NrasG12D/+ promotes leukemogenesis by aberrantly regulating hematopoietic stem cell functions
Bibliographic record
Abstract
Oncogenic NRAS mutations are frequently identified in human myeloid leukemias. In mice, expression of endogenous oncogenic Nras (Nras(G12D/+)) in hematopoietic cells leads to expansion of myeloid progenitors, increased long-term reconstitution of bone marrow cells, and a chronic myeloproliferative neoplasm (MPN). However, acute expression of Nras(G12D/+) in a pure C57BL/6 background does not induce hyperactivated granulocyte macrophage colony-stimulating factor signaling or increased proliferation in myeloid progenitors. It is thus unclear how Nras(G12D/+) signaling promotes leukemogenesis. Here, we show that hematopoietic stem cells (HSCs) expressing Nras(G12D/+) serve as MPN-initiating cells. They undergo moderate hyperproliferation with increased self-renewal. The aberrant Nras(G12D/+) HSC function is associated with hyperactivation of ERK1/2 in HSCs. Conversely, downregulation of MEK/ERK by pharmacologic and genetic approaches attenuates the cycling of Nras(G12D/+) HSCs and prevents the expansion of Nras(G12D/+) HSCs and myeloid progenitors. Our data delineate critical mechanisms of oncogenic Nras signaling in HSC function and leukemogenesis.
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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".