CKB inhibits epithelial-mesenchymal transition and prostate cancer progression by sequestering and inhibiting AKT activation
Bibliographic record
Abstract
Epithelial-mesenchymal transition (EMT) contributes to tumor invasion, metastasis and drug resistance. AKT activation is key in a number of cellular processes. While many positive regulators for either EMT or AKT activation have been reported, few negative regulators are established. Through kinase cDNA screen, we identified brain-type creatine kinase (CKB or BCK) as a potent suppressor for both. As a ubiquitously expressed kinase in normal tissues, CKB is significantly downregulated in several solid cancer types. Lower CKB expression is significantly associated with worse prognosis. Phenotypically, CKB overexpression suppresses, while its silencing promotes, EMT and cell migration, xenograft tumor growth and metastasis of prostate cancer cells. AKT activation is one of the most prominent signaling events upon CKB silencing in prostate cancer cells, which is in line with prostate cancer TCGA data. EMT enhanced by CKB silencing is abolished by AKT inhibition. Mechanistically, CKB interacts with AKT and sequestrates it from activation by mTOR. We further elucidated that an 84aa fragment at C-terminus of CKB protein interacts with AKT's PH domain. Ectopic expression of the 84aa CKB fragment inhibits AKT activation, EMT and cell proliferation. Interestingly, molecular dynamics simulation on crystal structures of AKT and CKB independently demonstrates that AKT's PH domain and CKB's 84aa fragment establish their major interaction interface. In summary, we have discovered CKB as a negative regulator of EMT and AKT activation, revealing a new mode of their regulation . We have also demonstrated that CKB downregulation is a poor prognosticator, which is sufficient to promote prostate cancer progression.
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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".