EZH2 Cooperates with BRD4-NUT to Drive NUT Carcinoma Growth by Silencing Key Tumor Suppressor Genes
Bibliographic record
Abstract
NUT carcinoma is an aggressive carcinoma driven by the BRD4-NUT fusion oncoprotein, which activates chromatin to promote expression of progrowth genes. BET bromodomain inhibitors (BETi) are a promising treatment for NUT carcinoma that can impede BRD4-NUT's ability to activate genes, but the efficacy of BETi as monotherapy is limited. Here, we demonstrated that enhancer of zeste homolog 2 (EZH2), which silences genes through establishment of repressive chromatin, is a dependency in NUT carcinoma. Inhibition of EZH2 with the clinical compound tazemetostat potently blocked growth of NUT carcinoma cells. Epigenetic and transcriptomic analysis revealed that tazemetostat reversed the EZH2-specific H3K27me3 silencing mark and restored expression of multiple tumor suppressor genes while having no effect on key oncogenic BRD4-NUT-regulated genes. Indeed, H3K27me3 and H3K27ac domains were found to be mutually exclusive in NUT carcinoma cells. CDKN2A was identified as the only gene among all tazemetostat-derepressed genes to confer resistance to tazemetostat in a CRISPR-Cas9 screen. Combined inhibition of EZH2 and BET synergized to downregulate cell proliferation genes, resulting in more pronounced growth arrest and differentiation than either inhibitor alone. In preclinical models, combined tazemetostat and BETi synergistically blocked tumor growth and prolonged survival of NUT carcinoma-xenografted mice, with complete remission without relapse in one cohort. Identification of EZH2 as a dependency in NUT carcinoma substantiates the reliance of NUT carcinoma tumor cells on epigenetic dysregulation of functionally opposite, yet highly complementary, chromatin regulatory pathways to maintain NUT carcinoma growth. SIGNIFICANCE: Repression of tumor suppressor genes, including CDKN2A, by EZH2 provides a mechanistic rationale for combining EZH2 and BET inhibitors for the clinical treatment of NUT carcinoma. See related commentary by Kazansky and Kentsis, p. 3827.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".