Lentiviral Transfer of γ-Globin with Fusion Gene NUP98-HOXA10HD Expands Hematopoietic Stem Cells and Ameliorates Murine β-Thalassemia
Bibliographic record
Abstract
Recently, an engineered Homeobox-nucleoporin fusion gene, NUP98-HOXA10HD or NA10HD, was reported to expand and maintain murine hematopoietic stem cells (HSCs). We postulated that NA10HD would increase the number of human γ-globin-expressing cells to therapeutic levels. We developed a double gene lentiviral vector encoding both human γ-globin and NA10HD, which was used to transduce human peripheral blood CD34 + cells and increased engraftment 2- to 2.5-fold at 15 weeks post-transplantation in immunodeficient mice. In β-thalassemic mice transplanted with β-thalassemic HSCs transduced with the γ-globin/NA10HD vector, the number of fetal hemoglobin (HbF)-expressing cells was significantly increased after 3 months, leading to resolution of the anemia. Furthermore, the increases in HbF were maintained at 6 months and persisted after secondary transplantation. In addition, NA10HD enrichment of transduced HSCs led to HbF increases without affecting homeostasis of the white blood cell lineages. Our results suggest that NA10HD increases the number of γ-globin-transduced HSCs that engraft, leading to an elevated number of fetal hemoglobin-containing red cells. These effects of NA10HD provide an improved platform for testing of the therapeutic efficacy of novel globin vectors and provide further impetus to develop safe and effective methods for selective expansion of genetically modified cells.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".