Donor-derived Double Negative T cells as a Vehicle for the Off-the-shelf Delivery of Chimeric Antigen Receptor Therapies for B-ALL
Bibliographic record
Abstract
Patient-derived anti-CD19 chimeric antigen receptor T-cell (CAR19-T) therapies have revolutionized the treatment of relapsed and refractory B-cell acute lymphoblastic leukemia (B-ALL). Due to problems associated with patient-derived immunotherapies, this life-saving treatment is inaccessible to many, leading to the development of donor-derived CAR19-T-cells. However, toxicities can arise when infusing donor T-cells into a patient. CD3+CD4-CD8- double negative T-cells (DNTs) can be expanded from the blood of healthy donors and fulfill the requirements of an off-the-shelf (OtS) cellular therapy. Incorporating CAR19 technology onto DNTs would create a safe and potent OtS cellular therapy against B-ALL. We transduced DNTs with a CAR19 construct and evaluated their efficacy, safety and OtS properties via various in vitro assays and a B-ALL xenograft model. Our results demonstrate the safety and efficacy of CAR19-DNTs against B-ALL, and provide proof of concept for using donor-derived DNTs as a platform for CAR technology to deliver OtS CAR-based cellular therapies.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".