Integrative Single-cell and Spatial Transcriptomic Analysis of Osteosarcoma Reveals Conserved and Distinct Ecosystems Across Sites and Species

Abstract Osteosarcoma is a heterogeneous malignancy, exhibiting significant variability among patients, individual cancer cells within a tumor, and the stromal cells that compose primary and metastatic lesions. To facilitate the study of this complex disease, we compiled a unique cross-species single-cell transcriptomic dataset totaling over a million cells/nuclei from human specimens, canine specimens, patient-derived xenografts/PDX, and syngeneic mouse models at both primary (bone) and metastatic (lung) sites. Using a rigorous process for multi-species alignment and annotation, we identified six conserved tumor cell transcriptional states organized along hierarchical differentiation trajectories from progenitor to differentiated phenotypes. Parallel analysis of tumor-associated cells identified conserved macrophage, fibroblast, and endothelial populations that exhibit species– and site-specific reprogramming. Validation by mapping cell types using spatial transcriptomics revealed structured neighborhood architectures that were reproduced across multiple samples. Cell-cell interaction analysis revealed similarities and differences in tumor-host networks across primary and metastatic sites and across species. This analysis enabled pathway-specific assessment of tumor-host communication fidelity across osteosarcoma model systems relative to humans, revealing canine osteosarcoma as a more faithful model. Metastatic lung lesions, counterintuitively, exhibited more intense and complex extracellular matrix (ECM) signaling than primary bone tumors. A key example was tumor-derived fibronectin (FN1), which engages integrin and syndecan receptors on lung epithelial cells, driving a pathological mesenchymal and profibrotic state that promotes fibrotic niche formation and metastatic lung colonization. Together, this cross-species resource delineates both conserved and divergent tumor microenvironment programs, demonstrates how model-aware analyses uncover previously unrecognized tumor-host interactions, and underscores the need for therapies that co-target tumor heterogeneity and its supportive metastatic niche. Statement of Significance We show that the tumor microenvironment in human osteosarcoma patients has biological phenotypes that are conserved across both patients and species. This points towards underlying molecular mechanisms that could be therapeutically targeted. Competing Interest Statement The authors have declared no competing interest. Footnotes Revised and reorganized figures and text.