MK2 Inhibition Induces p53-Dependent Senescence in Glioblastoma Cells
Bibliographic record
Abstract
MAPK-activated protein kinase 2 (MK2) has diverse roles in cancer. In response to chemotherapy, MK2 inhibition is synthetically lethal to p53-deficiency. While TP53 deletion is rare in glioblastomas, these tumors often carry TP53 mutations. Here, we show that MK2 inhibition strongly attenuated glioblastoma cell proliferation through p53wt stabilization and senescence. The senescence-inducing efficacy of MK2 inhibition was particularly strong when cells were co-treated with the standard-of-care temozolomide. However, MK2 inhibition also increased the stability of p53 mutants and enhanced the proliferation of p53-mutant stem cells. These observations reveal that in response to DNA damaging chemotherapy, targeting MK2 in p53-mutated cells produces a phenotype that is distinct from the p53-deficient phenotype. Thus, MK2 represents a novel drug target in 70% glioblastomas harboring intact TP53 gene. However, targeting MK2 in tumors with TP53 mutations may accelerate disease progression. These findings are highly relevant since TP53 mutations occur in over 50% of all cancers.
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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".