MEF2B mutations in non-Hodgkin lymphoma dysregulate cell migration by decreasing MEF2B target gene activation
Bibliographic record
Abstract
Myocyte enhancer factor 2B (MEF2B) is a transcription factor with mutation hotspots at K4, Y69 and D83 in diffuse large B-cell lymphoma (DLBCL). To provide insight into the regulatory network of MEF2B, in this study, we analyse global gene expression and DNA-binding patterns. We find that candidate MEF2B direct target genes include RHOB, RHOD, CDH13, ITGA5 and CAV1, and that indirect target genes of MEF2B include MYC, TGFB1, CARD11, MEF2C, NDRG1 and FN1. MEF2B overexpression increases HEK293A cell migration and epithelial-mesenchymal transition, and decreases DLBCL cell chemotaxis. K4E, Y69H and D83V MEF2B mutations decrease the capacity of MEF2B to activate transcription and decrease its' effects on cell migration. The K4E and D83V mutations decrease MEF2B DNA binding. In conclusion, our map of the MEF2B regulome connects MEF2B to drivers of oncogenesis.
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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) | 0.002 | 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".