Distinct Assemblies of Heterodimeric Cytokine Receptors Govern Stemness Programs in Leukemia
Bibliographic record
Abstract
Leukemia stem cells (LSC) possess distinct self-renewal and arrested differentiation properties that are responsible for disease emergence, therapy failure, and recurrence in acute myeloid leukemia (AML). Despite AML displaying extensive biological and clinical heterogeneity, LSC with high interleukin-3 receptor (IL3R) levels are a constant yet puzzling feature, as this receptor lacks tyrosine kinase activity. Here, we show that the heterodimeric IL3Rα/βc receptor assembles into hexamers and dodecamers through a unique interface in the 3D structure, where high IL3Rα/βc ratios bias hexamer formation. Importantly, receptor stoichiometry is clinically relevant as it varies across the individual cells in the AML hierarchy, in which high IL3Rα/βc ratios in LSCs drive hexamer-mediated stemness programs and poor patient survival, while low ratios mediate differentiation. Our study establishes a new paradigm in which alternative cytokine receptor stoichiometries differentially regulate cell fate, a signaling mechanism that may be generalizable to other transformed cellular hierarchies and of potential therapeutic significance. SIGNIFICANCE: Stemness is a hallmark of many cancers and is largely responsible for disease emergence, progression, and relapse. Our finding that clinically significant stemness programs in AML are directly regulated by different stoichiometries of cytokine receptors represents a hitherto unexplained mechanism underlying cell-fate decisions in cancer stem cell hierarchies. This article is highlighted in the In This Issue feature, p. 1749.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".