Double vulnerability of active-NRF2 lung squamous cell carcinoma to NRF2 and TRIM24
Bibliographic record
Abstract
Lung squamous cell cancer (LUSC) is associated with very poor survival due to the lack of specific treatments. A common genetic alteration in LUSC involves mutations in NFE2L2 (protein named NRF2) or its regulator, KEAP1, resulting in increased activity of the NRF2 transcription factor (TF). This study compares the requirement for active-NRF2 in LUSC cell lines. Although normal-NRF2 cells are more sensitive to oxidative stress, they do not require NRF2 for survival under non-stress conditions, in contrast, LUSC cells with active-NRF2 mutations depend on NRF2 for viability. NRF2 depletion in patient-derived organoid cultures with active-NRF2 as well as in xenografts with active-NRF2 triggers cell death. The focus of this study is to find genes that rescue cell death upon NRF2-depletion in active-NRF2 cells. A CRISPRa/dCas9 screening for gene targets capable of rescuing cell survival in these cells identified TRIM24 as a gene whose expression saves cell survival in NRF2-depleted active-NRF2 LUSC cells. Alongside oxidative stress, the lack of TRIM24 selectively contributed to the induction of cell death (apoptosis and ferroptosis) in active-NRF2 LUSC cells. Cells with a high NFE2L2/KEAP1 copy number ratio also undergo cell death. The increase in cell death observed upon TRIM24 depletion involves a reduction of TRIM24/PI3Kα complexes which destabilizes the PI3Kα catalytic subunit. Notably, overexpression of PI3Kα rescues cell survival in TRIM24-depleted active-NRF2 cells. These findings point to novel therapeutic approaches in LUSC.
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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".