Targeting CDK9 in KMT2A-Rearranged Infant Leukemia: Evidence for Activity and Drug Synergy with Enitociclib
Bibliographic record
Abstract
Introduction: Translocations of the lysine methyltransferase 2A (KMT2A) gene on 11q23 are seen in most infant leukemias. The outcomes in cases with KMT2A rearrangements (KMT2Ar) are significantly worse due to higher disease relapse rates and the emergence of chemo-resistance. Studies have shown that P-TEFb (CDK9/Cyclin T1) is an important component of the KMT2Ar complex and drives the transcriptional elongation step, subsequently contributing to the development of leukemia (Mueller, Dorothee et al.,2009). Based on this rationale, we investigated the potential of the selective P-TEFb/CDK9 inhibitor enitociclib in infant leukemia. Enitociclib potently inhibits MYC and MCL-1 in various tumor models (Sher, Steven et al.,2023). In addition, menin has been shown to be an important protein in the activation of target genes by KMT2Ar fusions, and menin inhibitors are considered promising therapeutic agents against infant leukemias, with at least four menin inhibitors currently in clinical development. We show preclinical data to support the activity of enitociclib with respect to cellular cytotoxicity, apoptosis induction and drug synergy in infant leukemia cells. Methods: A panel of pediatric leukemia cell lines representing high-risk and treatment resistant KMT2Ar cells were used. Leukemia cells with wild-type KMT2A as well as normal CD34+ cells and PBMCs from healthy donors were used as controls. Leukemic cells were treated with enitociclib (0.5µM - 0.03µM) and cell viability was measured using alamar blue assay. Apoptotic cell death following enitociclib treatment was measured by Annexin V/Propidium Iodide flow cytometry. Target modulation analyses were carried out by western blotting. Bone marrow (BM) stroma and leukemia co-culture experiments were performed to identify the effect of enitociclib on BM-derived growth support provided to leukemic cells. Drug combination assays were carried out with the menin inhibitor MI-463 and combination indices were calculated using the Chao-Talalay method. Rat xenograft models bearing infant leukemia cells were used to study the efficacy and tolerability of enitociclib therapy. Results: Data from in vitro cytotoxicity assays showed high sensitivity of KMT2Ar infant leukemia cells to enitociclib with IC 50 values of 30nM for KMT2Ar cells and 406nM for KMT2A-WT cells. Annexin V/PI staining showed a dose-dependent increase in cells in the late apoptotic stage for KMT2Ar cells after treatment. Target validation assays in KMT2Ar cells showed inhibition of transcriptional elongation by decreased serine phosphorylation by approximately 75% of RNA POL II CTD starting as early as 6 hours after treatment with 0.1µM enitociclib. Additionally, in KMT2Ar cells, an 80%-85% reduction in the amount of MCL-1 and MYC protein levels was observed after treatment with 0.1µM enitociclib for 6 hours. Furthermore, our data show that enitociclib may help to overcome the BM derived stromal mediated survival advantage in KMT2Ar leukemic cells. Enitociclib also potentiated the anti-leukemic effect of chemotherapies for childhood leukemia with the most effective combination observed with doxorubicin (0.01µM IC 50 for doxorubicin alone, 0.002µM IC 50 when combined with enitociclib) and prednisolone (25µM IC 50 for prednisolone only, 0.01µM IC 50 in combination). Drug combination assays showed effective synergy between enitociclib and the KMT2A-menin inhibitor MI-463 in KMT2Ar infant leukemia cells with a combination index of less than 1. As a detectable biomarker of activity, HOXA9 protein levels were found to be robustly diminished with 60% decrease after 24-hour treatment with the drug combination. In vivo, enitociclib given once weekly for 3 weeks led to complete remission in 10 out of 12 rats bearing KMT2Ar xenografts. Discussion: Our data demonstrate the ability of enitociclib to induce effective cellular cytotoxicity in high-risk KMT2Ar leukemia cells. We further show that enitociclib potentiated the anti-leukemic effect of chemotherapies that constitute the backbone of childhood leukemia protocols. Importantly, we show synergy with menin inhibition that is currently in consideration to be included in new generation clinical trials, suggesting the effective use of this novel combination in future treatment protocols. We provide the first in vitro and animal data supporting enitociclib in future treatment approaches for infants with KMT2Ar leukemia.
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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) | 0.001 | 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".