Proximal and Classic Epithelioid Sarcomas are Distinct Molecular Entities Defined by MYC/GATA3 and SOX17/Endothelial Markers, Respectively
Bibliographic record
Abstract
Epithelioid sarcoma (ES) is a rare tumor hallmarked by the loss of INI1/SMARCB1 expression. Apart from this alteration, little is known about the biology of ES. Despite recent advances in treatment, the prognosis of ES remains unsatisfactory. To elucidate the molecular underpinnings of ES, and to identify diagnostic biomarkers and potential therapeutic vulnerabilities, we performed an integrated omics profiling (RNA sequencing and methylation array) of 24 primary, untreated ESs. Transcriptome and methylome analysis identified 2 distinct molecular clusters that essentially corresponded to the morphologic variants of ES, classic ES (C-ES) and the more aggressive proximal ES (P-ES). The P-ES group was characterized by hyperactivation of GATA3 and MYC pathways, with extensive epigenetic rewiring associated with EZH2 overexpression. Both DNA methylation and gene expression analysis indicated a striking similarity with the "MYC subgroup" of atypical teratoid/rhabdoid tumor, another SMARCB1-deficient tumor, implying a shared molecular background and potential therapeutic vulnerabilities. Conversely, the C-ES group exhibited an endothelial-like molecular profile, with expression of vascular genes and elevated proangiogenic SOX17 signaling. Immunohistochemistry validated the overexpression of the chromatin regulators GATA3 (9/12 vs 0/16) and EZH2 (7/7 vs 2/6) in P-ESs, and of the vascular factors SOX17 (8/8 vs 1/10) and N-cadherin (5/9 vs 0/10) in C-ESs. Therefore, these molecules emerge as potential diagnostic tools to fill the gap represented by the lack of ES subtype-specific biomarkers. In summary, our study shows that P-ES and C-ES represent distinct molecular entities defined by MYC/GATA3 and SOX17/endothelial molecular traits, respectively. Besides providing insights into the biology of ES, our study pinpoints subtype-specific biomarkers and potential therapeutic vulnerabilities.
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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 | 0.000 |
| 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".