Synergism of Heat Shock Protein 90 and Histone Deacetylase Inhibitors in Synovial Sarcoma
Bibliographic record
Abstract
Current systemic therapies have little curative benefit for synovial sarcoma. Histone deacetylase (HDAC) inhibitors and the heat shock protein 90 (Hsp90) inhibitor 17-AAG have recently been shown to inhibit synovial sarcoma in preclinical models. We tested combinations of 17-AAG with the HDAC inhibitor MS-275 for synergism by proliferation and apoptosis assays. The combination was found to be synergistic at multiple time points in two synovial sarcoma cell lines. Previous studies have shown that HDAC inhibitors not only induce cell death but also activate the survival pathway NF-kappaB, potentially limiting therapeutic benefit. As 17-AAG inhibits activators of NF-kappaB, we tested if 17-AAG synergizes with MS-275 through abrogating NF-kappaB activation. In our assays, adding 17-AAG blocks NF-kappaB activation by MS-275 and siRNA directed against histone deacetylase 3 (HDAC3) recapitulates the effects of MS-275. Additionally, we find that the NF-kappaB inhibitor BAY 11-7085 synergizes with MS-275. We conclude that agents inhibiting NF-kappaB synergize with HDAC inhibitors against synovial sarcoma.
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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 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".