Genome-scale genetic interactions position the Mitotic Exit Network as a major antagonist of transient Topoisomerase II deficiency
Bibliographic record
Abstract
Abstract Topoisomerase II (Top2) is the essential protein that resolves DNA catenations. When the Top2 is inactivated, mitotic catastrophe results from massive entanglement of chromosomes. Top2 is also the target of many first-line anticancer drugs, the so-called Top2 poisons. Often, tumours become resistant to these drugs by downregulating Top2. Here, we have compared two isogenic yeast strains carrying top2 thermosensitive alleles that differ in their resistance to Top2 poisons, the broadly-used poison-sensitive top2-4 and the poison-resistant top2-5 . We found that top2-5 transits through anaphase faster than top2-4 . In order to define the biological importance of this difference, we performed genome-scale Synthetic Gene Array (SGA) analyses during chronic sublethal Top2 downregulation and acute, yet transient, Top2 inactivation. We find that downregulation of cell cycle progression, especially the Mitotic Exit Network (MEN), protects against Top2 deficiency. In all conditions, genetic protection was stronger in top2-5 , and this correlated with destabilization of anaphase bridges by execution of MEN. We suggest that mitotic exit may be a therapeutic target to hypersensitize cancer cells carrying downregulating mutations in TOP2 .
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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".