Plasmacytoid dendritic cells proliferation associated with acute myeloid leukemia: phenotype profile and mutation landscape
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Bibliographic record
Abstract
Neoplasms involving plasmacytoid Dendritic Cells (pDCs) include Blastic pDC Neoplasms (BPDCN) and other pDC proliferations, where pDCs are associated with myeloid malignancies: most frequently Chronic MyeloMonocytic Leukemia (CMML) but also Acute Myeloid Leukemia (AML), hereafter named pDC-AML. We aimed to determine the reactive or neoplastic origin of pDCs in pDC-AML, and their link with the CD34+ blasts, monocytes or conventional DCs (cDCs) associated in the same sample, by phenotypic and molecular analyses (targeted NGS, 70 genes). We compared 15 pDC-AML at diagnosis with 21 BPDCN and 11 normal pDCs from healthy donors. CD45low CD34+ blasts were found in all cases (10-80% of medullar cells), associated with pDCs (4-36%), monocytes in 14 cases (1-10%) and cDCs (2 cases, 4.8-19%). pDCs in pDC-AML harbor a clearly different phenotype from BPDCN: CD4+ CD56- in 100% of cases, most frequently CD303+, CD304+ and CD34+; lower expression of cTCL1 and CD123 with isolated lymphoid markers (CD22/CD7/CD5) in some cases, suggesting a pre-pDC stage. In all cases, pDCs, monocytes and cDC are neoplastic since they harbor the same mutations as CD34+ blasts. RUNX1 is the most commonly mutated gene: detected in all AML with minimal differentiation (M0-AML) but not in the other cases. Despite low number of cases, the systematic association between M0-AML, RUNX1 mutations and an excess of pDC is puzzling. Further evaluation in a larger cohort is required to confirm RUNX1 mutations in pDC-AML with minimal differentiation and to investigate whether it represents a proliferation of blasts with macrophage and DC progenitor potential.
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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) | 0.000 | 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) | 0.000 | 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 it