Data from Inhibition of Histone H3K27 Demethylases Inactivates Brachyury (TBXT) and Promotes Chordoma Cell Death
Bibliographic record
Abstract
Abstract Expression of the transcription factor brachyury (TBXT) is normally restricted to the embryo, and its silencing is epigenetically regulated. TBXT promotes mesenchymal transition in a subset of common carcinomas, and in chordoma, a rare cancer showing notochordal differentiation, TBXT acts as a putative oncogene. We hypothesized that TBXT expression is controlled through epigenetic inhibition to promote chordoma cell death. Screening of five human chordoma cell lines revealed that pharmacologic inhibition of the histone 3 lysine 27 demethylases KDM6A (UTX) and KDM6B (JMJD3) leads to cell death. This effect was phenocopied by dual genetic inactivation of KDM6A/B using CRISPR/Cas9. Inhibition of KDM6A/B with a novel compound KDOBA67 led to a genome-wide increase in repressive H3K27me3 marks with concomitant reduction in active H3K27ac, H3K9ac, and H3K4me3 marks. TBXT was a KDM6A/B target gene, and chromatin changes at TBXT following KDOBA67 treatment were associated with a reduction in TBXT protein levels in all models tested, including primary patient-derived cultures. In all models tested, KDOBA67 treatment downregulated expression of a network of transcription factors critical for chordoma survival and upregulated pathways dominated by ATF4-driven stress and proapoptotic responses. Blocking the AFT4 stress response did not prevent suppression of TBXT and induction of cell death, but ectopic overexpression of TBXT increased viability, therefore implicating TBXT as a potential therapeutic target of H3K27 demethylase inhibitors in chordoma. Our work highlights how knowledge of normal processes in fetal development can provide insight into tumorigenesis and identify novel therapeutic approaches. Significance: Pharmacologic inhibition of H3K27-demethylases in human chordoma cells promotes epigenetic silencing of oncogenic TBXT, alters gene networks critical to survival, and represents a potential novel therapy.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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 source (direct Gemma or distilled Codex), 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".