MK3 Modulation Affects BMI1-Dependent and Independent Cell Cycle Check-Points
Bibliographic record
Abstract
Although the MK3 gene was originally found deleted in some cancers, it is highly expressed in others. The relevance of MK3 for oncogenesis is currently not clear. We recently reported that MK3 controls ERK activity via a negative feedback mechanism. This prompted us to investigate a potential role for MK3 in cell proliferation. We here show that overexpression of MK3 induces a proliferative arrest in normal diploid human fibroblasts, characterized by enhanced expression of replication stress- and senescence-associated markers. Surprisingly, MK3 depletion evokes similar senescence characteristics in the fibroblast model. We previously identified MK3 as a binding partner of Polycomb Repressive Complex 1 (PRC1) proteins. In the current study we show that MK3 overexpression results in reduced cellular EZH2 levels and concomitant loss of epigenetic H3K27me3-marking and PRC1/chromatin-occupation at the CDKN2A/INK4A locus. In agreement with this, the PRC1 oncoprotein BMI1, but not the PCR2 protein EZH2, bypasses MK3-induced senescence in fibroblasts and suppresses P16INK4A expression. In contrast, BMI1 does not rescue the MK3 loss-of-function phenotype, suggesting the involvement of multiple different checkpoints in gain and loss of MK3 function. Notably, MK3 ablation enhances proliferation in two different cancer cells. Finally, the fibroblast model was used to evaluate the effect of potential tumorigenic MK3 driver-mutations on cell proliferation and M/SAPK signaling imbalance. Taken together, our findings support a role for MK3 in control of proliferation and replicative life-span, in part through concerted action with BMI1, and suggest that the effect of MK3 modulation or mutation on M/SAPK signaling and, ultimately, proliferation, is cell context-dependent.
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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".