ArticleMedical science monitor : international medical journal of experimental and clinical research2016
Identification of CD20, ECM, and ITGA as Biomarkers for Osteosarcoma by Integrating Transcriptome Analysis.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 13 citations in OpenAlex.
- Development and validation of a novel prognostic signature for osteosarcoma.Translational cancer research · 2025Article
- Combined transcriptome and proteome analysis reveals MSN and ARFIP2 as biomarkers for trastuzumab resistance of breast cancer.Breast cancer research and treatment · 2024Article
- Clinical Significance and Potential Mechanisms of the RNA Methyltransferase KIAA1429 in Osteosarcoma.Journal of Cancer · 2024Article
- The Clinical Significance and Potential Molecular Mechanism of Upregulated CDC28 Protein Kinase Regulatory Subunit 1B in Osteosarcoma.Journal of oncology · 2021Article
- Differentially expressed gene profile and relevant pathways of the traditional Chinese medicine cinobufotalin on MCF‑7 breast cancer cells.Molecular medicine reports · 2019Article
- Identification of a Two-Gene (Frontiers in oncology · 2019Article
- Identification of Key Genes Affecting Results of Hyperthermia in Osteosarcoma Based on Integrative ChIP-Seq/TargetScan Analysis.Medical science monitor : international medical journal of experimental and clinical research · 2017Article
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8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND Osteosarcoma is the most frequent primary bone cancer derived from primitive mesenchymal cells. The aim of this study was to explore the molecular mechanism of the development and progression of osteosarcoma. MATERIAL AND METHODS The gene expression profiles of osteosarcoma from 17 specimens (3 normal and 14 osteosarcoma) were downloaded from the GEO database. The differentially expressed genes were identified by use of the Limma package. DAVID and Enrichment Map were used to perform GO and KEGG pathways enrichment analysis and to integrate enrichment results of differentially expressed genes (DEGs). Protein-protein interaction network was constructed and analyzed to screen out the potential regulatory proteins using the STRING online tools. RESULTS A total of 417 DEGs were screened, including 215 up-regulated and 202 down-regulated ones, accounting for 51.56% and 48.4%, respectively. In GO term, a total of 12 up-regulated expression genes were enriched in Cellular Component. The up-regulated DEGs were enriched in 6 KEGG pathways while the down-regulated expression genes were enriched in 2 KEGG pathways. The constructed PPI network was aggregated with 1006 PPI relationships and 238 nodes, accounting for 57.07% of DEGs. We found that CD20, MCM, and CCNB1 (down-regulated) in cell cycle and ECM, ITGA, RTKin (up-regulated) in focal adhesion had important roles in the progression of osteosarcoma. CONCLUSIONS The identified DEGs and their enriched pathways provide references for the exploration of the molecular mechanism of the development and progression of osteosarcoma. Moreover, the key genes (CD20, ECM, and ITGA) may be useful in treatment and diagnosis of osteosarcoma.
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