Cotargeting CDK4/6 and BRD4 Promotes Senescence and Ferroptosis Sensitivity in Cancer
Bibliographic record
Abstract
Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors are approved for breast cancer treatment and show activity against other malignancies, including KRAS-mutant non-small cell lung cancer (NSCLC). However, the clinical efficacy of CDK4/6 inhibitors is limited due to frequent drug resistance and their largely cytostatic effects. Through a genome-wide cDNA screen, we identified that bromodomain-containing protein 4 (BRD4) overexpression conferred resistance to the CDK4/6 inhibitor palbociclib in KRAS-mutant NSCLC cells. Inhibition of BRD4, either by RNA interference or small-molecule inhibitors, synergized with palbociclib to induce senescence in NSCLC cells and tumors, and the combination prolonged survival in a KRAS-mutant NSCLC mouse model. Mechanistically, BRD4-inhibition enhanced cell-cycle arrest and reactive oxygen species (ROS) accumulation, both of which are necessary for senescence induction; this in turn elevated GPX4, a peroxidase that suppresses ROS-triggered ferroptosis. Consequently, GPX4 inhibitor treatment selectively induced ferroptotic cell death in the senescent cancer cells, resulting in tumor regression. Cotargeting CDK4/6 and BRD4 also promoted senescence and ferroptosis vulnerability in pancreatic and breast cancer cells. Together, these findings reveal therapeutic vulnerabilities and effective combinations to enhance the clinical utility of CDK4/6 inhibitors. SIGNIFICANCE: The combination of cytostatic CDK4/6 and BRD4 inhibitors induces senescent cancer cells that are primed for activation of ferroptotic cell death by targeting GPX4, providing an effective strategy for treating cancer.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".