Tailoring capsid-directed evolution technology for improved AAV-mediated CAR-T generation
Bibliographic record
Abstract
Chimeric antigen receptor (CAR) T cell (CAR-T) therapies present options for patients diagnosed with certain leukemias. Recent advances of the technology included a method to integrate the CAR into the T cell receptor alpha constant (TRAC) locus to take advantage of the endogenous promoter and regulatory elements for CAR expression. This method used adeno-associated viral (AAV) vectors based on AAV6 to deliver the donor template encoding the CAR construct. Since the original publication, improvements have been made to this targeted CAR integration technique; however, none of those techniques focused on improving the AAV vector used to deliver the therapeutic cargo. The herein presented study developed a novel AAV capsid directed evolution platform that allows for specifically selecting for novel AAV capsid variants that enable more efficient targeted gene editing-mediated CAR construct integration into the TRAC locus in primary T cells. Using this new platform, we selected several novel AAVs that enable more efficient editing in T cells than AAV6. Two novel capsids, AAV-T1 and AAV-T2, were able to mediate 5-fold improvement for on-target knockin, which resulted in 5-fold reduction of the vector dose to produce highly cytolytic T cells against a brain tumor cell line.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".