IFN‐γ directly inhibits murine B‐cell precursor leukemia‐initiating cell proliferation early in life
Bibliographic record
Abstract
The early-life immune environment has been implicated as a modulator of acute lymphoblastic leukemia (ALL) development in children, with infection being associated with significant changes in ALL risk. Furthermore, polymorphisms in several cytokine genes, including IL-10 and IFN-γ, are associated with leukemia development. However, the mechanisms and timing of these influences remain unknown. Here, we use the Eμ-ret transgenic mouse model of B-cell precursor ALL to assess the influence of IFN-γ on the early-life burden of leukemia-initiating cells. The absence of IFN-γ activity resulted in greater numbers of leukemia-initiating cells early in life and was associated with accelerated leukemia onset. The leukemia-initiating cells from IFN-γ-knockout mice had reduced suppressor of cytokine signaling (SOCS-1) expression, were significantly more sensitive to IFN-γ, and exhibited more rapid expansion in vivo than their wild-type counterparts. However, sensitivity to this inhibitory pathway was lost in fully transformed IFN-γ-knockout leukemia cells. These results demonstrate that the influence of IFN-γ on ALL progression may not be mediated by selection of nascent transformed cells but rather through a general SOCS-mediated reduction in B-cell precursor proliferation. Thus, while cytokine levels may influence leukemia at multiple points during disease progression, our study indicates a significant early influence of basal, infection-independent cytokine production on leukemogenesis.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".