Coherence analysis discriminates between retroviral integration patterns in CD34+ cells transduced under differing clinical trial conditions

Claus V. Hallwirth, Gagan Garg, Timothy J. Peters, Belinda A. Kramer, Nirav V. Malani, Jessica Hyman, Xiaoan Ruan, Samantha L. Ginn, Nicola A. Hetherington, Lavanya Veeravalli, Atif Shahab, Shoba Ranganathan, Chia Lin Wei, Christopher Liddle, Adrian J. Thrasher, Frederic D. Bushman, Michael J. Buckley, Ian E. Alexander

Research output: Contribution to journalArticleResearchpeer-review

Abstract

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.

LanguageEnglish
Article number15015
Pages1-10
Number of pages10
JournalMolecular Therapy - Methods and Clinical Development
Volume2
DOIs
Publication statusPublished - 29 Apr 2015

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Clinical Trials
Genetic Therapy
Hematopoietic System
Insertional Mutagenesis
Paris
Systems Analysis
Computational Biology
Epigenomics
Genome
Technology
Datasets
Therapeutics

Bibliographical note

Copyright the Publisher 2015. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Cite this

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. In: Molecular Therapy - Methods and Clinical Development. 2015 ; Vol. 2. pp. 1-10.
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title = "Coherence analysis discriminates between retroviral integration patterns in CD34+ cells transduced under differing clinical trial conditions",
abstract = "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.",
author = "Hallwirth, {Claus V.} and Gagan Garg and Peters, {Timothy J.} and Kramer, {Belinda A.} and Malani, {Nirav V.} and Jessica Hyman and Xiaoan Ruan and Ginn, {Samantha L.} and Hetherington, {Nicola A.} and Lavanya Veeravalli and Atif Shahab and Shoba Ranganathan and Wei, {Chia Lin} and Christopher Liddle and Thrasher, {Adrian J.} and Bushman, {Frederic D.} and Buckley, {Michael J.} and Alexander, {Ian E.}",
note = "Copyright the Publisher 2015. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.",
year = "2015",
month = "4",
day = "29",
doi = "10.1038/mtm.2015.15",
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Hallwirth, CV, Garg, G, Peters, TJ, Kramer, BA, Malani, NV, Hyman, J, Ruan, X, Ginn, SL, Hetherington, NA, Veeravalli, L, Shahab, A, Ranganathan, S, Wei, CL, Liddle, C, Thrasher, AJ, Bushman, FD, Buckley, MJ & Alexander, IE 2015, 'Coherence analysis discriminates between retroviral integration patterns in CD34+ cells transduced under differing clinical trial conditions', Molecular Therapy - Methods and Clinical Development, vol. 2, 15015, pp. 1-10. https://doi.org/10.1038/mtm.2015.15

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.

In: Molecular Therapy - Methods and Clinical Development, Vol. 2, 15015, 29.04.2015, p. 1-10.

Research output: Contribution to journalArticleResearchpeer-review

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T1 - Coherence analysis discriminates between retroviral integration patterns in CD34+ cells transduced under differing clinical trial conditions

AU - Hallwirth, Claus V.

AU - Garg, Gagan

AU - Peters, Timothy J.

AU - Kramer, Belinda A.

AU - Malani, Nirav V.

AU - Hyman, Jessica

AU - Ruan, Xiaoan

AU - Ginn, Samantha L.

AU - Hetherington, Nicola A.

AU - Veeravalli, Lavanya

AU - Shahab, Atif

AU - Ranganathan, Shoba

AU - Wei, Chia Lin

AU - Liddle, Christopher

AU - Thrasher, Adrian J.

AU - Bushman, Frederic D.

AU - Buckley, Michael J.

AU - Alexander, Ian E.

N1 - Copyright the Publisher 2015. Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

PY - 2015/4/29

Y1 - 2015/4/29

N2 - 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.

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