Expression of Skp2, a p27Kip1 ubiquitin ligase, in malignant lymphoma: correlation with p27Kip1 and proliferation index
Bibliographic record
Abstract
Reduced levels of p27(Kip1) are frequent in human cancers and have been associated with poor prognosis. Skp2, a component of the Skp1-Cul1-F-box protein (SCF) ubiquitin ligase complex, has been implicated in p27(Kip1) degradation. Increased Skp2 levels are seen in some solid tumors and are associated with reduced p27(Kip1). We examined the expression of these proteins using single and double immunolabeling in a large series of lymphomas to determine if alterations in their relative levels are associated with changes in cell proliferation and lymphoma subgroups. We studied the expression of Skp2 in low-grade and aggressive B-cell lymphomas (n = 86) and compared them with p27(Kip1) and the proliferation index (PI). Fifteen hematopoietic cell lines and peripheral blood lymphocytes were studied by Western blot analysis. In reactive tonsils, Skp2 expression was limited to proliferating germinal center and interfollicular cells. Skp2 expression in small lymphocytic lymphomas (SLLs) and follicular lymphomas (FCLs) was low (mean percentage of positive tumor cells, less than 20%) and was inversely correlated (r = -0.67; P <.0001) with p27(Kip1) and positively correlated with the PI (r = 0.82; P <.005). By contrast, whereas most mantle cell lymphomas (MCLs) demonstrated low expression of p27(Kip1) and Skp2, a subset (n = 6) expressed high Skp2 (exceeding 20%) with a high PI (exceeding 50%). Skp2 expression was highest in diffuse large B-cell lymphomas (DLBCLs) (mean, 22%) and correlated with Ki-67 (r = 0.55; P <.005) but not with p27(Kip1). Cytoplasmic Skp2 was seen in a subset of aggressive lymphomas. Our data provide evidence for p27(Kip1) degradative function of Skp2 in low-grade lymphomas. The absence of this relationship in aggressive lymphomas suggests that other factors contribute to deregulation of p27(Kip1) expression in these 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 | 0.000 |
| 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".