Pre-TCR-targeted immunotherapy for T cell acute lymphoblastic leukemia
Bibliographic record
Abstract
Targeted immunotherapy for T cell acute lymphoblastic leukemia (T-ALL), an aggressive tumor of developing T cell progenitors, is an urgent unmet need, especially for relapsed/refractory disease. Selective T-ALL targeting is challenging due to the shared antigen expression between leukemic and normal T cells. Here we identify the pre-T cell receptor (pre-TCR), a surface receptor essential for T cell development, as a biomarker of leukemia-initiating cells (LICs) in human T-ALL. Loss-of-function genetic approaches demonstrate that pre-TCR signaling is necessary for LIC activity and tumor progression in pre-TCR+ T-ALL patient xenografts in mice. Furthermore, we demonstrate the specific therapeutic targeting of the pre-TCR with a monoclonal antibody against the invariant pTα subunit of the human pre-TCR, and validate an anti-pTα antibody–drug conjugate in vivo treatment as a potent immunotherapy for inhibiting LIC activity and tumor progression of T-ALL in mice. These findings reveal the suitability of pre-TCR targeting as a promising therapy for the treatment of individuals with relapsed/refractory T-ALL expressing the pre-TCR. The authors identify pre-TCR as a key biomarker and therapeutic target in T-ALL. Targeting it with an anti-pTα antibody–drug conjugate inhibits leukemia-initiating cells and tumor growth in mice, offering promise for relapsed/refractory T-ALL treatment.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| 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".