Project description:SaOS2 osteosarcoma cells were cultured with or without atorvastatin (10 µM) for 6, 15 or 24h (2 biological replcates). RNA were isolated and hybridized to RNG microarrays. Background Osteosarcoma is the most common primary tumor of bone. The rapid development of metastatic lesions and resistance to chemotherapy remain major mechanisms responsible for the failure of treatments and poor survival rate for patients. Methods We previously showed that the HMGCoA reductase inhibitors statins exhibit anti-tumoral effects on osteosarcoma cells. Here, using microarray analysis, we identify cyr61/CCN1 as a new target of statins. Modulations of expression of cyr61 were performed in human and murine osteosarcoma cell lines to investigate in vitro cell viability, migratory potential and invasiveness. Cyr61 expression was evaluated in 231 tissue cores from osteosarcoma patients using tissue microarray. Tumor behavior and metastases occurence were analysed by IM injection of modified osteosarcoma cells to BALB/c mice. Results Transcriptome comparisons revealed that statins down-regulate cyr61 expression in SaOS2 cells. Cyr61 silencing in human and murine osteosarcoma cell lines enhanced cell death, but reduced cell migration and cell invasion compared to parental cells whereas cyr61 overexpression had opposite effects. Tissue microarray analysis demonstrated that cyr61 protein expression is higher in human osteosarcoma compared to normal bone tissue and is further increased in metastatic tissues. In vivo, cyr61 overexpression in osteosarcoma cells enhanced lung metastases development whereas cyr61 silencing strongly reduced metastases in mice. Conclusion The results reveal that cyr61 expression increases with tumor grade in human osteosarcoma and demonstrate that cyr61 silencing inhibits in vitro osteosarcoma cell invasion and migration as well as in vivo lung metastases in mice. These data provide a novel molecular target for therapeutic intervention in metastatic osteosarcoma. Dye balance-experiment comparing atorvastatin versus untreated cells at 6, 15 and 24 hours using 2 biological replicates.

Project description:SaOS2 osteosarcoma cells were cultured with or without atorvastatin (10 µM) for 6, 15 or 24h (2 biological replcates). RNA were isolated and hybridized to RNG microarrays. Background Osteosarcoma is the most common primary tumor of bone. The rapid development of metastatic lesions and resistance to chemotherapy remain major mechanisms responsible for the failure of treatments and poor survival rate for patients. Methods We previously showed that the HMGCoA reductase inhibitors statins exhibit anti-tumoral effects on osteosarcoma cells. Here, using microarray analysis, we identify cyr61/CCN1 as a new target of statins. Modulations of expression of cyr61 were performed in human and murine osteosarcoma cell lines to investigate in vitro cell viability, migratory potential and invasiveness. Cyr61 expression was evaluated in 231 tissue cores from osteosarcoma patients using tissue microarray. Tumor behavior and metastases occurence were analysed by IM injection of modified osteosarcoma cells to BALB/c mice. Results Transcriptome comparisons revealed that statins down-regulate cyr61 expression in SaOS2 cells. Cyr61 silencing in human and murine osteosarcoma cell lines enhanced cell death, but reduced cell migration and cell invasion compared to parental cells whereas cyr61 overexpression had opposite effects. Tissue microarray analysis demonstrated that cyr61 protein expression is higher in human osteosarcoma compared to normal bone tissue and is further increased in metastatic tissues. In vivo, cyr61 overexpression in osteosarcoma cells enhanced lung metastases development whereas cyr61 silencing strongly reduced metastases in mice. Conclusion The results reveal that cyr61 expression increases with tumor grade in human osteosarcoma and demonstrate that cyr61 silencing inhibits in vitro osteosarcoma cell invasion and migration as well as in vivo lung metastases in mice. These data provide a novel molecular target for therapeutic intervention in metastatic osteosarcoma.

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.

