IGFBP3 Promoter Methylation in Colorectal Cancer: Relationship with Microsatellite Instability, CpG Island Methylator Phenotype, p53
Bibliographic record
Abstract
Insulin-like growth factor binding protein 3 (IGFBP3), which is induced by wild-type p53, regulates IGF and interacts with the TGF-beta pathway. IGFBP3 promoter methylation may occur in colorectal cancer with or without the CpG island methylator phenotype (CIMP), which is associated with microsatellite instability (MSI) and TGFBR2 mutation. We examined the relationship between IGFBP3 methylation, p53 expression, CIMP and MSI in 902 population-based colorectal cancers. Utilizing real-time PCR (MethyLight), we quantified promoter methylation in IGFBP3 and eight other CIMP-high-specific promoters (CACNA1G, CDKN2A, CRABP1, IGF2, MLH1, NEUROG1, RUNX3, and SOCS1). IGFBP3 methylation was far more frequent in non-MSI-high CIMP-high tumors (85% = 35/41) than in MSI-high CIMP-high (49% = 44/90, P < .0001), MSI-high non-CIMP-high (17% = 6/36, P < .0001), and non-MSI-high non-CIMP-high tumors (22% = 152/680, P < .0001). Among CIMP-high tumors, the inverse relationship between MSI and IGFBP3 methylation persisted in p53-negative tumors (P < .0001), but not in p53-positive tumors. IGFBP3 methylation was associated inversely with TGFBR2 mutation in MSI-high non-CIMP-high tumors (P = .02). In conclusion, IGFBP3 methylation is inversely associated with MSI in CIMP-high colorectal cancers, and this relationship is limited to p53-negative tumors. Our data suggest complex relationship between global genomic/epigenomic phenomena (such as MSI/CIMP), single molecular events (e.g., IGFBP3 methylation, TP53 mutation, and TGFBR2 mutation), and the related pathways.
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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 | 0.000 | 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".