The epigenetic mechanism involved in MBD2-mediated induction of interleukin-33
Bibliographic record
Abstract
Il-33, the most recently discovered member of the il-1 family of cytokines, is mainly expressed by fibroblasts, epithelial cells, and endothelial cells and signals via the ST2 receptor to promote Th2 type immune responses. This newly discovered cytokine has a well established role in airways inflammation, most notably asthma, and is involved in a wide range of diseases such a s atherosclerosis and atopic dermatitis, but its role in cancer remains unknown. Previous studies in our lab have demonstrated that expression of ectopic MBD2 transforms mouse fibroblasts NIH3T3 cells into highly invasive metastatic cancerous cells. Il-33 is the top gene induced by upregulation of the putative DNA demethylase MBD2 suggesting an undiscovered role of this new cytokine in tumorigenesis. The aim of this thesis is to assess the mechanisms underlying MBD2-mediated induction of il-33. We identify here using high-density tiling arrays with a combination of mDIP and ChIP-on-chip a regulatory region of il-33 which is partially demethylated by increasing the levels of methylated DNA binding protein domain 2 (MBD2) in the cell. Luciferase reporter assays confirm that this region bearing promoter activity is silenced upon in vitro methylation as well as show MBD2-dependent activation of a reporter gene. We further demonstrate using bisulfite pyrosequencing that similar methylation patterns are observed in murine tissues and cell types expressing il-33. Taken all together, our data suggest that il-33 is silenced by DNA methylation and activated by MBD2 triggering cell transformation and invasion. Thus, the new mechanism of il-33 regulation discovered in our studies might have important therapeutic implications in cancer growth and metastasis.
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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) | 0.001 | 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".