A Ploidy Increase Promotes Sensitivity of Glioma Stem Cells to Aurora Kinases Inhibition
Bibliographic record
Abstract
Glioma stem cells account for glioblastoma relapse and resistance to conventional therapies, and protein kinases, involved in the regulation of the mitotic machinery (i.e., Aurora kinases), have recently emerged as attractive therapeutic targets. In this study, we investigated the effect of Aurora kinases inhibition in five glioma stem cell lines isolated from glioblastoma patients. As expected, cell lines responded to the loss of Aurora kinases with cytokinesis failure and mitotic exit without cell division. Surprisingly, this resulted in a proliferative arrest in only two of the five cell lines. These sensitive cell lines entered a senescent/autophagic state following aberrant mitotic exit, while the non-sensitive cell lines continued to proliferate. This senescence response did not correlate with TP53 mutation status but only occurred in the cell lines with the highest chromosome content. Repeated rounds of Aurora kinases inhibition caused a gradual increase in chromosome content in the resistant cell lines and eventually caused a similar senescence response and proliferative arrest. Our results suggest that a ploidy threshold is the main determinant of Aurora kinases sensitivity in TP53 mutant glioma stem cells. Thus, ploidy could be used as a biomarker for treating glioma patients with Aurora kinases 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) | 0.001 | 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".