Eradication of B-ALL using chimeric antigen receptor–expressing T cells targeting the TSLPR oncoprotein
Bibliographic record
Abstract
Adoptive transfer of T cells genetically modified to express chimeric antigen receptors (CARs) targeting the CD19 B cell-associated protein have demonstrated potent activity against relapsed/refractory B-lineage acute lymphoblastic leukemia (B-ALL). Not all patients respond, and CD19-negative relapses have been observed. Overexpression of the thymic stromal lymphopoietin receptor (TSLPR; encoded by CRLF2) occurs in a subset of adults and children with B-ALL and confers a high risk of relapse. Recent data suggest the TSLPR signaling axis is functionally important, suggesting that TSLPR would be an ideal immunotherapeutic target. We constructed short and long CARs targeting TSLPR and tested efficacy against CRLF2-overexpressing B-ALL. Both CARs demonstrated activity in vitro, but only short TSLPR CAR T cells mediated leukemia regression. In vivo activity of the short CAR was also associated with long-term persistence of CAR-expressing T cells. Short TSLPR CAR treatment of mice engrafted with a TSLPR-expressing ALL cell line induced leukemia cytotoxicity with efficacy comparable with that of CD19 CAR T cells. Short TSLPR CAR T cells also eradicated leukemia in 4 xenograft models of human CRLF2-overexpressing ALL. Finally, TSLPR has limited surface expression on normal tissues. TSLPR-targeted CAR T cells thus represent a potent oncoprotein-targeted immunotherapy for high-risk ALL.
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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".