Data from A Cohort Study of Cyclin D1 Expression and Prognosis in 602 Colon Cancer Cases
Bibliographic record
Abstract
Abstract Purpose: Cyclin D1 and cyclin-dependent kinases (CDK) are commonly activated in colorectal cancer. The activity of cyclin D1 can be blocked by CDK inhibitors, including p27 (CDKN1B) and p21 (CDKN1A, which is induced by p53). However, prognostic significance of tumoral cyclin D1 remains uncertain, and no previous study has considered potential confounding effect of p53, p21, p27, and related molecular events [microsatellite instability (MSI), CpG island methylator phenotype, and LINE-1 hypomethylation]. Experimental Design: Among 602 colon cancer patients (stage I-IV) in two prospective cohort studies, cyclin D1 overexpression was detected in 330 (55%) tumors by immunohistochemistry. Cox proportional hazard models computed hazard ratios (HR) of colon cancer–specific and overall mortalities, adjusted for patient characteristics and tumoral molecular features, including p53, p21, p27, cyclooxygenase-2, fatty acid synthase, LINE-1 methylation, CpG island methylator phenotype, MSI, BMI, KRAS, and BRAF. Results: Cyclin D1 overexpression was associated with a low cancer-specific mortality in Kaplan-Meier analysis (P = 0.006), and in both univariate Cox regression [unadjusted HR, 0.64; 95% confidence interval (CI), 0.47-0.88; P = 0.0063] and multivariate analyses (adjusted HR, 0.57; 95% CI, 0.39-0.84; P = 0.0048). Similar findings were observed for an overall mortality (adjusted HR, 0.74; 95% CI, 0.57-0.98; P = 0.036). Notably, the effect of cyclin D1 on survival might differ by MSI status (Pinteraction = 0.008). Compared with tumors that were both cyclin D1–negative and MSI-low/microsatellite stable, the presence of either cyclin D1 or MSI-high or both seemed to confer better clinical outcome (adjusted HR point estimates, 0.10-0.65). Conclusions: Cyclin D1 overexpression is associated with longer survival in colon cancer.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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) | 0.001 | 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".