Abstract A13: Genome-wide transcriptional analysis of HDAC inhibition-induced apoptosis in synovial sarcoma
Bibliographic record
Abstract
Abstract Introduction: Conventional cytotoxic therapies for synovial sarcoma provide limited benefit, and no drugs specifically targeting its driving SS18-SSX fusion oncoprotein are currently available. HDAC inhibition has been shown in previous studies to disrupt the driving complex implicated in synovial sarcoma, resulting in apoptosis induction. Methods: Transcriptome analysis was undertaken in a panel of six human synovial sarcoma cell lines in order to uncover potential mechanisms of cell death following HDAC inhibition. By comparison studies with five additional publicly available related expression datasets, common class effects resulting from HDAC inhibition were investigated. Five human synovial sarcoma tumor samples were profiled by RNA-seq for comparison. A mouse model of synovial sarcoma was treated by HDAC inhibition and tumors were profiled for apoptotic markers. Results: Cell cycle arrest, differentiation, and response to oxygen-containing species and cell death were common biologic responses among the panel of post-HDAC inhibitor expression studies. Specific to synovial sarcoma, reactivation of repressed tumor suppressor CDKN2A and induction of proapoptotic transcriptional patterns results in apoptosis and decreased tumor burden in vivo. Conclusion: HDAC inhibition impedes SS18-SSX-mediated transcriptional deregulation, allowing for reactivation of normal cell cycle regulatory and apoptotic pathways. This study provides mechanistic support for a particular susceptibility of synovial sarcoma to HDAC inhibition as a means of potential clinical treatment. Citation Format: Aimee N. Laporte, Neal M. Poulin, Alireza Lorzadeh, Xiu Qing Wang, Ryan Vander werff, Jared J. Barrott, Michelle Moska, Christopher Hughes, Gregg Morin, Kevin B. Jones, Martin Hirst, T. Michael Underhill, Torsten O. Nielsen. Genome-wide transcriptional analysis of HDAC inhibition-induced apoptosis in synovial sarcoma [abstract]. In: Proceedings of the AACR Conference on Advances in Sarcomas: From Basic Science to Clinical Translation; May 16-19, 2017; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(2_Suppl):Abstract nr A13.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".