The Implication of Topoisomerase II Inhibitors in Synthetic Lethality for Cancer Therapy
Bibliographic record
Abstract
DNA topoisomerase II (Top2) is essential for all eukaryotic cells in the regulation of DNA topology through the generation of temporary double-strand breaks. Cancer cells acquire enhanced Top2 functions to cope with the stress generated by transcription and DNA replication during rapid cell division since cancer driver genes such as Myc and EZH2 hijack Top2 in order to realize their oncogenic transcriptomes for cell growth and tumor progression. Inhibitors of Top2 are therefore designed to target Top2 to trap it on DNA, subsequently causing protein-linked DNA breaks, a halt to the cell cycle, and ultimately cell death. Despite the effectiveness of these inhibitors, cancer cells can develop resistance to them, thereby limiting their therapeutic utility. To maximize the therapeutic potential of Top2 inhibitors, combination therapies to co-target Top2 with DNA damage repair (DDR) machinery and oncogenic pathways have been proposed to induce synthetic lethality for more thorough tumor suppression. In this review, we will discuss the mode of action of Top2 inhibitors and their potential applications in cancer treatments.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".