Correlation of β-Catenin Localization with Cyclooxygenase-2 Expression and CpG Island Methylator Phenotype (CIMP) in Colorectal Cancer
Bibliographic record
Abstract
The WNT/beta-catenin (CTNNB1) pathway is commonly activated in the carcinogenic process. Cross-talks between the WNT and cyclooxygenase-2 (COX-2 or PTGS2)/prostaglandin pathways have been suggested. The relationship between beta-catenin activation and microsatellite instability (MSI) in colorectal cancer has been controversial. The CpG island methylator phenotype (CIMP or CIMP-high) with widespread promoter methylation is a distinct epigenetic phenotype in colorectal cancer, which is associated with MSI-high. However, no study has examined the relationship between beta-catenin activation and CIMP status. Using 832 population-based colorectal cancer specimens, we assessed beta-catenin localization by immunohistochemistry. We quantified DNA methylation in eight CIMP-specific promoters [CACNA1G, CDKN2A(p16), CRABP1, IGF2, MLH1, NEUROG1, RUNX3, and SOCS1] by real-time polymerase chain reaction (MethyLight). MSI-high, CIMP-high, and BRAF mutation were associated inversely with cytoplasmic and nuclear beta-catenin expressions (i.e., beta-catenin activation) and associated positively with membrane expression. The inverse relation between beta-catenin activation and CIMP was independent of MSI. COX-2 overexpression correlated with cytoplasmic beta-catenin expression (even after tumors were stratified by CIMP status), but did not correlate significantly with nuclear or membrane expression. In conclusion, beta-catenin activation is inversely associated with CIMP-high independent of MSI status. Cytoplasmic beta-catenin is associated with COX-2 overexpression, supporting the role of cytoplasmic beta-catenin in stabilizing PTGS2 (COX-2) mRNA.
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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".