Centromere fragmentation is a common mitotic defect of S and G<sub>2</sub>checkpoint override
Bibliographic record
Abstract
DNA damaging agents, including those used in the clinic, activate cell cycle checkpoints, which blocks entry into mitosis. Given that checkpoint override results in cell death via mitotic catastrophe, inhibitors of the DNA damage checkpoint are actively being pursued as chemosensitization agents. Here we explored the effects of gemcitabine in combination with Chk1 inhibitors in a panel of pancreatic cancer cell lines and found variable abilities to override the S phase checkpoint. In cells that were able to enter mitosis, the chromatin was extensively fragmented, as assessed by metaphase spreads and Comet assay. Notably, electron microscopy and high-resolution light microscopy showed that the kinetochores and centromeres appeared to be detached from the chromatin mass, in a manner reminiscent of mitosis with unreplicated genomes (MUGs). Cell lines that were unable to override the S phase checkpoint were able to override a G2 arrest induced by the alkylator MMS or the topoisomerase II inhibitors doxorubicin or etoposide. Interestingly, checkpoint override from the topoisomerase II inhibitors generated fragmented kinetochores (MUGs) due to unreplicated centromeres. Our studies show that kinetochore and centromere fragmentation is a defining feature of checkpoint override and suggests that loss of cell viability is due in part to acentric genomes. Furthermore, given the greater efficacy of forcing cells into premature mitosis from topoisomerase II-mediated arrest as compared with gemcitabine-mediated arrest, topoisomerase II inhibitors maybe more suitable when used in combination with checkpoint inhibitors.
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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 | 0.000 |
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".