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Record W4392543343 · doi:10.1182/blood.2023022589

Vector integration and fate in the hemophilia dog liver multiple years after AAV-FVIII gene transfer

2024· article· en· W4392543343 on OpenAlexaff
Paul Batty, Sylvia Fong, Matteo Franco, Choong‐Ryoul Sihn, Laura L. Swystun, Saira Afzal, L. Harpell, David Hurlbut, Abbey Pender, Cheng Su, Hauke Thomsen, Christopher Wilson, Loubna Youssar, Andrew Winterborn, Irene Gil-Fariña, David Lillicrap

Bibliographic record

VenueBlood · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicVirus-based gene therapy research
Canadian institutionsQueen's University
FundersBioMarin PharmaceuticalCSL BehringNovo NordiskSanofiPfizer
KeywordsGene transferVector (molecular biology)VirologyMedicineBiologyImmunologyGeneRecombinant DNAGenetics

Abstract

fetched live from OpenAlex

ABSTRACT: Gene therapy using adeno-associated virus (AAV) vectors is a promising approach for the treatment of monogenic disorders. Long-term multiyear transgene expression has been demonstrated in animal models and clinical studies. Nevertheless, uncertainties remain concerning the nature of AAV vector persistence and whether there is a potential for genotoxicity. Here, we describe the mechanisms of AAV vector persistence in the liver of a severe hemophilia A dog model (male = 4, hemizygous; and female = 4, homozygous), more than a decade after portal vein delivery. The predominant vector form was nonintegrated episomal structures with levels correlating with long-term transgene expression. Random integration was seen in all samples (median frequency, 9.3e-4 sites per cell), with small numbers of nonrandom common integration sites associated with open chromatin. No full-length integrated vectors were found, supporting predominant episomal vector-mediated long-term transgene expression. Despite integration, this was not associated with oncogene upregulation or histopathological evidence of tumorigenesis. These findings support the long-term safety of this therapeutic modality.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.275

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.258
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations25
Published2024
Admission routes1
Has abstractyes

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