Comparative Interactomes of VRK1 and VRK3 with Their Distinct Roles in the Cell Cycle of Liver Cancer
Bibliographic record
Abstract
Vaccinia-related kinase 1 (VRK1) and VRK3 are members of the VRK family of serine/threonine kinases and are principally localized in the nucleus. Despite the crucial roles of VRK1/VRK3 in physiology and disease, the molecular and functional interactions of VRK1/VRK3 are poorly understood. Here, we identified over 200 unreported VRK1/VRK3-interacting candidate proteins by affinity purification and LC-MS/MS. The networks of VRK1 and VRK3 interactomes were found to be associated with important biological processes such as the cell cycle, DNA repair, chromatin assembly, and RNA processing. Interactions of interacting proteins with VRK1/VRK3 were confirmed by biochemical assays. We also found that phosphorylations of XRCC5 were regulated by both VRK1/VRK3, and that of CCNB1 was regulated by VRK3. In liver cancer cells and tissues, VRK1/VRK3 were highly upregulated and its depletion affected cell cycle progression in the different phases. VRK3 seemed to affect S phase progression and G2 or M phase entry and exit, whereas VRK1 affects G1/S transition in the liver cancer, which could be explained by different interacting candidate proteins. Thus, this study not only provides a resource for investigating the unidentified functions of VRK1/VRK3, but also an insight into the regulatory roles of VRK1/VRK3 in biological processes.
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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 | 0.001 |
| 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".