DNMT3B Expression Might Contribute to CpG Island Methylator Phenotype in Colorectal Cancer
Bibliographic record
Abstract
PURPOSE: DNA methyltransferase-3B (DNMT3B) plays an important role in de novo CpG island methylation. Dnmt3b can induce colon tumor in mice with methylation in specific CpG islands. We hypothesized that cellular DNMT3B level might influence the occurrence of widespread CpG island methylation (i.e., the CpG island methylator phenotype, CIMP) in colon cancer. EXPERIMENTAL DESIGN: Utilizing 765 colorectal cancers in two cohort studies, we detected DNMT3B expression in 116 (15%) tumors by immunohistochemistry. We assessed microsatellite instability, quantified DNA methylation in repetitive long interspersed nucleotide element-1 (LINE-1) by Pyrosequencing, eight CIMP-specific promoters [CACNA1G, CDKN2A (p16), CRABP1, IGF2, MLH1, NEUROG1, RUNX3, and SOCS1], and eight other CpG islands (CHFR, HIC1, IGFBP3, MGMT, MINT1, MINT31, p14, and WRN) by real-time PCR (MethyLight). RESULTS: Tumoral DNMT3B overexpression was significantly associated with CIMP-high [> or =6/8 methylated CIMP-specific promoters; odds ratio (OR), 3.34; 95% confidence interval, 2.11-5.29; P < 0.0001]. The relations between DNMT3B and methylation in 16 individual CpG islands varied substantially (OR, 0.80-2.96), suggesting variable locus-to-locus specificities of DNMT3B activity. DNMT3B expression was not significantly related with LINE-1 hypomethylation. In multivariate logistic regression, the significant relation between DNMT3B and CIMP-high persisted (OR, 2.39; 95% confidence interval, 1.11-5.14; P = 0.026) after adjusting for clinical and other molecular features, including p53, beta-catenin, LINE-1, microsatellite instability, KRAS, PIK3CA, and BRAF. DNMT3B expression was unrelated with patient outcome, survival, or prognosis. CONCLUSIONS: Tumoral DNMT3B overexpression is associated with CIMP-high in colorectal cancer. Our data support a possible role of DNMT3B in nonrandom de novo CpG island methylation leading to colorectal 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 | 0.000 | 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".