Targeting CDK9 inhibits the growth of KMT2A-rearranged infant leukemia and demonstrates synergy with menin inhibition
Bibliographic record
Abstract
• Enitociclib synergizes with MI-463 to effectively decrease HOXA9 protein levels in infant KMT2A-r leukemia cells. • Enitociclib potentiates the cytotoxicity of venetoclax in relatively venetoclax-resistant KMT2A-r leukemic cells. The KMT2A-rearranged (KMT2A-r) leukemia is one of the most challenging cancers to treat in children, owing to the higher relapse rates and chemoresistance frequently observed in this patient population. At the molecular level, chromosomal translocation in the KMT2A gene leads to a deregulated epigenetic landscape resulting in the upregulation of transcription factors like HOXA9 , consequently contributing to leukemogenesis. One crucial component of the oncogenic KMT2A-r complex is the involvement of positive transcription elongation factor b, which is composed of cyclin T and cyclin-dependent kinase 9 (CDK9), which leads to the dysregulation of transcriptional elongation. This study investigated the function of enitociclib, a small molecule CDK9 inhibitor in clinical development that has shown effective activity in other tumor types. Enitociclib showed growth inhibition and an on-target effect in KMT2A-r leukemic cells with a significant decrease in MYC and MCL-1 protein levels. Moreover, enitociclib was found to reduce the growth advantage provided to leukemic cells by the bone marrow microenvironment. In addition, it demonstrates the ability to synergize with menin inhibitors, leading to an effective decrease in HOXA9 protein levels in KMT2A-r infant leukemia cells. Enitociclib also potentiates the cytotoxicity of venetoclax in relatively venetoclax-resistant KMT2A-r leukemic cells. Overall, enitociclib has shown measurable in vitro antitumor activity in KMT2A-r infant leukemia and is a rational therapeutic option to explore in future clinical trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".