Skp2 is oncogenic and overexpressed in human cancers
Bibliographic record
Abstract
Skp2 is a member of the F-box family of substrate-recognition subunits of SCF ubiquitin-protein ligase complexes that has been implicated in the ubiquitin-mediated degradation of several key regulators of mammalian G(1) progression, including the cyclin-dependent kinase inhibitor p27, a dosage-dependent tumor suppressor protein. In this study, we examined Skp2 and p27 protein expression by immunohistochemistry in normal oral epithelium and in different stages of malignant oral cancer progression, including dysplasia and oral squamous cell carcinoma. We found that increased levels of Skp2 protein are associated with reduced p27 in a subset of oral epithelial dysplasias and carcinomas compared with normal epithelial controls. Tumors with high Skp2 (>20% positive cells) expression invariably showed reduced or absent p27 and tumors with high p27 (>20% positive cells) expression rarely showed Skp2 positivity. Increased Skp2 protein levels were not always correlated with increased cell proliferation (assayed by Ki-67 staining), suggesting that alterations of Skp2 may contribute to the malignant phenotype without affecting proliferation. Skp2 protein overexpression may lead to accelerated p27 proteolysis and contribute to malignant progression from dysplasia to oral epithelial carcinoma. Moreover, we also demonstrate that Skp2 has oncogenic potential by showing that Skp2 cooperates with H-Ras(G12V) to malignantly transform primary rodent fibroblasts as scored by colony formation in soft agar and tumor formation in nude mice. The observations that Skp2 can mediate transformation and is up-regulated during oral epithelial carcinogenesis support a role for Skp2 as a protooncogene in human tumors.
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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 | 0.001 | 0.001 |
| 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".