High frequency of GATA2 mutations in patients with mild chronic neutropenia evolving to MonoMac syndrome, myelodysplasia, and acute myeloid leukemia
Bibliographic record
Abstract
UNLABELLED: Congenital neutropenia is a group of genetic disorders that involve chronic neutropenia and susceptibility to infections. These neutropenias may be isolated or associated with immunologic defects or extra-hematopoietic manifestations. Complications may occur as infectious diseases, but also less frequently as myelodysplastic syndrome (MDS) or acute myeloid leukemia (AML). Recently, the transcription factor GATA2 has been identified as a new predisposing gene for familial AML/MDS. In the present study, we describe the initial identification by exome sequencing of a GATA2 R396Q mutation in a family with a history of chronic mild neutropenia evolving to AML and/or MDS. The subsequent analysis of the French Severe Chronic Neutropenia Registry allowed the identification of 6 additional pedigrees and 10 patients with 6 different and not previously reportedGATA2 mutations (R204X, E224X, R330X, A372T, M388V, and a complete deletion of the GATA2 locus). The frequent evolution to MDS and AML in these patients reveals the importance of screening GATA2 in chronic neutropenia associated with monocytopenia because of the frequent hematopoietic transformation, variable clinical expression at onset, and the need for aggressive therapy in patients with poor clinical outcome. KEY POINTS: Mutations of key transcription factor in myeloid malignancies.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".