High incidence of leukemia in large animals after stem cell gene therapy with a HOXB4-expressing retroviral vector
Bibliographic record
Abstract
Retroviral vector-mediated HSC gene therapy has been used to treat individuals with a number of life-threatening diseases. However, some patients with SCID-X1 developed retroviral vector-mediated leukemia after treatment. The selective growth advantage of gene-modified cells in patients with SCID-X1 suggests that the transgene may have played a role in leukemogenesis. Here we report that 2 of 2 dogs and 1 of 2 macaques developed myeloid leukemia approximately 2 years after being transplanted with cells that overexpressed homeobox B4 (HOXB4) and cells transduced with a control gammaretroviral vector that did not express HOXB4. The leukemic cells had dysregulated expression of oncogenes, a block in myeloid differentiation, and overexpression of HOXB4. HOXB4 knockdown restored differentiation in leukemic cells, suggesting involvement of HOXB4. In contrast, leukemia did not arise from the cells carrying the control gammaretroviral vector. In addition, leukemia did not arise in 5 animals with high-level marking and polyclonal long-term repopulation following transplantation with cells transduced with an identical gammaretrovirus vector backbone expressing methylguanine methyltransferase. These findings, combined with the absence of leukemia in many other large animals transplanted with cells transduced with gammaretroviral vectors expressing genes other than HOXB4, show that HOXB4 overexpression poses a significant risk of leukemogenesis. Our data thus suggest the continued need for caution in genetic manipulation of repopulating cells, particularly when the transgene might impart an intrinsic growth advantage.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".