Genomically Complex Human Angiosarcoma and Canine Hemangiosarcoma Establish Convergent Angiogenic Transcriptional Programs Driven by Novel Gene Fusions
Bibliographic record
Abstract
Abstract Sporadic angiosarcomas are aggressive vascular sarcomas whose rarity and genomic complexity present significant obstacles in deciphering the pathogenic significance of individual genetic alterations. Numerous fusion genes have been identified across multiple types of cancers, but their existence and significance remain unclear in sporadic angiosarcomas. In this study, we leveraged RNA-sequencing data from 13 human angiosarcomas and 76 spontaneous canine hemangiosarcomas to identify fusion genes associated with spontaneous vascular malignancies. Ten novel protein-coding fusion genes, including TEX2-PECAM1 and ATP8A2-FLT1, were identified in seven of the 13 human tumors, with two tumors showing mutations of TP53. HRAS and NRAS mutations were found in angiosarcomas without fusions or TP53 mutations. We found 15 novel protein-coding fusion genes including MYO16-PTK2, GABRA3-FLT1, and AKT3-XPNPEP1 in 11 of the 76 canine hemangiosarcomas; these fusion genes were seen exclusively in tumors of the angiogenic molecular subtype that contained recurrent mutations in TP53, PIK3CA, PIK3R1, and NRAS. In particular, fusion genes and mutations of TP53 cooccurred in tumors with higher frequency than expected by random chance, and they enriched gene signatures predicting activation of angiogenic pathways. Comparative transcriptomic analysis of human angiosarcomas and canine hemangiosarcomas identified shared molecular signatures associated with activation of PI3K/AKT/mTOR pathways. Our data suggest that genome instability induced by TP53 mutations might create a predisposition for fusion events that may contribute to tumor progression by promoting selection and/or enhancing fitness through activation of convergent angiogenic pathways in this vascular malignancy. Implications: This study shows that, while drive events of malignant vasoformative tumors of humans and dogs include diverse mutations and stochastic rearrangements that create novel fusion genes, convergent transcriptional programs govern the highly conserved morphologic organization and biological behavior of these tumors in both species.
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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 | 0.000 | 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) | 0.001 | 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".