Myeloproliferative Neoplasm Driven by ETV6-ABL1 in an Adolescent with Recent History of Burkitt Leukemia
Bibliographic record
Abstract
ETV6-ABL1 gene fusion is a rare genetic rearrangement in a variety of malignancies, including myeloproliferative neoplasms (MPN), acute lymphoblastic leukemia (ALL), and acute myeloid leukemia (AML). Here, we report the case of a 16-year-old male diagnosed with a MPN, 7 months post-completion of treatment for Burkitt leukaemia. RNA sequencing analysis confirmed the presence of an ETV6-ABL1 fusion transcript, with an intact, in-frame ABL tyrosine–kinase domain. Of note, secondary ETV6-ABL1-rearranged neoplastic diseases have not been reported to date. The patient was started on a tyrosine kinase inhibitor (TKI; imatinib) and, subsequently, underwent a 10/10 matched unrelated haematopoietic stem cell transplant. He is disease-free five years post-transplant. Definitive evidence of the prognostic influence of the ETV6-ABL1 fusion in haematological neoplasms is lacking; however, overall data suggest that it is a poor prognostic factor, particularly in patients with ALL and AML. The presence of this ETV6-ABL1 fusion should be more routinely investigated, especially in patients with a CML-like picture. More routine use of whole-genome and RNA sequencing analyses in clinical diagnostic care, in conjunction with conventional cytogenetics, will facilitate these investigations.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".