Combined Targeting of the BRD4–NUT–p300 Axis in NUT Midline Carcinoma by Dual Selective Bromodomain Inhibitor, NEO2734
Bibliographic record
Abstract
Abstract NUT midline carcinoma (NMC) is a rare, aggressive subtype of squamous carcinoma that is driven by the BRD4-NUT fusion oncoprotein. BRD4, a BET protein, binds to chromatin through its two bromodomains, and NUT recruits the p300 histone acetyltransferse (HAT) to activate transcription of oncogenic target genes. BET-selective bromodomain inhibitors have demonstrated on-target activity in patients with NMC, but with limited efficacy. P300, like BRD4, contains a bromodomain. We show that combining selective p300/CBP and BET bromodomain inhibitors, GNE-781 and OTX015, respectively, induces cooperative depletion of MYC and synergistic inhibition of NMC growth. Treatment of NMC cells with the novel dual p300/CBP and BET bromodomain–selective inhibitor, NEO2734, potently inhibits growth and induces differentiation of NMC cells in vitro; findings that correspond with potentiated transcriptional effects from combined BET and p300 bromodomain inhibition. In three disseminated NMC xenograft models, NEO2734 provided greater growth inhibition, with tumor regression and significant survival benefit seen in two of three models, compared with a lead clinical BET inhibitor or “standard” chemotherapy. Our findings provide a strong rationale for clinical study of NEO2734 in patients with NMC. Moreover, the synergistic inhibition of NMC growth by CBP/p300 and BET bromodomain inhibition lays the groundwork for greater mechanistic understanding of the interplay between p300 and BRD4-NUT that drives this 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 | 0.000 | 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".