Rare MLL-ELL fusion transcripts in childhood acute myeloid leukemia—association with young age and myeloid sarcomas?
Bibliographic record
Abstract
BACKGROUND: The chromosomal translocation t(11;19)(q23;p13) with a breakpoint within subband 19p13.1 is found mainly in acute myeloid leukemia (AML) and results in the MLL-ELL fusion gene. Variations in the structure of MLL-ELL seem to influence the leukemogenic potency of the fusion in vivo and may lie behind differences in clinical features. The number of cases reported so far is very limited and the addition of more information about MLL-ELL variants is essential if the possible clinical significance of rare fusions is to be determined. CASE PRESENTATION: Cytogenetic and molecular genetic analyses were done on the bone marrow cells of a 20-month-old boy with an unusual form of myelomonocytic AML with multiple myeloid sarcomas infiltrating bone and soft tissues. The G-banding analysis together with FISH yielded the karyotype 47,XY, +6,t(8;19;11)(q24;p13;q23). FISH analysis also demonstrated that MLL was split. RNA-sequencing showed that the translocation had generated an MLL-ELL chimera in which exon 9 of MLL (nt 4241 in sequence with accession number NM_005933.3) was fused to exon 6 of ELL (nt 817 in sequence with accession number NM_006532.3). RT-PCR together with Sanger sequencing verified the presence of the above-mentioned fusion transcript. CONCLUSIONS: Based on our findings and information on a few previously reported patients, we speculate that young age, myelomonoblastic AML, and the presence of extramedullary disease may be typical of children with rare MLL-ELL fusion transcripts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".