Development of an Effective, Durable, and Safe Lentiviral Gene Therapy in a Mouse Model of Purine Nucleoside Phosphorylase Deficiency
Bibliographic record
Abstract
Deficiency of the purine nucleoside phosphorylase (PNP) enzyme results in an inherited immune defect with impaired purine metabolism and a severe T cell deficiency. While allogeneic hematopoietic stem cell (HSC) transplantations can correct the immune deficiency, the associated complications are significant. We have developed a novel autologous gene therapy approach for ex vivo delivery of the PNP gene to HSCs using a third-generation self-inactivating lentiviral vector expressing a codon-optimized human PNP gene under the control of the elongation factor- 1 alpha short promoter (LVV-EFS-PNP).In vitro, lineage negative (lin-) cells from Pnp-deficient (-/-) mice transduced with LVV-EFS-PNP demonstrated effective gene transfer, with a dose-dependent increase in vector copy number (VCN) and PNP enzyme activity, without jeopardizing hematopoietic colony formation. In vivo, sublethally irradiated Pnp-/- mice were transplanted with lin- cells transduced with LVV-EFS- PNP. Donor chimerism of at least 10% and VCN of 0.1 in the bone marrow led to sustained correction of the metabolic abnormalities including urinary uric acid production and enzyme activity in primary and secondary lymphoid tissues. Twenty-four weeks after transplant with LVV- EFS-PNP transduced lin- cells, Pnp-/- mice demonstrated restored thymocyte development, T cell proliferation, and T cell-dependent and independent antibody responses, comparable to levels in healthy PNP-proficient (Pnp+/-) littermates. Importantly, in vitro genotoxicity assessments demonstrated that LVV-EFS-PNP had a low frequency of integration near oncogenes, and a low transformation potential, similar to other clinically used lentiviral-based gene therapies. These results demonstrate the safety and efficacy of autologous gene therapy using LVV-EFS-PNP, offering a promising gene therapy for PNP deficiency.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".