The Tumor Suppressor Kinase LKB1 Activates the Downstream Kinases SIK2 and SIK3 to Stimulate Nuclear Export of Class IIa Histone Deacetylases
Bibliographic record
Abstract
Histone deacetylases 4 (HDAC4), -5, -7, and -9 form class IIa within the HDAC superfamily and regulate diverse physiological and pathological cellular programs. With conserved motifs for phosphorylation-dependent 14-3-3 binding, these deacetylases serve as novel signal transducers that are able to modulate histone acetylation and gene expression in response to extracellular cues. Here, we report that in a PKA-sensitive manner the tumor suppressor kinase LKB1 acts through salt-inducible kinase 2 (SIK2) and SIK3 to promote nucleocytoplasmic trafficking of class IIa HDACs. Both SIK2 and SIK3 phosphorylate the deacetylases at the conserved motifs and stimulate 14-3-3 binding. SIK2 activates MEF2-dependent transcription and relieves repression of myogenesis by the deacetylases. Distinct from SIK2, SIK3 induces nuclear export of the deacetylases independent of kinase activity and 14-3-3 binding. These findings highlight the difference among members of the SIK family and indicate that LKB1-dependent SIK activation constitutes an important signaling module upstream from class IIa deacetylases for regulating cellular programs controlled by MEF2 and other transcription factors.
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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 | 0.000 |
| 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".