Identification of Cell Type-Specific Effects of DNMT3A Mutations on Relapse in Acute Myeloid Leukemia
Why this work is in the frame
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Bibliographic record
Abstract
Acute myeloid leukemia (AML) is a heterogeneous disease caused by distinctive mutations in individual patients; therefore, each patient may display different cell-type compositions. Although most patients with AML achieve complete remission (CR) through intensive chemotherapy, the likelihood of relapse remains high. Several studies have attempted to characterize the genetic and cellular heterogeneity of AML; however, our understanding of the cellular heterogeneity of AML remains limited. In this study, we performed single-cell RNA sequencing (scRNAseq) of bone marrow-derived mononuclear cells obtained from same patients at different AML stages (diagnosis, CR, and relapse). We found that hematopoietic stem cells (HSCs) at diagnosis were abnormal compared to normal HSCs. By improving the detection of the DNMT3A R882 mutation with targeted scRNAseq, we identified that DNMT3A -mutant cells that mainly remained were granulocyte-monocyte progenitors (GMPs) or lymphoid-primed multipotential progenitors (LMPPs) from CR to relapse and that DNMT3A -mutant cells have gene signatures related to AML and leukemic cells. Copy number variation analysis at the single-cell level indicated that the cell type that possesses DNMT3A mutations is an important factor in AML relapse and that GMP and LMPP cells can affect relapse in patients with AML. This study advances our understanding of the role of DNMT3A in AML relapse and our approach can be applied to predict treatment outcomes.
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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 | 0.001 |
| 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