CSNK2 in cancer: pathophysiology and translational applications
Bibliographic record
Abstract
Protein kinase CSNK2 (CK2) is a pleiotropic serine/threonine kinase frequently dysregulated in solid and hematologic malignancies. To consolidate a wide range of biological and clinically oriented data from this unique kinase in cancer, this systematic review summarises existing knowledge from in vitro, in vivo and pre-clinical studies on CSNK2 across 24 different human cancer types. CSNK2 mRNA transcripts, protein levels and activity were found to be routinely upregulated in cancer, and commonly identified phosphotargets included AKT, STAT3, RELA, PTEN and TP53. Phenotypically, it frequently influenced evasion of apoptosis, enhancement of proliferation, cell invasion/metastasis and cell cycle control. Clinically, it held prognostic significance across 14 different cancers, and its inhibition in xenograft experiments resulted in a positive treatment response in 12. In conjunction with commentary on preliminary studies of CSNK2 inhibitors in humans, this review harmonises an extensive body of CSNK2 data in cancer and reinforces its emergence as an attractive target for cancer therapy. Continuing to investigate CSNK2 will be crucial to advancing our understanding of CSNK2 biology, and offers the promise of important new discoveries scientifically and clinically.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".