The whole genome landscape of adult metastatic sarcoma.
Bibliographic record
Abstract
3137 Background: Metastatic sarcomas represent a heterogeneous, difficult to treat family of cancers with poor median overall survival of 18 months. While global sequencing initiatives have catalogued genomic variation among primary sarcomas, metastatic sarcoma is less well understood. Genome-guided targeted therapy has made promising advances but is difficult to study in sarcomas due to heterogeneity and low prevalence. Whole genome and transcriptome analysis (WGTA) can help elucidate sarcoma oncogenesis, metastasis, and potential therapeutic targets. Methods: Using whole genome (80X) and transcriptome (200M read) sequencing of 43 metastatic sarcomas across 19 subtypes, we analyzed structural variants (SV), copy-number variants (CNV), mutation signatures, gene expression, and the immune microenvironment. All prior treatments were retrieved through chart review. Results: 17 patients (40%) attempted WGTA-informed therapy, of which 8 (47%) were classified as responders. Metastatic sarcomas demonstrated recurrent CNVs, with 17p11-p12 amplification in 42% of cases. Some recurrent expression outliers were associated with potential targets (e.g. MYOCD, PMP22, COPS3) while others (e.g. ADORA2B) have not been previously observed in sarcoma. Discovery of oncogenic fusions refined diagnoses in two cases with atypical histology. Clustering by mutation signatures distinguished histological subtypes, and two signatures were novel in sarcoma: (1) a strong base excision repair signature associated with NTHL1 loss and (2) a cisplatin-associated signature exclusive to platinum-treated cases. Frequent homologous recombination deficiency was observed and was associated with response to ifosfamide in three leiomyosarcomas. Of four immunotherapy-treated cases, the only responder demonstrated outlier CIBERSORT immune infiltration score, which did not correlate with PD-L1 expression. Conclusions: This is the first in-depth WGTA of metastatic sarcoma. We found recurrent and potentially targetable CNVs, expression outliers, mutation signatures, and immune markers. Our results suggest that clinical translation is promising using actionable insights obtained through WGTA.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".