Mule determines the apoptotic response to HDAC inhibitors by targeted ubiquitination and destruction of HDAC2
Bibliographic record
Abstract
Histone deacetylases (HDACs) are major epigenetic modulators involved in a broad spectrum of human diseases including cancers. Administration of HDAC inhibitors (HDACis) leads to growth inhibition, differentiation, and apoptosis of cancer cells. Understanding the regulatory mechanism of HDACs is imperative to harness the therapeutic potentials of HDACis. Here we show that HDACi- and DNA damage-induced apoptosis are severely compromised in mouse embryonic fibroblasts lacking a HECT domain ubiquitin ligase, Mule (Mcl-1 ubiquitin ligase E3). Mule specifically targets HDAC2 for ubiquitination and degradation. Accumulation of HDAC2 in Mule-deficient cells leads to compromised p53 acetylation as well as crippled p53 transcriptional activation, accumulation, and apoptotic response upon DNA damage and Nutlin-3 treatments. These defects in Mule-null cells can be partially reversed by HDACis and fully rescued by lowering the elevated HDAC2 in Mule-null cells to the normal levels as in wild-type cells. Taken together, our results reveal a critical regulatory mechanism of HDAC2 by Mule and suggest this pathway determines the cellular response to HDACis and DNA damage.
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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".