Proliferation, apoptosis and their regulatory protein expression in colorectal adenomas and serrated lesions
Bibliographic record
Abstract
BACKGROUND: Adenomas and serrated lesions represent heterogeneous sets of early precursors in the colorectum with varying malignant potential. They are often distinguished by their histopathologic differences, but little is known about potential differences in regulation of epithelial proliferation and apoptosis. METHODS: We conducted a protein expression analysis using tissue microarrays of 625 colorectal adenomas and 142 serrated lesions to determine potential differences in regulation of epithelial proliferation and apoptosis. We quantitated proliferation with Ki-67; apoptosis with activated caspase-3 (CASP3); up- and down-regulators of proliferation with cyclin D1, p16INK2, and p21Cip1; and apoptosis regulators with BAX, BCL2, and survivin. Linear mixed effects models and circos diagrams were used to determine relationships among expression and lesion characteristics. RESULTS: Adenomas had a significantly higher CASP-3 labeling index (LI) than serrated lesions, resulting in a lower net growth ratio (Ki-67 LI/activated CASP-3 LI, p-value<0.0001). Cyclin D1 LI, p16 LI and p21 LI were lower in adenomas compared to serrated lesions, while expression of both BCL2 and BAX were higher (p <0.001). Among adenomas, cyclin D1 LI and p16 LI levels increased with greater villous component, and the highest BAX expression was detected in adenomas larger than 2 cm (both p<0.0001). Right-sided adenomas had higher CASP3 LI than left colorectal adenomas (p = 0.008). Significant differences in cyclin D1 LI, p21 LI and survivin LI were also observed across histopathologic subtypes of serrated lesions. CONCLUSIONS: Our findings demonstrate different patterns of regulatory protein expression in adenomas than serrated lesions, especially involving apoptosis. ClinicalTrials.gov Identifier: NCT00272324.
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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 | 0.001 |
| 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) | 0.001 | 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".