Persistence of CRISPR/Cas9 Gene Edited Hematopoietic Stem Cells Following Transplantation: A Systematic Review and Meta-Analysis of Preclinical Studies
Bibliographic record
Abstract
Gene editing blood-derived cells is an attractive approach to cure selected monogenic diseases but remains experimental. A systematic search of preclinical controlled studies is needed to determine the persistence of edited cells following reinfusion. All studies identified in our systematic search (to 20 October 2020) examining the use of CRISPR/Cas9 gene editing in blood-derived cells for transplantation were included. Meta-analysis was performed to determine the engraftment and persistence of gene edited cells. A total of 3538 preclinical studies were identified with 15 published articles meeting eligibility for meta-analysis. These in vivo animal studies examined editing of hemoglobin to correct sickle cell disease (eight studies), inducing resistance to acquired immunodeficiency syndrome (two studies), and six other monogenic disorders (single studies). CRISPR-Cas9 edited hematopoietic stem and progenitor cells demonstrated equivalent early engraftment compared to controls in meta-analysis but persistence of gene-edited cells was reduced at later time points and in secondary transplant recipients. Subgroup analysis in studies targeting the hemoglobin gene revealed a significant reduction in the persistence of gene-edited cells whether homology-directed repair or nonhomologous end-joining were used. No adverse side effects were reported. Significant heterogeneity in study design and outcome reporting was observed and the potential for bias was identified in all studies. CRISPR-Cas9 gene edited cells engraft similarly to unedited hematopoietic cells. Persistence of gene edited cells, however, remains a challenge and improved methods of targeting hematopoietic stem cells are needed. Reducing heterogeneity and potential risk of bias will hasten the development of informative clinical trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.002 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".