Lipophilic Statins Deplete GPX4 to Promote Ferroptosis and Sensitize Cancer Cells to Immune Checkpoint Blockade
Bibliographic record
Abstract
Statins have been reported to exert anticancer activity, varying with cancer type and specific statins. These findings suggest that more mechanistic insights into the anticancer effects of statins are needed. In this study, we interrogated the ability of statins to induce cell death and ferroptosis in melanoma and colorectal cancer. First, we showed that statins induce cell death in patient-derived melanoma cell lines and that lower expression of mevalonate pathway genes correlates with increased CD8+ T-cell infiltration and improved overall survival in patients with melanoma. We found that lipophilic statins induce cell death with features of ferroptosis. Transcriptional data also revealed system-level changes to a variety of ferroptosis-related pathways. We found that mevalonate rescued statin-induced cell death. Mechanistically, mevalonate-derived isopentyl pyrophosphate is necessary for isopentylation of tRNA [Ser]Sec, which is required for efficient synthesis of the selenoprotein ferroptosis suppressor GPX4. Given the emerging role for ferroptosis in antitumor immunity, we tested lipophilic statins, including simvastatin, alone and in combination with α-PD1 in vivo and found that simvastatin and α-PD1 promoted tumor clearance and extended survival in 20% to 60% of mice alone but in nearly 100% of mice when administered together. Simvastatin also depleted GPX4 in vivo. These results highlight the therapeutic potential of statin use in combination with immunotherapies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".