Vorinostat-induced autophagy switches from a death-promoting to a cytoprotective signal to drive acquired resistance
Bibliographic record
Abstract
Histone deacetylase inhibitors (HDACi) have shown promising activity against hematological malignancies in clinical trials and have led to the approval of vorinostat for the treatment of cutaneous T-cell lymphoma. However, de novo or acquired resistance to HDACi therapy is inevitable, and their molecular mechanisms are still unclear. To gain insight into HDACi resistance, we developed vorinostat-resistant clones from the hematological cell lines U937 and SUDHL6. Although cross-resistant to some but not all HDACi, the resistant cell lines exhibit dramatically increased sensitivity toward chloroquine, an inhibitor of autophagy. Consistent with this, resistant cells growing in vorinostat show increased autophagy. Inhibition of autophagy in vorinostat-resistant U937 cells by knockdown of Beclin-1 or Lamp-2 (lysosome-associated membrane protein 2) restores sensitivity to vorinostat. Interestingly, autophagy is also activated in parental U937 cells by de novo treatment with vorinostat. However, in contrast to the resistant cells, inhibition of autophagy decreases sensitivity to vorinostat. These results indicate that autophagy can switch from a proapoptotic signal to a prosurvival function driving acquired resistance. Moreover, inducers of autophagy (such as mammalian target of rapamycin inhibitors) synergize with vorinostat to induce cell death in parental cells, whereas the resistant cells remain insensitive. These data highlight the complexity of the design of combination strategies using modulators of autophagy and HDACi for the treatment of hematological malignancies.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".