N‐end‐rule‐mediated Degradation of the Proteolytically Activated Form of PKC‐theta Kinase attenuates its Pro‐Apoptotic Function
Bibliographic record
Abstract
Cellular stresses and signalling that lead to the initiation of apoptotic pathways often result in the activation of caspases or calpains which in turn leads to the generation of proteolytically generated protein fragments with new or altered functions. Mounting number of studies reveal that the activity of these proteolytically activated protein fragments can be counteracted via their selective degradation by the N‐End Rule pathway. Here we investigate the proteolytically generated fragment of the PKC theta kinase, where we report the first study on the stability of this pro‐apoptotic protein fragment. We have determined that the pro‐apoptotic cleaved fragment of PKC‐theta is unstable in cells as its N‐terminal lysine targets it for proteasomal degradation via the N‐end rule pathway and this degradation is inhibited by mutating the destabilizing N‐Termini, knockdown of the UBR1 and UBR2 E3 ligases. Tellingly, we demonstrate that the metabolic stabilization of the cleaved fragment of PKC‐theta or inhibition of the N‐end rule augments the apoptosis‐inducing effect of staurosporine in Jurkat cells. Notably, we have demonstrated that the cleaved fragment of PKC theta, per se , can induce apoptotic cell death in Jurkat T‐cell leukemia. Our results expand the functional scope of N‐end rule pathway and support the notion that targeting N‐end rule machinery may have therapeutic implications. Support or Funding Information Mohamed Eldeeb is supported by Alberta‐Innovates Technology Futures (AITF) scholarship.
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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) | 0.002 | 0.001 |
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".