Clinical, Phenotypic and Molecular Characterization of <i>NUP214-ABL1</i> Fusion Positive Myeloid Malignancies
Bibliographic record
Abstract
The identification of a NUP214-ABL1 fusion has been seen in about 6% of patients with T lymphoblastic leukemia (T-ALL). It has been described at a lower frequency in B-lymphoblastic leukemia (B-ALL) patients as well. To our knowledge, this is the first case report documenting a NUP214-ABL1 fusion in a patient with newly diagnosed myelodysplastic syndrome (MDS) as identified by next-generation sequencing (NGS). A case report by Wang et al recently described a case report of the first NUP214-ABL1 fusion in a patient with newly diagnosed acute myeloid leukemia (AML). This shows that this specific translocation is not isolated to lymphoid malignancies, and can be associated with myeloid malignancies as well. The potential use of tyrosine kinase inhibitors (TKIs) as a line of treatment for patients who harbor this translocation makes this finding of particular interest. However, while there have been individual reports noting the effect of TKIs in T-ALLs with NUP214-ABL1 fusions, additional research is needed to fully understand the role of this mutation in myeloid derived malignancies, and its corresponding treatment and prognostic implications. J Med Cases. 2024;15(9):250-255 doi: https://doi.org/10.14740/jmc4286
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".