The AMPK-like protein kinases Sik2 and Sik3 interact with Hipk and induce synergistic tumorigenesis in a Drosophila cancer model
Bibliographic record
Abstract
Homeodomain-interacting protein kinases (Hipks) regulate cell proliferation, apoptosis, and tissue development. Overexpression of Hipk in Drosophila causes tumorigenic phenotypes in larval imaginal discs. We find that depletion of Salt-inducible kinases Sik2 or Sik3 can suppress Hipk-induced overgrowth. Furthermore, co-expression of constitutively active forms of Sik2 or Sik3 with Hipk caused significant tissue hyperplasia and tissue distortion, indicating that both Sik2 and Sik3 can synergize with Hipk to promote tumorous phenotypes, accompanied by elevated dMyc, Armadillo/β-catenin, and the Yorkie target gene expanded. Larvae expressing these hyperplastic growths also display an extended larval phase, characteristic of other Drosophila tumour models. Examination of total protein levels from fly tissues showed that Hipk proteins were reduced when Siks were depleted through RNAi, suggesting that Siks may regulate Hipk protein stability and/or activity. Conversely, expression of constitutively active Siks with Hipk leads to increased Hipk protein levels. Furthermore, Hipk can interact with Sik2 and Sik3 by co-immunoprecipitation. Co-expression of both proteins leads to a mobility shift of Hipk protein, suggesting it is post-translationally modified. In summary, our research demonstrates a novel function of Siks in synergizing with Hipk to promote tumour growth.
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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) | 0.001 | 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".