CBFA2T3::GLIS2 pediatric acute megakaryoblastic leukemia is sensitive to BCL-XL inhibition by navitoclax and DT2216
Bibliographic record
Abstract
ABSTRACT: Acute megakaryoblastic leukemia (AMKL) is a rare, developmentally restricted, and highly lethal cancer of early childhood. The paucity and hypocellularity (due to myelofibrosis) of primary patient samples hamper the discovery of cell- and genotype-specific treatments. AMKL is driven by mutually exclusive chimeric fusion oncogenes in two-thirds of the cases, with CBFA2T3::GLIS2 (CG2) and NUP98 fusions (NUP98r) representing the highest-fatality subgroups. We established CD34+ cord blood-derived CG2 models (n = 6) that sustain serial transplantation and recapitulate human leukemia regarding immunophenotype, leukemia-initiating cell frequencies, comutational landscape, and gene expression signature, with distinct upregulation of the prosurvival factor B-cell lymphoma 2 (BCL2). Cell membrane proteomic analyses highlighted CG2 surface markers preferentially expressed on leukemic cells compared with CD34+ cells (eg, NCAM1 and CD151). AMKL differentiation block in the mega-erythroid progenitor space was confirmed by single-cell profiling. Although CG2 cells were rather resistant to BCL2 genetic knockdown or selective pharmacological inhibition with venetoclax, they were vulnerable to strategies that target the megakaryocytic prosurvival factor BCL-XL (BCL2L1), including in vitro and in vivo treatment with BCL2/BCL-XL/BCL-W inhibitor navitoclax and DT2216, a selective BCL-XL proteolysis-targeting chimera degrader developed to limit thrombocytopenia in patients. NUP98r AMKL were also sensitive to BCL-XL inhibition but not the NUP98r monocytic leukemia, pointing to a lineage-specific dependency. Navitoclax or DT2216 treatment in combination with low-dose cytarabine further reduced leukemic burden in mice. This work extends the cellular and molecular diversity set of human AMKL models and uncovers BCL-XL as a therapeutic vulnerability in CG2 and NUP98r AMKL.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".