Polo-Like Kinase 1 Inhibition Kills Glioblastoma Multiforme Brain Tumor Cells in Part Through Loss of SOX2 and Delays Tumor Progression in Mice
Bibliographic record
Abstract
Glioblastoma multiforme (GBM) ranks among the deadliest types of cancer and given these new therapies are urgently needed. To identify molecular targets, we queried a microarray profiling 467 human GBMs and discovered that polo-like kinase 1 (PLK1) was highly expressed in these tumors and that it clustered with the proliferative subtype. Patients with PLK1-high tumors were more likely to die from their disease suggesting that current therapies are inactive against such tumors. This prompted us to examine its expression in brain tumor initiating cells (BTICs) given their association with treatment failure. BTICs isolated from patients expressed 110-470 times more PLK1 than normal human astrocytes. Moreover, BTICs rely on PLK1 for survival because the PLK1 inhibitor BI2536 inhibited their growth in tumorsphere cultures. PLK1 inhibition suppressed growth, caused G(2) /M arrest, induced apoptosis, and reduced the expression of SOX2, a marker of neural stem cells, in SF188 cells. Consistent with SOX2 inhibition, the loss of PLK1 activity caused the cells to differentiate based on elevated levels of glial fibrillary acidic protein and changes in cellular morphology. We then knocked glial fibrillary acidic protein (GFAP) down SOX2 with siRNA and showed that it too inhibited cell growth and induced cell death. Likewise, in U251 cells, PLK1 inhibition suppressed cell growth, downregulated SOX2, and induced cell death. Furthermore, BI2536 delayed tumor growth of U251 cells in an orthotopic brain tumor model, demonstrating that the drug is active against GBM. In conclusion, PLK1 level is elevated in GBM and its inhibition restricts the growth of brain cancer cells.
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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 | 0.001 |
| 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".