High frequency of germline <i>RUNX1</i> mutations in patients with<i> RUNX1</i>-mutated AML
Bibliographic record
Abstract
RUNX1 is mutated in ∼10% of adult acute myeloid leukemia (AML). Although most RUNX1 mutations in this disease are believed to be acquired, they can also be germline. Indeed, germline RUNX1 mutations result in the well-described autosomal-dominant familial platelet disorder with predisposition to hematologic malignancies (RUNX1-FPD, FPD/AML, FPDMM); ∼44% of affected individuals progress to AML or myelodysplastic syndromes. Using the Leucegene RUNX1 AML patient group, we sought to investigate the proportion of germline vs acquired RUNX1 mutations in this cohort. Our results showed that 30% of RUNX1 mutations in our AML cohort are germline. Molecular profiling revealed higher frequencies of NRAS mutations and other mutations known to activate various signaling pathways in these patients with RUNX1 germline-mutated AML. Moreover, 2 patients (mother and son) had co-occurrence of RUNX1 and CEBPA germline mutations, with variable AML disease onset at 59 and 27 years, respectively. Together, these data suggest a higher than anticipated frequency of germline RUNX1 mutations in the Leucegene cohort and further highlight the importance of testing for RUNX1 mutations in instances in which allogeneic stem cell transplantation using a related donor is envisioned.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".