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Single-Cell Fixed RNA Profiling of Osteosarcoma Evolution Reveals a Coordinated Multi-cellular Network Driving Metastasis

ABSTRACT: Osteosarcoma remains a profound clinical challenge, particularly for patients with metastatic or recurrent disease where survival rates have stagnated for decades. In this study, we present the first systematic application of Single-cell Fixed RNA Profiling (FLEX) to the osteosarcoma clinical spectrum. We profiled over 40,000 cells across treatment-naïve, post-chemotherapy, recurrent, and lung metastatic stages. By identifying the ADAMTS12/RNASE1/S100A4/PLVAP multi-cellular network, we move beyond simple cell-type identification toward an integrated understanding of how malignant cells and their microenvironment co-evolve. These findings offer a translational framework for improved risk stratification and the development of next-generation therapies designed to disrupt the interactive networks supporting metastatic osteosarcoma.

ORGANISM(S): Homo sapiens

PROVIDER: GSE318840 | GEO | 2026/06/30

REPOSITORIES: GEO

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Project description:Purpose: The overall survival rate for metastatic osteosarcoma hovers around 20%. Responses to second-line chemotherapy, targeted therapies, and immunotherapies have demonstrated limited efficacy in metastatic osteosarcoma. Our objective is to validate differentially expressed genes and signaling pathways between non-metastatic and metastatic osteosarcoma, employing single-cell RNA sequencing (scRNA-Seq) and additional functional investigations. We aim to enhance comprehension of metastatic mechanisms and potentially unveil a therapeutic target. Methods: scRNA-Seq was performed on two primary osteosarcoma lesions (1 non-metastatic and 1 metastatic). Uniform manifold approximation and projection (UMAP) facilitated dimensionality reduction and cluster identification. Copy number variation (CNV) was predicted using InferCNV. CellChat characterized ligand-receptor-based intercellular communication networks. Differentially expressed genes underwent GO function enrichment analysis and GSEA. Validation was achieved through the GSE 52048 dataset, which identified PDGFD-PDGFRB as a common ligand-receptor pair with significant contribution. Immunohistochemistry assessed PDGFD and PDGFRB expression, while multicolor immunofluorescence and flow cytometry provided insight into spatial relationships and the tumor immune microenvironment. Kaplan-Meier survival analysis compared metastasis-free survival and overall survival between high and low levels of PDGFD and PDGFRB. Manipulation of PDGFD expression in primary osteosarcoma cells examined invasion abilities and related markers. Results: Ten clusters encompassing osteoblasts, osteoclasts, osteocytes, fibroblasts, pericytes, endothelial cells, myeloid cells, T cells, B cells, and proliferating cells were identified. Osteoblasts, osteoclasts, and osteocytes exhibited heightened CNV levels. Ligand-receptor-based communication networks exposed significant fibroblast crosstalk with other cell types, and the PDGF signaling pathway was activated in non-metastatic osteosarcoma primary lesions. These results were corroborated by the GSE 52048 dataset, confirming the prominence of PDGFD-PDGFRB as a common ligand-receptor pair. Immunohistochemistry demonstrated considerably greater PDGFD expression in non-metastatic osteosarcoma tissue and organoids, correlating with extended metastasis-free and overall survival. PDGFRB expression showed no significant variation between non-metastatic and metastatic osteosarcoma, nor strong correlations with survival times. Multicolor immunofluorescence suggested co-localization of PDGFD with PDGFRB. Flow cytometry unveiled a highly immunosuppressive microenvironment in metastatic osteosarcoma. Manipulating PDGFD expression demonstrated altered invasive abilities and marker expressions in primary osteosarcoma cells from both non-metastatic and metastatic lesions. Conclusions: scRNA-Seq illuminated the activation of the PDGF signaling pathway in primary lesions of non-metastatic osteosarcoma. PDGFD displayed an inhibitory effect on osteosarcoma metastasis, likely through the suppression of the EMT signaling pathway.

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Single-Cell Fixed RNA Profiling of Osteosarcoma Evolution Reveals a Coordinated Multi-cellular Network Driving Metastasis

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