Comparative oncology reveals DNMT3B as a molecular vulnerability in soft-tissue sarcoma
Bibliographic record
Abstract
ABSTRACT Undifferentiated pleomorphic sarcoma (UPS), an aggressive subtype of soft-tissue sarcoma (STS), is exceedingly rare in humans and lacks effective, well-tolerated therapies. In contrast, STS are relatively common in canine companion animals; thus, incorporation of veterinary patients into studies of UPS offers an exciting opportunity to develop novel therapeutic strategies for this rare human disease. Genome-wide studies have demonstrated that UPS is characterized by aberrant patterns of DNA methylation. However, the mechanisms and impact of this epigenetic modification on UPS biology and clinical behavior are poorly understood. Leveraging cell lines and tissue specimens derived from human and canine patients, we discovered that the DNA methyltransferase DNMT3B is overexpressed in UPS relative to normal mesenchymal tissues and associated with a poor prognosis. Consistent with these findings, genetic DNMT3B depletion strongly inhibited UPS cell proliferation and tumor progression. However, existing hypomethylating agents, including the clinically approved drug 5-aza-2’-deoxycytidine and the DNMT3B-inhibiting tool compound nanaomycin A, were ineffective in UPS due to cellular uptake and toxicity issues. Thus, further development of DNMT3B-targeting strategies for these patients is critical.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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 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".