ArticleTranslational cancer research2022
Identification of novel prognostic biomarkers for osteosarcoma: a bioinformatics analysis of differentially expressed genes in the mesenchymal stem cells from single-cell sequencing data set.
Article in Translational cancer research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 12 citations in OpenAlex.
- LL-37 inhibits osteosarcoma progression by suppressing SQLE-mediated cholesterol synthesis via the PTEN/AKT/mTOR pathway.Journal of bone oncology · 2026Article
- Single-cell RNA sequencing in osteosarcoma: applications in diagnosis, prognosis, and treatment.Medical oncology (Northwood, London, England) · 2025Review
- Tropomyosin isoforms encoded by TPM2 control the actin-bundling activity of fascin-1.Biological research · 2025Article
- Review
- The whole transcriptome analysis using FFPE and fresh tissue samples identifies the molecular fingerprint of osteosarcoma.Experimental biology and medicine (Maywood, N.J.) · 2024Article
- Single-cell RNA sequencing reveals the communications between tumor microenvironment components and tumor metastasis in osteosarcoma.Frontiers in immunology · 2024Article
- A bioinformatics analysis of potential cellular communication networks in non-alcoholic steatohepatitis and colorectal adenoma using scRNA-seq and bulk-seq.Journal of gastrointestinal oncology · 2023Article
- Abnormal signal pathways and tumor heterogeneity in osteosarcoma.Journal of translational medicine · 2023Article
- Screening and identification of susceptibility genes for osteosarcoma based on bioinformatics analysis.Annals of translational medicine · 2023Article
- A novel molecular signature for predicting prognosis and immunotherapy response in osteosarcoma based on tumor-infiltrating cell marker genes.Frontiers in immunology · 2023Article
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Authors and funding
6 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Mesenchymal stem cells (MSCs) play a crucial role in osteosarcoma (OS) growth and progression. This study conducted a bioinformatics analysis of a single-cell ribonucleic acid sequencing data set and explored the MSC-specific differentially expressed genes (DEGs) in advanced OS. Methods: MSC-specific DEGs from GSE152048 was extracted using Seurat R package. These DEGs were then subjected to the functional analysis, and several key genes were further identified and underwent a prognosis analysis. Results: A total of 234 upregulated and 280 downregulated DEGs were identified between the MSCs and other cells, and a total of 188 upregulated and 158 downregulated DEGs were identified between the MSCs and osteoblastic cells. The Gene Ontology (GO) functional analysis showed that the specific DEGs between the MSCs and osteoblastic cells were enriched in GO terms such as "collagen catabolic process", "positive regulation of pathway-restricted SMAD protein phosphorylation", "osteoblast differentiation", "regulation of release of cytochrome c from mitochondria" and "interleukin-1 production". The specific DEGs between the MSCs and osteoblastic cells were subjected to a protein-protein interaction network analysis. Further, a survival analysis of 20 genes with combined scores >0.94 revealed that the low expression of Conclusions: Our bioinformatics analysis revealed 7 hub genes derived from the specific DEGs between the MSCs and osteoblastic cells. The 7 hub genes may serve as potential prognostic biomarkers for patients with OS.
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