Thymic expression of a T-cell receptor targeting a tumor-associated antigen coexpressed in the thymus induces T-ALL
Bibliographic record
Abstract
T-cell receptors (TCRs) and chimeric antigen receptors recognizing tumor-associated antigens (TAAs) can now be engineered to be expressed on a wide array of immune effectors. Engineered receptors targeting TAAs have most commonly been expressed on mature T cells, however, some have postulated that receptor expression on immune progenitors could yield T cells with enhanced potency. We generated mice (survivin-TCR-transgenic [Sur-TCR-Tg]) expressing a TCR recognizing the immunodominant epitope (Sur20-28) of murine survivin during early stages of thymopoiesis. Spontaneous T-cell acute lymphoblastic leukemia (T-ALL) occurred in 100% of Sur-TCR-Tg mice derived from 3 separate founders. The leukemias expressed the Sur-TCR and signaled in response to the Sur20-28 peptide. In preleukemic mice, we observed increased cycling of double-negative thymocytes expressing the Sur-TCR and increased nuclear translocation of nuclear factor of activated T cells, consistent with TCR signaling induced by survivin expression in the murine thymus. β2M(-/-) Sur-TCR-Tg mice, which cannot effectively present survivin peptides on class I major histocompatibility complex, had significantly diminished rates of leukemia. We conclude that TCR signaling during the early stages of thymopoiesis mediates an oncogenic signal, and therefore expression of signaling receptors on developing thymocytes with specificity for TAAs expressed in the thymus could pose a risk for neoplasia, independent of insertional mutagenesis.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".