy J Kramer, Belinda A Malani, Nirav V Hyman, Jessica Ruan, Xiaoan Ginn, Samantha L Hetherington, Nicola A Veeravalli, Lavanya Shahab, Atif Ranganathan, Shoba Wei, Chia-Lin Liddle, Christopher Thrasher, Adrian J Bushman, Frederic D Buckley, Michael J Alexander, Ian E |
author_sort | Hallwirth, Claus V |
collection | PubMed |
description | Unequivocal demonstration of the therapeutic utility of γ-retroviral vectors for gene therapy applications targeting the hematopoietic system was accompanied by instances of insertional mutagenesis. These events stimulated the ongoing development of putatively safer integrating vector systems and analysis methods to characterize and compare integration site (IS) biosafety profiles. Continuing advances in next-generation sequencing technologies are driving the generation of ever-more complex IS datasets. Available bioinformatic tools to compare such datasets focus on the association of integration sites (ISs) with selected genomic and epigenetic features, and the choice of these features determines the ability to discriminate between datasets. We describe the scalable application of point-process coherence analysis (CA) to compare patterns produced by vector ISs across genomic intervals, uncoupled from association with genomic features. To explore the utility of CA in the context of an unresolved question, we asked whether the differing transduction conditions used in the initial Paris and London SCID-X1 gene therapy trials result in divergent genome-wide integration profiles. We tested a transduction carried out under each condition, and showed that CA could indeed resolve differences in IS distributions. Existence of these differences was confirmed by the application of established methods to compare integration datasets. |
format | Online Article Text |
id | pubmed-4445430 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-44454302015-05-29 Coherence analysis discriminates between retroviral integration patterns in CD34(+) cells transduced under differing clinical trial conditions Hallwirth, Claus V Garg, Gagan Peters, Timothy J Kramer, Belinda A Malani, Nirav V Hyman, Jessica Ruan, Xiaoan Ginn, Samantha L Hetherington, Nicola A Veeravalli, Lavanya Shahab, Atif Ranganathan, Shoba Wei, Chia-Lin Liddle, Christopher Thrasher, Adrian J Bushman, Frederic D Buckley, Michael J Alexander, Ian E Mol Ther Methods Clin Dev Article Unequivocal demonstration of the therapeutic utility of γ-retroviral vectors for gene therapy applications targeting the hematopoietic system was accompanied by instances of insertional mutagenesis. These events stimulated the ongoing development of putatively safer integrating vector systems and analysis methods to characterize and compare integration site (IS) biosafety profiles. Continuing advances in next-generation sequencing technologies are driving the generation of ever-more complex IS datasets. Available bioinformatic tools to compare such datasets focus on the association of integration sites (ISs) with selected genomic and epigenetic features, and the choice of these features determines the ability to discriminate between datasets. We describe the scalable application of point-process coherence analysis (CA) to compare patterns produced by vector ISs across genomic intervals, uncoupled from association with genomic features. To explore the utility of CA in the context of an unresolved question, we asked whether the differing transduction conditions used in the initial Paris and London SCID-X1 gene therapy trials result in divergent genome-wide integration profiles. We tested a transduction carried out under each condition, and showed that CA could indeed resolve differences in IS distributions. Existence of these differences was confirmed by the application of established methods to compare integration datasets. Nature Publishing Group 2015-04-29 /pmc/articles/PMC4445430/ /pubmed/26029726 http://dx.doi.org/10.1038/mtm.2015.15 Text en Copyright © 2015 American Society of Gene & Cell Therapy http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/ |
spellingShingle | Article Hallwirth, Claus V Garg, Gagan Peters, Timothy J Kramer, Belinda A Malani, Nirav V Hyman, Jessica Ruan, Xiaoan Ginn, Samantha L Hetherington, Nicola A Veeravalli, Lavanya Shahab, Atif Ranganathan, Shoba Wei, Chia-Lin Liddle, Christopher Thrasher, Adrian J Bushman, Frederic D Buckley, Michael J Alexander, Ian E Coherence analysis discriminates between retroviral integration patterns in CD34(+) cells transduced under differing clinical trial conditions |
title | Coherence analysis discriminates between retroviral integration patterns in CD34(+) cells transduced under differing clinical trial conditions |
title_full | Coherence analysis discriminates between retroviral integration patterns in CD34(+) cells transduced under differing clinical trial conditions |
title_fullStr | Coherence analysis discriminates between retroviral integration patterns in CD34(+) cells transduced under differing clinical trial conditions |
title_full_unstemmed | Coherence analysis discriminates between retroviral integration patterns in CD34(+) cells transduced under differing clinical trial conditions |
title_short | Coherence analysis discriminates between retroviral integration patterns in CD34(+) cells transduced under differing clinical trial conditions |
title_sort | coherence analysis discriminates between retroviral integration patterns in cd34(+) cells transduced under differing clinical trial conditions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4445430/ https://www.ncbi.nlm.nih.gov/pubmed/26029726 http://dx.doi.org/10.1038/mtm.2015.15 |
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