EIF4A inhibition targets bioenergetic homeostasis in AML MOLM-14 cells in vitro and in vivo and synergizes with cytarabine and venetoclax
Bibliographic record
Abstract
BACKGROUND: Acute myeloid leukemia (AML) is an aggressive hematological cancer resulting from uncontrolled proliferation of differentiation-blocked myeloid cells. Seventy percent of AML patients are currently not cured with available treatments, highlighting the need of novel therapeutic strategies. A promising target in AML is the mammalian target of rapamycin complex 1 (mTORC1). Clinical inhibition of mTORC1 is limited by its reactivation through compensatory and regulatory feedback loops. Here, we explored a strategy to curtail these drawbacks through inhibition of an important effector of the mTORC1signaling pathway, the eukaryotic initiation factor 4A (eIF4A). METHODS: We tested the anti-leukemic effect of a potent and specific eIF4A inhibitor (eIF4Ai), CR-1-31-B, in combination with cytosine arabinoside (araC) or the BCL2 inhibitor venetoclax. We utilized the MOLM-14 human AML cell line to model chemoresistant disease both in vitro and in vivo. In eIF4Ai-treated cells, we assessed for changes in survival, apoptotic priming, de novo protein synthesis, targeted intracellular metabolite content, bioenergetic profile, mitochondrial reactive oxygen species (mtROS) and mitochondrial membrane potential (MMP). RESULTS: eIF4Ai exhibits anti-leukemia activity in vivo while sparing non-malignant myeloid cells. In vitro, eIF4Ai synergizes with two therapeutic agents in AML, araC and venetoclax. EIF4Ai reduces mitochondrial membrane potential (MMP) and the rate of ATP synthesis from mitochondrial respiration and glycolysis. Furthermore, eIF4i enhanced apoptotic priming while reducing the expression levels of the antiapoptotic factors BCL2, BCL-XL and MCL1. Concomitantly, eIF4Ai decreases intracellular levels of specific metabolic intermediates of the tricarboxylic acid cycle (TCA cycle) and glucose metabolism, while enhancing mtROS. In vitro redox stress contributes to eIF4Ai cytotoxicity, as treatment with a ROS scavenger partially rescued the viability of eIF4A inhibition. CONCLUSIONS: We discovered that chemoresistant MOLM-14 cells rely on eIF4A-dependent cap translation for survival in vitro and in vivo. EIF4A drives an intrinsic metabolic program sustaining bioenergetic and redox homeostasis and regulates the expression of anti-apoptotic proteins. Overall, our work suggests that eIF4A-dependent cap translation contributes to adaptive processes involved in resistance to relevant therapeutic agents in AML.
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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".