Proteomics Analysis of Interleukin (IL)-7-induced Signaling Effectors Shows Selective Changes in IL-7Rα449F Knock-in T Cell Progenitors
Bibliographic record
Abstract
Interleukin (IL)-7 is a cytokine that plays a central role in the development, survival, and proliferation of T and B cell lymphocytes. Overexpression of IL-7 in mice (transgenic (Tg) IL-7) leads to both increased proliferation of early T and B cell progenitors and T and B cell lymphomas. Genetic evidence indicates that known IL-7 receptor (IL-7R)-dependent proteins, including prosurvival protein BCL-2, may not be solely responsible for the effects of IL-7. Other studies indicate that known IL-7-induced signaling proteins dock to a specific tyrosine (Tyr(449)) residue on the alpha-subunit of the IL-7R. We have previously shown in an IL-7Ralpha(449F) knock-in model that IL-7-induced lymphomas require Tyr(449) phosphorylation and that loss of this phosphorylation confers protection from disease. However, the mechanism by which this lymphoma protection occurs remains unclear. Using this genetic model, we aimed to identify novel prosurvival factors important for IL-7-mediated lymphocyte development and lymphomagenesis. An iTRAQ (isobaric tags for relative and absolute quantitation) proteomics analysis was performed comparing CD4(-)CD8(-) double negative T cell progenitors from mice overexpressing IL-7 (Tg IL-7) (lymphoma-prone) with Tg IL-7 mice with a mutated IL-7 receptor (Tg IL-7/IL-7Ralpha(449F)) (lymphoma-protected). Several proteins involved in survival, proliferation, and apoptosis were found to be differentially expressed between the two samples, and three proteins of particular interest, GIMAP4, BIT1, and FKBP51, were validated by immunoblot analysis.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".