A CK2-dependent mechanism for activation of the JAK-STAT signaling pathway
Bibliographic record
Abstract
JAK-STAT signaling is involved in the regulation of cell survival, proliferation, and differentiation. JAK tyrosine kinases can be transiently activated by cytokines or growth factors in normal cells, whereas they become constitutively activated as a result of mutations that affect their function in tumors. Specifically, the JAK2V617F mutation is present in the majority of patients with myeloproliferative disorders (MPDs) and is implicated in the pathogenesis of these diseases. In the present study, we report that the kinase CK2 is a novel interaction partner of JAKs and is essential for JAK-STAT activation. We demonstrate that cytokine-induced activation of JAKs and STATs and the expression of suppressor of cytokine signaling 3 (SOCS-3), a downstream target, are inhibited by CK2 small interfering RNAs or pharmacologic inhibitors. Endogenous CK2 is associated with JAK2 and JAK1 and phosphorylates JAK2 in vitro. To extend these findings, we demonstrate that CK2 interacts with JAK2V617F and that CK2 inhibitors suppress JAK2V617F autophosphorylation and downstream signaling in HEL92.1.7 cells (HEL) and primary cells from polycythemia vera (PV) patients. Furthermore, CK2 inhibitors potently induce apoptosis of HEL cells and PV cells. Our data provide evidence for novel cross-talk between CK2 and JAK-STAT signaling, with implications for therapeutic intervention in JAK2V617F-positive MPDs.
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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) | 0.001 | 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 | 0.000 |
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".