Engineering human protein switches for functional control of CARs and transcription factors via oral drug administration
Bibliographic record
Abstract
Abstract While CAR T cells have revolutionized the treatment of certain hematologic malignancies, they can cause severe toxicities, which are expected to be exacerbated with next-generation CAR Ts engineered for improved proliferation, persistence, and efficacy. Therefore, regulatory systems are urgently needed to be able to control these living drugs directly in patients. Here, we engineered a molecular switch, in which the interaction of two human proteins is efficiently induced with the orally available and non-toxic drug A1120. We demonstrate the versatility of this switch by regulating CAR signaling and transcriptional activity in human T cells in vitro and in vivo . Both systems were tightly controlled in the absence of the drug but strongly activated upon administration of the small molecule. Since this switch enables the regulation of diverse systems including CARs and transcription factors, we anticipate that it represents an important step towards next-generation cellular therapies with improved safety and efficacy.
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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) | 0.002 | 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".