HDAC and Proteasome Inhibitors Synergize to Activate Pro-Apoptotic Factors in Synovial Sarcoma
Bibliographic record
Abstract
Conventional cytotoxic therapies for synovial sarcoma provide limited benefit, and no drugs specifically targeting its driving SS18-SSX fusion oncoprotein are currently available. Patients remain at high risk for early and late metastasis. A high-throughput drug screen consisting of over 900 tool compounds and epigenetic modifiers, representing over 100 drug classes, was undertaken in a panel of synovial sarcoma cell lines to uncover novel sensitizing agents and targetable pathways. Top scoring drug categories were found to be HDAC inhibitors and proteasomal targeting agents. We find that the HDAC inhibitor quisinostat disrupts the SS18-SSX driving protein complex, thereby reestablishing expression of EGR1 and CDKN2A tumor suppressors. In combination with proteasome inhibition, HDAC inhibitors synergize to decrease cell viability and elicit apoptosis. Quisinostat inhibits aggresome formation in response to proteasome inhibition, and combination treatment leads to elevated endoplasmic reticulum stress, activation of pro-apoptotic effector proteins BIM and BIK, phosphorylation of BCL-2, increased levels of reactive oxygen species, and suppression of tumor growth in a murine model of synovial sarcoma. This study identifies and provides mechanistic support for a particular susceptibility of synovial sarcoma to the combination of quisinostat and proteasome inhibition.
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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 | 0.001 |
| 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".