The ubiquitin-conjugating enzyme UBE2O modulates c-Maf stability and induces myeloma cell apoptosis
Bibliographic record
Abstract
BACKGROUND: UBE2O is proposed as a ubiquitin-conjugating enzyme, but its function was largely unknown. METHODS: Mass spectrometry was applied to identify c-Maf ubiquitination-associated proteins. Immunoprecipitation was applied for c-Maf and UBE2O interaction. Immunoblotting was used for Maf protein stability. Luciferase assay was used for c-Maf transcriptional activity. Lentiviral infections were applied for UBE2O function in multiple myeloma (MM) cells. Flow cytometry and nude mice xenografts were applied for MM cell apoptosis and tumor growth assay, respectively. RESULTS: UBE2O was found to interact with c-Maf, a critical transcription factor in MM, by the affinity purification/tandem mass spectrometry assay and co-immunoprecipitation assays. Subsequent studies showed that UBE2O mediated c-Maf polyubiquitination and degradation. Moreover, UBE2O downregulated the transcriptional activity of c-Maf and the expression of cyclin D2, a typical gene modulated by c-Maf. DNA microarray revealed that UBE2O was expressed in normal bone marrow cells but downregulated in MGUS, smoldering MM and MM cells, which was confirmed by RT-PCR in primary MM cells, suggesting its potential role in myeloma pathophysiology. When UBE2O was restored, c-Maf protein in MM cells was significantly decreased and MM cells underwent apoptosis. Furthermore, the human MM xenograft in nude mice showed that re-expression of UBE2O delayed the growth of myeloma xenografts in nude mice in association with c-Maf downregulation and activation of the apoptotic pathway. CONCLUSIONS: UBE2O mediates c-Maf polyubiquitination and degradation, induces MM cell apoptosis, and suppresses myeloma tumor growth, which provides a novel insight in understanding myelomagenesis and UBE2O biology.
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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".