ArticleInternational journal of molecular medicine2018
Logistic regression analysis for the identification of the metastasis-associated signaling pathways of osteosarcoma.
Article in International journal of molecular medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 9 citations in OpenAlex.
- Biological Activity of Biomarkers Associated With Metastasis in Osteosarcoma Cell Lines.Cancer medicine · 2025Article
- Antisense mediated blockade of Dickkopf 1 attenuates tumor survival, metastases and bone damage in experimental osteosarcoma.Scientific reports · 2025Article
- Review
- Uncovering periodontitis-associated markers through the aggregation of transcriptomics information from diverse sources.Frontiers in genetics · 2024Article
- Development and Validation of Novel Prognostic Models for Immune-Related Genes in Osteosarcoma.Frontiers in molecular biosciences · 2022Article
- Article
- Identification of potential diagnostic gene biomarkers in patients with osteoarthritis.Scientific reports · 2020Article
- Regulatory effects of microRNA‑184 on osteosarcoma via the Wnt/β‑catenin signaling pathway.Molecular medicine reports · 2018Article
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Authors and funding
10 authors at 5 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Osteosarcoma (OS) is the most common histological type of primary bone cancer. The present study was designed to identify the key genes and signaling pathways involved in the metastasis of OS. Microarray data of GSE39055 were downloaded from the Gene Expression Omnibus database, which included 19 OS biopsy specimens before metastasis (control group) and 18 OS biopsy specimens after metastasis (case group). After the differentially expressed genes (DEGs) were identified using the Linear Models for Microarray Analysis package, hierarchical clustering analysis and unsupervised clustering analysis were performed separately, using orange software and the self-organization map method. Based upon the Database for Annotation, Visualization and Integrated Discovery tool and Cytoscape software, enrichment analysis and protein-protein interaction (PPI) network analysis were conducted, respectively. After function deviation scores were calculated for the significantly enriched terms, hierarchical clustering analysis was performed using Cluster 3.0 software. Furthermore, logistic regression analysis was used to identify the terms that were significantly different. Those terms that were significantly different were validated using other independent datasets. There were 840 DEGs in the case group. There were various interactions in the PPI network [including intercellular adhesion molecule-1 (ICAM1), transforming growth factor β1 (TGFB1), TGFB1-platelet-derived growth factor subunit B (PDGFB) and PDGFB-platelet‑derived growth factor receptor-β (PDGFRB)]. Regulation of cell migration, nucleotide excision repair, the Wnt signaling pathway and cell migration were identified as the terms that were significantly different. ICAM1, PDGFB, PDGFRB and TGFB1 were identified to be enriched in cell migration and regulation of cell migration. Nucleotide excision repair and the Wnt signaling pathway were the metastasis-associated pathways of OS. In addition, ICAM1, PDGFB, PDGFRB and TGFB1, which were involved in cell migration and regulation of cell migration may affect the metastasis of OS.
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