Mutations in UBA3 Confer Resistance to the NEDD8-Activating Enzyme Inhibitor MLN4924 in Human Leukemic Cells
Bibliographic record
Abstract
The NEDD8-activating enzyme (NAE) initiates neddylation, the cascade of post-translational NEDD8 conjugation onto target proteins. MLN4924, a selective NAE inhibitor, has displayed preclinical anti-tumor activity in vitro and in vivo, and promising clinical activity has been reported in patients with refractory hematologic malignancies. Here, we sought to understand the mechanisms of resistance to MLN4924. K562 and U937 leukemia cells were exposed over a 6 month period to MLN4924 and populations of resistant cells (R-K562(MLN), R-U937(MLN)) were selected. R-K562(MLN) and R-U937(MLN) cells contain I310N and Y352H mutations in the NAE catalytic subunit UBA3, respectively. Biochemical analyses indicate that these mutations increase the enzyme's affinity for ATP while decreasing its affinity for NEDD8. These mutations effectively contribute to decreased MLN4924 potency in vitro while providing for sufficient NAE function for leukemia cell survival. Finally, R-K562(MLN) cells showed cross-resistance to other NAE-selective inhibitors, but remained sensitive to a pan-E1 (activating enzyme) inhibitor. Thus, our work provides insight into mechanisms of MLN4924 resistance to facilitate the development of more effective second-generation NAE inhibitors.
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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 | 0.001 |
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".