Translation inhibitors induce cell death by multiple mechanisms and Mcl-1 reduction is only a minor contributor
Bibliographic record
Abstract
There is significant interest in treating cancers by blocking protein synthesis, to which hematological malignancies seem particularly sensitive. The translation elongation inhibitor homoharringtonine (Omacetaxine mepesuccinate) is undergoing clinical trials for chronic myeloid leukemia, whereas the translation initiation inhibitor silvestrol has shown promise in mouse models of cancer. Precisely how these compounds induce cell death is unclear, but reduction in Mcl-1, a labile pro-survival Bcl-2 family member, has been proposed to constitute the critical event. Moreover, the contribution of translation inhibitors to neutropenia and lymphopenia has not been precisely defined. Herein, we demonstrate that primary B cells and neutrophils are highly sensitive to translation inhibitors, which trigger the Bax/Bak-mediated apoptotic pathway. However, contrary to expectations, reduction of Mcl-1 did not significantly enhance cytotoxicity of these compounds, suggesting that it does not have a principal role and cautions that strong correlations do not always signify causality. On the other hand, the killing of T lymphocytes was less dependent on Bax and Bak, indicating that translation inhibitors can also induce cell death via alternative mechanisms. Indeed, loss of clonogenic survival proved to be independent of the Bax/Bak-mediated apoptosis altogether. Our findings warn of potential toxicity as these translation inhibitors are cytotoxic to many differentiated non-cycling cells.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".