The Lipid Anticancer Drug Edelfosine Affects Gene Expression Regulation
Bibliographic record
Abstract
Sirtuins are highly conserved regulators of gene expression. A genetic screen performed by our group using budding yeast found that sensitivity to the anticancer lipid drug edelfosine is alleviated in cells lacking sirtuins (SIR complex in yeast). The mechanism by which sirtuins mediate sensitivity to edelfosine, which localizes to the nuclear envelope (NE), is unclear. Here, we investigated the effect of edelfosine on the nuclear membrane and regulation of the nucleus. Using fluorescence microscopy, we observed NE deformation and changes in clustering of the telomere‐binding proteins Rap1 and Sir4. Transcriptomic analysis of cells treated with edelfosine showed major downregulation of genes known to be bound by Rap1, with enrichment of ribosomal protein genes. The overall effect of edelfosine on gene expression was reduced in sir4 Δ mutant cells. We also found that constitutive deacetylation of histone H4 Lys16, a target of the SIR complex, caused hypersensitivity to edelfosine. We speculate that edelfosine disrupts genomic regulation via a SIR‐mediated mechanism. We show here that lipid anticancer drugs can affect DNA regulation by disrupting the NE, which has interesting implications for potential combination therapies. Support or Funding Information This work has been financially supported by the Natural Sciences and Engineering Research Council of Canada to VZ and JAC. Also supported by a QEII scholarship to MLSP.
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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) | 0.001 | 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".