Selective ablation of the YxxM motif of IL-7R alpha suppresses lymphomagenesis but maintains lymphocyte development (38.5)
Bibliographic record
Abstract
Abstract Lymphocyte homeostasis is exquisitely sensitive to the cytokine interleukin (IL)-7. Loss of IL-7 signaling prevents lymphocyte development whereas excess IL-7 causes murine lymphoma and has been detected in several human lymphomas. We have previously shown that targeted disruption of the Y449xxM motif of the IL-7 receptor alpha (IL-7Rα) in a knock-in mouse model (IL-7Rα449F) has minor effects on lymphocyte production, but interferes with activation of survival effectors. We hypothesized that targeted signal ablation would selectively affect lymphocyte transformation. To address this, IL-7Rα449F mice were crossed with two lymphomagenesis models, transgenic (Tg) IL-7 and Eμ Myc mice. We found that loss of IL-7Rα Y449 signaling was sufficient to reverse the developmental aberrations induced by both the IL-7 and Eμ Myc transgenes, prevented Tg IL-7 mediated T and B lymphocyte transformation and significantly decreased development of Eμ Myc-induced B cell tumors. We show that the IL-7Rα449F mutation is essential for Tg IL-7 mediated up-regulation of pro-survival Bcl-2 family members, and for rapid cycling of bone marrow progenitor B cells induced by Eμ Myc. This study highlights the therapeutic potential of targeting the IL-7Rα Y449xxM motif or its downstream effectors in treatment of human lymphocyte malignancies. Research supported by the Canadian Institutes of Health Research, the Natural Sciences and Engineering Research Council of Canada and the Michael Smith Foundation for Health Research.
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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 | 0.001 |
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".