Mutations of polycomb‐associated gene <i>ASXL1</i> in myelodysplastic syndromes and chronic myelomonocytic leukaemia
Bibliographic record
Abstract
The myelodysplastic syndromes (MDSs) are a heterogeneous group of clonal haematological diseases characterized by ineffective haematopoiesis and predisposition to acute myeloid leukaemia (AML). The pathophysiology of MDSs remains unclear. A definition of the molecular biology of MDSs may lead to a better classification, new prognosis indicators and new treatments. We studied a series of 40 MDS/AML samples by high-density array-comparative genome hybridization (aCGH). The genome of MDSs displayed a few alterations that can point to candidate genes, which potentially regulate histone modifications and WNT pathways (e.g. ASXL1, ASXL2, UTX, CXXC4, CXXC5, TET2, TET3). To validate some of these candidates we studied the sequence of ASXL1. We found mutations in the ASXL1 gene in four out of 35 MDS patients (11%). To extend these results we searched for mutations of ASXL1 in a series of chronic myelomonocytic leukaemias, a disease classified as MDS/Myeloproliferative disorder, and found mutations in 17 out of 39 patients (43%). These results show that ASXL1 might play the role of a tumour suppressor 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) | 0.001 | 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".