Preclinical Testing of the Safety and Tolerability of Lentiviral Vector–Mediated Above-Normal Alpha-L-Iduronidase Expression in Murine and Human Hematopoietic Cells Using Toxicology and Biodistribution Good Laboratory Practice Studies
Bibliographic record
Abstract
In order to support the clinical application of hematopoietic stem cell (HSC) gene therapy for mucopolysaccharidosis I (MPS I), biosafety studies were conducted to assess the toxicity and tumorigenic potential, as well as the biodistribution of HSCs and progenitor cells (HSPCs) transduced with lentiviral vectors (LV) encoding the cDNA of the alpha-iduronidase (IDUA) gene, which is mutated in MPS I patients. To this goal, toxicology and biodistribution studies were conducted, employing Good Laboratory Practice principles. Vector integration site (IS) studies were applied in order to predict adverse consequences of vector gene transfer and to obtain HSC-related information. Overall, the results obtained in these studies provided robust evidence to support the safety and tolerability of high-efficiency LV-mediated gene transfer and above-normal IDUA enzyme expression in both murine and human HSPCs and their in vivo progeny. Taken together, these investigations provide essential safety data to support clinical testing of HSC gene therapy in MPS I patients. These studies also underline criticisms associated with the use of currently available models, and highlight the value of surrogate markers of tumorigenicity that may be further explored in the future. Notably, biological evidence supporting the efficacy of gene therapy on MPS I disease and its feasibility on patients' HSCs were also generated, employing clinical-grade LVs. Finally, the clonal contribution of LV-transduced HSPCs to hematopoiesis along serial transplantation was quantified in a minimum of 200-300 clones, with the different level of repopulating cells in primary recipients being reflected in the secondary.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".