Genotoxic Anti-Cancer Agents and Their Relationship to DNA Damage, Mitosis, and Checkpoint Adaptation in Proliferating Cancer Cells
Bibliographic record
Abstract
When a human cell detects damaged DNA, it initiates the DNA damage response (DDR) that permits it to repair the damage and avoid transmitting it to daughter cells. Despite this response, changes to the genome occur and some cells, such as proliferating cancer cells, are prone to genome instability. The cellular processes that lead to genomic changes after a genotoxic event are not well understood. Our research focuses on the relationship between genotoxic cancer drugs and checkpoint adaptation, which is the process of mitosis with damaged DNA. We examine the types of DNA damage induced by widely used cancer drugs and describe their effects upon proliferating cancer cells. There is evidence that cell death caused by genotoxic cancer drugs in some cases includes exiting a DNA damage cell cycle arrest and entry into mitosis. Furthermore, some cells are able to survive this process at a time when the genome is most susceptible to change or rearrangement. Checkpoint adaptation is poorly characterised in human cells; we predict that increasing our understanding of this pathway may help to understand genomic instability in cancer cells and provide insight into methods to improve the efficacy of current cancer therapies.
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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 | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".