Hemangiosarcoma Cells Promote Conserved Host-derived Hematopoietic Expansion.

Hemangiosarcoma and angiosarcoma are soft-tissue sarcomas of blood vessel-forming cells in dogs and humans, respectively. These vasoformative sarcomas are aggressive and highly metastatic, with disorganized, irregular blood-filled vascular spaces. Our objective was to define molecular programs which support the niche that enables progression of canine hemangiosarcoma and human angiosarcoma. Dog-in-mouse hemangiosarcoma xenografts recapitulated the vasoformative and highly angiogenic morphology and molecular characteristics of primary tumors. Blood vessels in the tumors were complex and disorganized, and they were lined by both donor and host cells. In a series of xenografts, we observed that the transplanted hemangiosarcoma cells created exuberant myeloid hyperplasia and gave rise to lymphoproliferative tumors of mouse origin. Our functional analyses indicate that hemangiosarcoma cells generate a microenvironment that supports expansion and differentiation of hematopoietic progenitor populations. Furthermore, gene expression profiling data revealed hemangiosarcoma cells expressed a repertoire of hematopoietic cytokines capable of regulating the surrounding stromal cells. We conclude that canine hemangiosarcomas, and possibly human angiosarcomas, maintain molecular properties that provide hematopoietic support and facilitate stromal reactions, suggesting their potential involvement in promoting the growth of hematopoietic tumors. SIGNIFICANCE: We demonstrate that hemangiosarcomas regulate molecular programs supporting hematopoietic expansion and differentiation, providing insights into their potential roles in creating a permissive stromal-immune environment for tumor progression.

Genomically Complex Human Angiosarcoma and Canine Hemangiosarcoma Establish Convergent Angiogenic Transcriptional Programs Driven by Novel Gene Fusions.

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.

Machine learning application identifies novel gene signatures from transcriptomic data of spontaneous canine hemangiosarcoma.

Angiosarcomas are soft-tissue sarcomas that form malignant vascular tissues. Angiosarcomas are very rare, and due to their aggressive behavior and high metastatic propensity, they have poor clinical outcomes. Hemangiosarcomas commonly occur in domestic dogs, and share pathological and clinical features with human angiosarcomas. Typical pathognomonic features of this tumor are irregular vascular channels that are filled with blood and are lined by a mixture of malignant and nonmalignant endothelial cells. The current gold standard is the histological diagnosis of angiosarcoma; however, microscopic evaluation may be complicated, particularly when tumor cells are undetectable due to the presence of excessive amounts of nontumor cells or when tissue specimens have insufficient tumor content. In this study, we implemented machine learning applications from next-generation transcriptomic data of canine hemangiosarcoma tumor samples (n = 76) and nonmalignant tissues (n = 10) to evaluate their training performance for diagnostic utility. The 10-fold cross-validation test and multiple feature selection methods were applied. We found that extra trees and random forest learning models were the best classifiers for hemangiosarcoma in our testing datasets. We also identified novel gene signatures using the mutual information and Monte Carlo feature selection method. The extra trees model revealed high classification accuracy for hemangiosarcoma in validation sets. We demonstrate that high-throughput sequencing data of canine hemangiosarcoma are trainable for machine learning applications. Furthermore, our approach enables us to identify novel gene signatures as reliable determinants of hemangiosarcoma, providing significant insights into the development of potential applications for this vascular malignancy.