IL-15 Prevents the Development of T-ALL from Aberrant Thymocytes with Impaired DNA Repair Functions and Increased NOTCH1 Activation
Bibliographic record
Abstract
We previously reported that NOD.Scid mice lacking interleukin-15 (IL-15), or IL-15 receptor alpha-chain, develop T-acute lymphoblastic leukemia (T-ALL). To understand the mechanisms by which IL-15 signaling controls T-ALL development, we studied the thymocyte developmental events in IL-15-deficient Scid mice from NOD and C57BL/6 genetic backgrounds. Both kinds of mice develop T-ALL characterized by circulating TCR-negative cells expressing CD4, CD8 or both. Analyses of thymocytes in NOD.Scid.Il15−/− mice prior to T-ALL development revealed discernible changes within the CD4−CD8− double-negative (DN) thymocyte developmental stages and increased frequencies of CD4+CD8+ double-positive cells with a high proportion of TCR-negative CD4+ and CD8+ cells. The DN cells also showed elevated expressions of CXCR4 and CD117, molecules implicated in the expansion of DN thymocytes. T-ALL cell lines and primary leukemic cells from IL-15-deficient NOD.Scid and C57BL/6.Scid mice displayed increased NOTCH1 activation that was inhibited by NOTCH1 inhibitors and blockers of the PI3K/AKT pathway. Primary leukemic cells from NOD.Scid.Il15−/− mice survived and expanded when cultured with MS5 thymic stromal cells expressing Delta-like ligand 4 and supplemented with IL-7 and FLT3 ligand. These findings suggest that IL-15 signaling in the thymus controls T-ALL development from aberrant thymocytes with an impaired DNA repair capacity and increased NOTCH1 activation.
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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".