Interleukin-15 enhances cellular proliferation and upregulates CNS homing molecules in pre-B acute lymphoblastic leukemia
Bibliographic record
Abstract
Genome-wide association studies have consistently implicated the interleukin-15 (IL-15) gene in acute lymphoblastic leukemia (ALL) biology, including associations with disease susceptibility, and increased risk of central nervous system (CNS) involvement. However, whether pre-B ALL blasts directly respond to IL-15 is unknown. Here, we show that most pre-B ALL primary samples and cell lines express IL-15 and components of its receptor and that primary pre-B ALL cells show increased growth in culture in response to IL-15. Investigation of mechanisms of action using IL-15-responsive SD-1 cells shows this growth advantage is maximal under low-serum conditions, mimicking those found in cerebrospinal fluid. IL-15 also upregulates PSGL-1 and CXCR3, molecules associated with CNS trafficking. Investigation of downstream signaling pathways indicates that IL-15 induces signal transducer and activator of transcription 5 (STAT5), extracellular signal-regulated kinase (ERK) 1/2, and to a lesser extent phosphatidylinositol 3-kinase (PI3K) and nuclear factor κB (NF-κB) phosphorylation. The IL-15-mediated growth advantage is abolished by mitogen-activated protein kinase kinase/extracellular signal-regulated kinase (MEK/ERK), PI3K, and NF-κB inhibitors but preserved in the presence of STAT5 inhibition. Together, these observations provide a mechanistic link between increased levels of IL-15 expression and leukemogenesis, high-risk disease, and CNS relapse and suggest potential therapeutic targets.
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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 | 0.000 |
| 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".