Heterozygous PU.1 mutations are associated with acute myeloid leukemia
Bibliographic record
Abstract
The transcription factor PU.1 is required for normal blood cell development. PU.1 regulates the expression of a number of crucial myeloid genes, such as the macrophage colony-stimulating factor (M-CSF) receptor, the granulocyte colony-stimulating factor (G-CSF) receptor, and the granulocyte-macrophage colony-stimulating factor (GM-CSF) receptor. Myeloid cells derived from PU.1(-/-) mice are blocked at the earliest stage of myeloid differentiation, similar to the blast cells that are the hallmark of human acute myeloid leukemia (AML). These facts led us to hypothesize that molecular abnormalities involving the PU.1 gene could contribute to the development of AML. We identified 10 mutant alleles of the PU.1 gene in 9 of 126 AML patients. The PU.1 mutations comprised 5 deletions affecting the DNA-binding domain, and 5 point mutations in 1) the DNA-binding domain (2 patients), 2) the PEST domain (2 patients), and 3) the transactivation domain (one patient). DNA binding to and transactivation of the M-CSF receptor promoter, a direct PU.1 target gene, were deficient in the 7 PU.1 mutants that affected the DNA-binding domain. In addition, these mutations decreased the ability of PU.1 to synergize with PU.1-interacting proteins such as AML1 or c-Jun in the activation of PU.1 target genes. This is the first report of mutations in the PU.1 gene in human neoplasia and suggests that disruption of PU.1 function contributes to the block in differentiation found in AML patients.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".