Inhibiting neddylation modification alters mitochondrial morphology and reprograms energy metabolism in cancer cells
Bibliographic record
Abstract
Abnormal activation of neddylation modification and dysregulated energy metabolism are frequently seen in many types of cancer cells. Whether and how neddylation modification affects cellular metabolism remains largely unknown. Here, we showed that MLN4924, a small-molecule inhibitor of neddylation modification, induces mitochondrial fission-to-fusion conversion in breast cancer cells via inhibiting ubiquitylation and degradation of fusion-promoting protein mitofusin 1 (MFN1) by SCFβ-TrCP E3 ligase and blocking the mitochondrial translocation of fusion-inhibiting protein DRP1. Importantly, MLN4924-induced mitochondrial fusion is independent of cell cycle progression, but confers cellular survival. Mass-spectrometry-based metabolic profiling and mitochondrial functional assays reveal that MLN4924 inhibits the TCA cycle but promotes mitochondrial OXPHOS. MLN4924 also increases glycolysis by activating PKM2 via promoting its tetramerization. Biologically, MLN4924 coupled with the OXPHOS inhibitor metformin, or the glycolysis inhibitor shikonin, significantly inhibits cancer cell growth both in vitro and in vivo. Together, our study links neddylation modification and energy metabolism, and provides sound strategies for effective combined cancer therapies.
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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".