A novel microtubule inhibitor promotes tumor ferroptosis by attenuating SLC7A11/GPX4 signaling
Bibliographic record
Abstract
MP-HJ-1b is a novel microtubule inhibitor that we designed and reported previously. Ferroptosis is a newly identified type of nonapoptotic cell death induced by ferrous catalysis and lipid peroxidation. Here, transcriptomics, proteomics, and molecular docking analyses were combined to explore the novel effects of MP-HJ-1b on tumors. Both omics analyses suggested that MP-HJ-1b affects ribosomes, and we confirmed that it inhibits the ribosomal component proteins RPL35 and MRPL28. Colchicine was used as an analog, and the results showed that MP-HJ-1b and colchicine increased reactive oxygen species and malondialdehyde levels and decreased reduced glutathione levels, suggesting that they promoted ferroptosis in HeLa cells. Specifically, MP-HJ-1b downregulated SLC7A11 and GPX4 to enhance the classical pathway of ferroptosis, while colchicine upregulated LC3A/B-II and enhanced autophagy. Clinically, the serum concentrations of ferrous ions, reduced glutathione, and Hcy were higher in cervical cancer patients than in healthy individuals. ALT, AST, Cho, HDL-C, and LDL-C levels were decreased in the serum of patients. Our study expands understanding of the way MP-HJ-1b promotes cell death and enriches research on microtubule inhibitors in the ferroptosis field.
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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".