A high-content cytokine screen identifies myostatin propeptide as a positive regulator of primitive chronic myeloid leukemia cells
Bibliographic record
Abstract
Aberrantly expressed cytokines in the bone marrow (BM) niche are increasingly recognized as critical mediators of survival and expansion of leukemic stem cells. To identify regulators of primitive chronic myeloid leukemia (CML) cells, we performed a high-content cytokine screen using primary CD34+ CD38low chronic phase CML cells. Out of the 313 unique human cytokines evaluated, 11 were found to expand cell numbers ≥2-fold in a 7-day culture. Focusing on novel positive regulators of primitive CML cells, the myostatin antagonist myostatin propeptide gave the largest increase in cell expansion and was chosen for further studies. Herein, we demonstrate that myostatin propeptide expands primitive CML and normal BM cells, as shown by increased colony-forming capacity. For primary CML samples, retention of CD34-expression was also seen after culture. Furthermore, we show expression of MSTN by CML mesenchymal stromal cells, and that myostatin propeptide has a direct and instant effect on CML cells, independent of myostatin, by demonstrating binding of myostatin propeptide to the cell surface and increased phosphorylation of STAT5 and SMAD2/3. In summary, we identify myostatin propeptide as a novel positive regulator of primitive CML cells and corresponding normal hematopoietic cells.
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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 | 0.000 |
| 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 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".