Inhibition of mitochondrial translation overcomes venetoclax resistance in AML through activation of the integrated stress response
Bibliographic record
Abstract
Venetoclax is a specific B cell lymphoma 2 (BCL-2) inhibitor with promising activity against acute myeloid leukemia (AML), but its clinical efficacy as a single agent or in combination with hypomethylating agents (HMAs), such as azacitidine, is hampered by intrinsic and acquired resistance. Here, we performed a genome-wide CRISPR knockout screen and found that inactivation of genes involved in mitochondrial translation restored sensitivity to venetoclax in resistant AML cells. Pharmacologic inhibition of mitochondrial protein synthesis with antibiotics that target the ribosome, including tedizolid and doxycycline, effectively overcame venetoclax resistance. Mechanistic studies showed that both tedizolid and venetoclax suppressed mitochondrial respiration, with the latter demonstrating inhibitory activity against complex I [nicotinamide adenine dinucleotide plus hydrogen (NADH) dehydrogenase] of the electron transport chain (ETC). The drugs cooperated to activate a heightened integrated stress response (ISR), which, in turn, suppressed glycolytic capacity, resulting in adenosine triphosphate (ATP) depletion and subsequent cell death. Combination treatment with tedizolid and venetoclax was superior to either agent alone in reducing leukemic burden in mice engrafted with treatment-resistant human AML. The addition of tedizolid to azacitidine and venetoclax further enhanced the killing of resistant AML cells in vitro and in vivo. Our findings demonstrate that inhibition of mitochondrial translation is an effective approach to overcoming venetoclax resistance and provide a rationale for combining tedizolid, azacitidine, and venetoclax as a triplet therapy for 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".