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Exploring differentially expressed lncRNAs between the osteosarcoma and adjacent normal tissues using RNA-Seq method

ABSTRACT: Osteosarcoma is one of the most commonly primary malignant tumors of bone, and the five-year survival rate for osteosarcoma patients is not satisfactory. Dysregulations of lncRNAs are frequently found in multiple cancers, including osteosarcoma, and these data reveal the critical involvement of lncRNAs in the tumorigenesis. Osteosarcoma tissues and adjacent normal tissues for controls were obtained and analyzed by high-throughput sequencing. Our data showed that hundreds of lncRNAs were identified, with LINC00673 ranking first among all the up-regulated lncRNAs. This study suggests that different expressions of lncRNAs may involve in the potential function in osteosarcoma and provide a novel insight for diagnosis of this disease.

ORGANISM(S): Homo sapiens

PROVIDER: GSE309091 | GEO | 2026/01/01

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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Exploring differentially expressed lncRNAs between the osteosarcoma and adjacent normal tissues using RNA-Seq method

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