Epigenetic Silencing of DKK3 in Medulloblastoma
Bibliographic record
Abstract
Medulloblastoma (MB) is a malignant pediatric brain tumor arising in the cerebellum consisting of four distinct subgroups: WNT, SHH, Group 3 and Group 4, which exhibit different molecular phenotypes. We studied the expression of Dickkopf (DKK) 1-4 family genes, inhibitors of the Wnt signaling cascade, in MB by screening 355 expression profiles derived from four independent datasets. Upregulation of DKK1, DKK2 and DKK4 mRNA was observed in the WNT subgroup, whereas DKK3 was downregulated in 80% MBs across subgroups with respect to the normal cerebellum (p < 0.001). Since copy number aberrations targeting the DKK3 locus (11p15.3) are rare events, we hypothesized that epigenetic factors could play a role in DKK3 regulation. Accordingly, we studied 77 miRNAs predicting to repress DKK3; however, no significant inverse correlation between miRNA/mRNA expression was observed. Moreover, the low methylation levels in the DKK3 promoters (median: 3%, 5% and 5% for promoter 1, 2 and 3, respectively) excluded the downregulation of gene expression by methylation. On the other hand, the treatment of MB cells with Trichostatin A (TSA), a potent inhibitor of histone deacetylases (HDAC), was able to restore both DKK3 mRNA and protein. In conclusion, DKK3 downregulation across all MB subgroups may be due to epigenetic mechanisms, in particular, through chromatin condensation.
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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 | 0.000 | 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) | 0.000 | 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".