Application of Mass Spectrometry Profiling to Establish Brusatol as an Inhibitor of Global Protein Synthesis
Bibliographic record
Abstract
The KEAP1/Nrf2 pathway senses and responds to changes in intracellular oxidative stress. Mutations that result in constitutive activation of Nrf2 are present in several human tumors, especially non-small cell lung cancer. Therefore, compounds that inhibit Nrf2 activity might be beneficial in treating patients whose tumors show activation of this pathway. Recent reports suggest that the natural product brusatol can potently and selectively inhibit Nrf2 activity, resulting in cell cytotoxicity, and can be effectively combined with chemotherapeutic agents. Here, we analyzed the effects of brusatol on the cellular proteome in the KEAP1 mutant non-small cell lung cancer cell line A549. Brusatol was found to rapidly and potently decrease the expression of the majority of detected proteins, including Nrf2. The most dramatically decreased proteins are those that display a short half-life, like Nrf2. This effect was confirmed by restricting the analysis to newly synthesized proteins using a labeled methionine analogue. Moreover, brusatol increased the expression of multiple components of the ribosome, suggesting that it regulates the function of this macromolecular complex. Finally, we show that brusatol induces its potent cellular cytotoxicity effects on multiple cancer cell lines in a manner independent of KEAP1/Nrf2 activity and with a profile similar to the protein translation inhibitor silvestrol. In conclusion, our data show that the activity of brusatol is not restricted to Nrf2 but, rather, functions as a global protein synthesis inhibitor.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".