Loss of the SMRT/NCoR2 Corepressor Correlates with JAG2 Overexpression in Multiple Myeloma
Bibliographic record
Abstract
Multiple myeloma (MM) is a clonal B-cell neoplasm that accounts for 10% of all malignant hematologic neoplasms and that affects terminally differentiated B cells (i.e., plasma cells). It is now well recognized that the cytokine interleukin-6 (IL-6) is a major cytokine that promotes the proliferation of malignant plasma cells in MM. The IL-6 gene can be regulated by the NOTCH genes products. We have previously shown that the NOTCH ligand, JAG2, is overexpressed in MM. To investigate the mechanism(s) leading to JAG2 overexpression in MM, we assessed potential epigenetic modifications of the JAG2 promoter. We showed that the JAG2 promoter region is aberrantly acetylated in MM cell lines and patient samples. The acetylation state of histones is regulated by the recruitment of histone deacetylases (HDAC). HDACs are typically recruited to promoter regions through interaction with nuclear corepressors such as SMRT. SMRT levels were therefore investigated. Interestingly, MM cell lines and patient samples presented significantly reduced SMRT levels. The experiments suggest a correlation between constitutive acetylation of the JAG2 core promoter in the MM cell lines and reduced levels of the SMRT corepressor that recruits HDAC to promoter regions. Finally, SMRT function restoration induced JAG2 down-regulation as well as MM cell apoptosis.
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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 | 0.001 |
| 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".