Project description:Purpose: Lung metastasis is responsible for nearly all deaths caused by osteosarcoma, the most common pediatric bone tumor. How malignant bone cells coerce the lung microenvironment to support metastatic growth is unclear. This study delineates how osteosarcoma cells educate the lung microenvironment during metastatic progression. Experimental design: Using single-cell transcriptomics (scRNA-seq), we characterized genome- and tissue-wide molecular changes induced within lung tissues by disseminated osteosarcoma cells in both immunocompetent murine models of metastasis and patient samples. We confirmed transcriptomic findings at the protein level and determined spatial relationships with multi-parameter immunofluorescence. We evaluated the ability of nintedanib to impair metastatic colonization and prevent osteosarcoma-induced education of the lung microenvironment in both immunocompetent murine osteosarcoma and immunodeficient human xenograft models. Results: Osteosarcoma cells induced acute alveolar epithelial injury upon lung dissemination. scRNA-seq demonstrated that the surrounding lung stroma adopts a chronic, non-resolving wound-healing phenotype similar to that seen in other models of lung injury. Accordingly, metastasis-associated lung demonstrated marked fibrosis, likely due to the accumulation of pathogenic, pro-fibrotic, partially-differentiated epithelial intermediates. Inhibitionintermediates. Inhibition of fibrotic pathways with nintedanib prevented metastatic progression in multiple murine and human xenograft models. Conclusions: Our work demonstrates that osteosarcoma cells co-opt fibrosis to promote metastatic outgrowth. When harmonized with data from adult epithelial cancers, our results support a generalized model wherein aberrant mesenchymal-epithelial interactions are critical for promoting lung metastasis. Adult epithelial carcinomas induce fibrotic pathways in normal lung fibroblasts, whereas osteosarcoma, a pediatric mesenchymal tumor, exhibits fibrotic reprogramming in response to the aberrant wound-healing behaviors of an otherwise normal lung epithelium, which are induced by tumor cell interactions.

Project description:High-grade osteosarcoma is a tumor with a complex genomic profile, occurring primarily in adolescents with a second peak at middle age. The extensive genomic alterations obscure the identification of genes driving tumorigenesis during osteosarcoma development. In order to identify such driver genes, we integrated DNA copy number profiles (Affymetrix SNP 6.0) of 32 diagnostic biopsies with 84 expression profiles (Illumina Human-6 v2.0) of high-grade osteosarcoma as compared with its putative progenitor cells, i.e. mesenchymal stem cells (n=12) or osteoblasts (n=3). In addition, we performed paired analyses between copy number and expression profiles of a subset of 29 patients for which both DNA and mRNA profiles were available. Integrative analyses were performed in Nexus Copy Number software and statistical language R. Paired analyses were performed on all probes detecting significantly differentially expressed genes in corresponding LIMMA analyses. For both non-paired and paired analyses, copy number aberration frequency was set to >35%. Non-paired and paired integrative analyses resulted in 45 and 101 genes, respectively, which were present in both analyses using different control sets. Paired analyses detected >90% of all genes found with the corresponding non-paired analyses. Remarkably, approximately twice as many genes as found in the corresponding non-paired analyses were detected. Affected genes were intersected with differentially expressed genes in osteosarcoma cell lines, resulting in 31 new osteosarcoma driver genes. Cell division related genes, such as MCM4 and LATS2, were overrepresented and genomic-instability was predictive for metastasis-free survival, suggesting that deregulation of the cell cycle is a driver of osteosarcomagenesis. This SuperSeries is composed of the following subset Series: GSE28974: Genome-wide gene expression profiling of mesenchymal stem cells GSE33153: Copy number analysis of high-grade osteosarcoma GSE33382: Genome-wide gene expression analysis of high-grade osteosarcoma For data processing, we refer to the individual series. We performed both non-paired and paired integrative analyses on SNP and gene expression data. Non-paired integrative analysis was performed by importing lists of differentially expressed genes into the Copy Number module of Nexus software version 5 (BioDiscovery, CA). Based on the length of the gene list, Nexus software performs a Fisher's exact test in order to determine whether the number of differentially expressed genes in a specific region with a significant copy number alteration is larger than expected by chance. Genes present in such regions of copy number alteration with FDR-adjusted P-values (Q-bounds in Nexus software) < 0.05 were returned from this integrative analysis. Nexus software only reports genes which are both gained and overexpressed, or both deleted and downregulated. For the paired integrative analysis, copy number data of all autosomal overlapping genes between the copy number and gene expression arrays were exported from Nexus software, and converted into a binary file containing all genes with a gain (1) and no gain (0), and a similar binary file for losses. As in the non-paired integrative analysis, we did not apply any restrictions on the size of copy number alterations. Gene expression data of each probe for each sample were normalized against average gene expression of the corresponding probes over all control samples (either expression data from 12 MSCs, or from 3 osteoblasts). This was performed by subtracting the average expression of the control samples from the expression levels of the sample of interest, since these are log-transformed expression values. For both analyses, only genes that were significantly differentially expressed between the 84 osteosarcoma samples and the specific control set were analyzed, in order to make sure that no genes returned from the integrative analysis were not significantly differentially expressed. Subse quently, genes that overlapped between the copy number binary files and that matched the fold change of expression (upregulation for genes with gains, and downregulation for genes with losses) were returned.

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WGS and WES of pediatric osteosarcoma

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