CRISPR activation screens identify the SWI/SNF ATPases as suppressors of ferroptosis
Bibliographic record
Abstract
Ferroptosis is an iron-dependent cell death mechanism characterized by the accumulation of toxic lipid peroxides and cell membrane rupture. GPX4 (glutathione peroxidase 4) prevents ferroptosis by reducing these lipid peroxides into lipid alcohols. Ferroptosis induction by GPX4 inhibition has emerged as a vulnerability of cancer cells, highlighting the need to identify ferroptosis regulators that may be exploited therapeutically. Through genome-wide CRISPR activation screens, we identify the SWI/SNF (switch/sucrose non-fermentable) ATPases BRM (SMARCA2) and BRG1 (SMARCA4) as ferroptosis suppressors. Mechanistically, they bind to and increase chromatin accessibility at NRF2 target loci, thus boosting NRF2 transcriptional output to counter lipid peroxidation and confer resistance to GPX4 inhibition. We further demonstrate that the BRM/BRG1 ferroptosis connection can be leveraged to enhance the paralog dependency of BRG1 mutant cancer cells on BRM. Our data reveal ferroptosis induction as a potential avenue for broadening the efficacy of BRM degraders/inhibitors and define a specific genetic context for exploiting GPX4 dependency.
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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".