The Canine Factor VIII 3′-Untranslated Region and a Concatemeric Hepatocyte Nuclear Factor 1 Regulatory Element Enhance Factor VIII Transgene Expression <i>In Vivo</i>
Bibliographic record
Abstract
If gene therapy is to be an effective treatment modality for hemophilia A, therapeutic levels and tissue-restricted expression of factor VIII (FVIII) must be achieved through optimization of transgene expression. To this end, we incorporated three types of sequence elements into a canine B domain-deleted FVIII transgene cassette and individually evaluated their effect on FVIII transgene expression. Functional FVIII activity was initially assessed in vitro and hydrodynamic injection of the different transgene constructs into mice was subsequently used as a model to compare in vivo expression of the various modified transgenes. Our results demonstrate that in vitro transgene expression is, in these studies, not a good predictor of in vivo transgene performance. In vivo analysis of a hybrid tissue-restricted promoter element, consisting of a concatemer of five hepatocyte nuclear factor 1 (HNF-1) consensus-binding motifs juxtaposed to the human FVIII proximal promoter, indicates that it is as efficient at mediating expression of the FVIII protein as the cytomegalovirus promoter. Addition of the full-length canine FVIII 3'-UTR also enhances transgene expression of FVIII in vivo. Sequence analysis of the canine FVIII 3'-UTR and human FVIII 3'-UTR indicates that the former lacks instability sequences and may therefore be more effective in stabilizing FVIII mRNA. Subsequent inclusion of FVIII introns 16 and 17 into the natural locations of the transgene disrupted mRNA processing and abolished expression of the FVIII protein. Introduction of intron 17 proximal to the FVIII cDNA did not enhance in vivo expression of canine FVIII from the transgene.
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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) | 0.001 | 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".