Osteosarcoma (OS) is a heterogeneous and rare disease with a disproportionate impact because it mainly affects children and adolescents. Lamentably, more than half of patients with OS succumb to metastatic disease. Clarification of the etiology of the disease, development of better strategies to manage progression, and methods to guide personalized treatments are among the unmet health needs for OS patients. Progress in managing the disease has been hindered by the extreme heterogeneity of OS; thus, better models that accurately recapitulate the natural heterogeneity of the disease are needed. For this study, we used cell lines derived from two spontaneous canine OS tumors with distinctly different biological behavior (OS-1 and OS-2) for heterotypic in vivo modeling that recapitulates the heterogeneous biology and behavior of this disease. Both cell lines demonstrated stability of the transcriptome when grown as orthotopic xenografts in athymic nude mice. Consistent with the behavior of the original tumors, OS-2 xenografts grew more rapidly at the primary site and had greater propensity to disseminate to lung and establish microscopic metastasis. Moreover, OS-2 promoted formation of a different tumor-associated stromal environment than OS-1 xenografts. OS-2-derived tumors comprised a larger percentage of the xenograft tumors than OS-1-derived tumors. In addition, a robust pro-inflammatory population dominated the stromal cell infiltrates in OS-2 xenografts, whereas a mesenchymal population with a gene signature reflecting myogenic signaling dominated those in the OS-1 xenografts. Our studies show that canine OS cell lines maintain intrinsic features of the tumors from which they were derived and recapitulate the heterogeneous biology and behavior of bone cancer in mouse models. This system provides a resource to understand essential interactions between tumor cells and the stromal environment that drive the progression and metastatic propensity of OS.
Bibliographical noteFunding Information:
This study was supported by grants from Morris Animal Foundation (D13CA-032 to J.F.M. and D15CA-047 to J.F.M., S.S. and B.A.B.), the American Cancer Society (RSG-13-381-01 to S.S.), Karen Wyckoff Rein in Sarcoma Foundation (2011-1 to J.F.M.), and theComparative Medicine SignatureProgramof theCollege ofVeterinary Medicine, University of Minnesota (to J.F.M., S.S. and B.A.B.). The National Institutes of Health (NIH) Comprehensive Cancer Center Support Grant to the Masonic Cancer Center, University of Minnesota (P30 CA077598) provided support for bioinformatics, genomics, bioimaging and comparative pathology services. J.F.M. is supported by the Alvin and June Perlman Chair in Animal Oncology, University of Minnesota College of Veterinary Medicine. The authors also gratefully acknowledge funds from donors to the Animal Cancer Care and Research Program of the University of Minnesota that helped support the project. The automated RNA-sequence analysis pipeline used for this work was made possible by support from the University of Minnesota Informatics Institute, in collaboration with theUniversity ofMinnesotaGenomicsCenterand the RIS group at the University of Minnesota Supercomputing Institute
© 2016. Published by The Company of Biologists Ltd | Disease Models & Mechanisms.
- Comparative studies
- Heterotypic models
- Tumor-stromal interactions