Acute myeloid leukemia ontogeny is defined by distinct somatic mutations
Bibliographic record
Abstract
Acute myeloid leukemia (AML) can develop after an antecedent myeloid malignancy (secondary AML [s-AML]), after leukemogenic therapy (therapy-related AML [t-AML]), or without an identifiable prodrome or known exposure (de novo AML). The genetic basis of these distinct pathways of AML development has not been determined. We performed targeted mutational analysis of 194 patients with rigorously defined s-AML or t-AML and 105 unselected AML patients. The presence of a mutation in SRSF2, SF3B1, U2AF1, ZRSR2, ASXL1, EZH2, BCOR, or STAG2 was >95% specific for the diagnosis of s-AML. Analysis of serial samples from individual patients revealed that these mutations occur early in leukemogenesis and often persist in clonal remissions. In t-AML and elderly de novo AML populations, these alterations define a distinct genetic subtype that shares clinicopathologic properties with clinically confirmed s-AML and highlights a subset of patients with worse clinical outcomes, including a lower complete remission rate, more frequent reinduction, and decreased event-free survival. This trial was registered at www.clinicaltrials.gov as #NCT00715637.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".