Peroxisomes protect lymphoma cells from HDAC inhibitor-mediated apoptosis
Bibliographic record
Abstract
Peroxisomes are a critical rheostat of reactive oxygen species (ROS), yet their role in drug sensitivity and resistance remains unexplored. Gene expression analysis of clinical lymphoma samples suggests that peroxisomes are involved in mediating drug resistance to the histone deacetylase inhibitor (HDACi) Vorinostat (Vor), which promotes ROS-mediated apoptosis. Vor augments peroxisome numbers in cultured lymphoma cells, concomitant with increased levels of peroxisomal proteins PEX3, PEX11B, and PMP70. Genetic inhibition of peroxisomes, using PEX3 knockdown, reveals that peroxisomes protect lymphoma cells against Vor-mediated cell death. Conversely, Vor-resistant cells were tolerant to elevated ROS levels and possess upregulated levels of (1) catalase, a peroxisomal antioxidant, and (2) plasmalogens, ether glycerophospholipids that represent peroxisome function and serve as antioxidants. Catalase knockdown induces apoptosis in Vor-resistant cells and potentiates ROS-mediated apoptosis in Vor-sensitive cells. These findings highlight the role of peroxisomes in resistance to therapeutic intervention in cancer, and provide a novel modality to circumvent drug resistance.
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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 | 0.000 |
| 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".