Mesenchymal Stromal Cells Gene-Enhanced To Express Human Factor IX and Their In Vivo Use for Correction of Hemophilia B Phenotype in R333Q Mice.
Bibliographic record
Abstract
Abstract Hemophilia B is considered an appropriate disease target for gene therapy because it is a well characterized monogenic disease with a large therapeutic index. Despite promising preclinical and clinical trials in the last decade, safety and efficacy concerns associated with the in vivo administration of viral vectors still need to be addressed before gene therapy becomes part of the standard arsenal for clinicians. Our laboratory has developed a cell therapy approach using gene-enhanced autologous Mesenchymal Stromal Cells (MSCs) to deliver a therapeutic plasmatic protein which addresses these safety concerns. In this study, we tested whether MSCs engineered to express human Factor IX (hFIX) can be used to reverse the bleeding phenotype of R333Q hemophilia B mice developed by Stafford et al. We retrovirally engineered MSCs harvested from normal C57Bl/6 to express hFIX. A gene enhanced polyclonal population of MSCs was capable of producing carboxylated and fully active hFIX by in vitro clotting assays. By ELISA, the cells were shown to produce approximately 250ng of hFIX per million cells per 24h. Ten million of these cells were embedded in a collagen I gel matrix and implanted subcutaneously in R333Q hemophilia B mice (n=10). hFIX activity in mouse plasma (test and control groups) were followed weekly by aPTT assays. hFIX activity reached levels as high as 20% normal activity in some animals with an average +/− SEM of 11.2 +/− 2.1 (FIX activity in controls is <1%). The hFIX activity returned to baseline within 4 weeks. In conclusion, we demonstrate that gene-enhanced autologous MSCs can serve as an effective delivery of functional FIX for temporary correction of the hemophilia B phenotype. We hypothesize the presence of GFP co-expression by the implanted MSCs caused their immune rejection and we are currently testing this hypothesis.
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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 | 0.001 | 0.001 |
| 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".