Cytokinetic effects of Wee1 disruption in pancreatic cancer
Bibliographic record
Abstract
The Wee1 kinase, which is activated in response to DNA damage, regulates exit from G2 through inhibitory phosphorylation of Cdk1/Cdc2, and is an attractive drug target. However, recent work has highlighted effects of Cdk2 phosphorylation by Wee1 on movement through S-phase, suggesting the potential to sensitize to S-phase specific agents by Wee1 inhibitors. In this paper we applied multiparametric flow cytometry to patient-derived pancreatic cancer xenograft tumor cells to study the cell cycle perturbations of Wee1 disruption via the small molecule inhibitor MK-1775, and genetic knockdown. We find that in vitro treatment with MK-1775, and to a lesser degree, Wee1 RNA transcript knockdown, results in the striking appearance of S-phase cells prematurely entering into mitosis. This effect was not seen in vivo in any of the models tested. Here, although we noted an increase of S-phase cells expressing the damage response marker γH2AX, treatment with MK-1775 did not significantly sensitize cells to the cytidine analog gemcitabine. Treatment with MK-1775 did result in a transient but large increase in cells expressing the mitotic marker phosphorylated H3S10 that reached a peak 4 hours after treatment. This suggests a role for Wee1 regulating the progression of genomically unstable cancer cells through G2 in the absence of extrinsically-applied DNA damage. A single dose of 8Gy ionizing radiation resulted in the time-dependent accumulation of Cyclin A2 positive/phosphorylated H3S10 negative cells at the 4N position, which was abrogated by treatment with MK-1775. Consistent with these findings, a genome-scale pooled RNA interference screen revealed that toxic doses of MK-1775 are suppressed by CDK2 or Cyclin A2 knockdown. These findings support G2 exit as the more significant effect of Wee1 inhibition in pancreatic cancers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".