MNDA controls the expression of MCL-1 and BCL-2 in chronic lymphocytic leukemia cells
Bibliographic record
Abstract
The myeloid nuclear differentiation antigen (MNDA) is a stress-induced protein that promotes degradation of the anti-apoptotic factor MCL-1 and apoptosis in myeloid cells. MNDA is also expressed in normal lymphoid cells and in B-cell clones isolated from individuals with chronic lymphocytic leukemia (CLL), a disease characterized by abnormal apoptosis control. We found that MNDA expression levels inversely correlate with the amount of the anti-apoptotic proteins MCL-1 and BCL-2 in human CLL samples. We report that in response to chemotherapeutic agents that induce genotoxic stress, MNDA exits its typical nucleolar localization and accumulates in the nucleoplasm of CLL and lymphoid cells. Then, MNDA binds chromatin at Mcl1 and Bcl2 genes and affects the transcriptional competence of RNA polymerase II. Our data also reveal that MNDA specifically associates with Mcl1 and Bcl2 (pre-) mRNAs and favors their rapid turnover as a prompt response to genotoxic stress. We propose that this rapid dynamic tuning of RNA levels, which leads to the destabilization of Mcl1 and Bcl2 transcripts, represents a post-transcriptional mechanism of apoptosis control in CLL cells. These results provide an explanation of previous clinical data and corroborate the finding that higher MNDA expression levels in CLL are associated with a better clinical course.
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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 | 0.001 | 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".