Affiliation:
1. Key Laboratory of Organ Development and Regeneration of Zhejiang Province, College of Life and Environmental Science, Hangzhou Normal University, Hangzhou, Zhejiang, China
2. College of Medicine, Hangzhou Normal University, Hangzhou, Zhejiang, China
3. Department of stomatology, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China
Abstract
BACKGROUND: Pulmonary metastasis is the most frequent cause of death in osteosarcoma (OS) patients. Recently, several bioinformatics studies specific to pulmonary metastatic osteosarcoma (PMOS) have been applied to identify genetic alterations. However, the interpretation and reliability of the results obtained were limited for the independent database analysis. OBJECTIVE: The expression profiles and key pathways specific to PMOS remain to be comprehensively explored. Therefore, in our study, three original datasets of GEO database were selected. METHODS: Initially, three microarray datasets (GSE14359, GSE14827, and GSE85537) were downloaded from the GEO database. Differentially expressed genes (DEGs) between PMOS and nonmetastatic osteosarcoma (NMOS) were identified and mined using DAVID. Subsequently, GO and KEGG pathway analyses were carried out for DEGs. Corresponding PPI network of DEGs was constructed based on the data collected from STRING datasets. The network was visualized with Cytoscape software, and ten hub genes were selected from the network. Finally, survival analysis of these hub genes also used the TARGET database. RESULTS: In total, 569 upregulated and 1238 downregulated genes were filtered as DEGs between PMOS and NMOS. Based on the GO analysis result, these DEGs were significantly enriched in the anatomical structure development, extracellular matrix, biological adhesion, and cell adhesion terms. Based on the KEGG pathway analysis result, these DEGs were mainly enriched in the pathways in cancer, PI3K-Akt signaling, MAPK signaling, focal adhesion, cytokine-cytokine receptor interaction, and IL-17 signaling. Hub genes (ANXA1 and CXCL12) were significantly associated with overall survival time in OS patient. CONCLUSION: Our results may provide new insight into pulmonary metastasis of OS. However, experimental studies remain necessary to elucidate the biological function and mechanism underlying PMOS.
Subject
Health Informatics,Biomedical Engineering,Information Systems,Biomaterials,Bioengineering,Biophysics
Reference48 articles.
1. The metastasectomy and timing of pulmonary metastases on the outcome of osteosarcoma patients;Huang;Clin Med Oncol.,2009
2. Metastatic osteosarcoma: A challenging multidisciplinary treatment;Meazza;Expert Rev Anticancer Ther.,2016
3. Positively selected enhancer elements endow osteosarcoma cells with metastatic competence;Morrow;Nat Med.,2018
4. Effect of timing of pulmonary metastasis occurrence on the outcome of metastasectomy in osteosarcoma patients;Ahmed;J Pediatr Surg.,2019
5. Gene function analysis in osteosarcoma based on microarray gene expression profiling;Zhao;Int J Clin Exp Med.,2015
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献