Unknown

Dataset Information

Identification of Metastasis-Associated Biomarkers in Synovial Sarcoma Using Bioinformatics Analysis.


ABSTRACT: Synovial sarcoma (SS) is a highly aggressive soft tissue tumor with high risk of local recurrence and metastasis. However, the mechanisms underlying SS metastasis are still largely unclear. The purpose of this study is to screen metastasis-associated biomarkers in SS by integrated bioinformatics analysis. Two mRNA datasets (GSE40018 and GSE40021) were selected to analyze the differentially expressed genes (DEGs). Using the Database for Annotation, Visualization and Integrated Discovery (DAVID) and gene set enrichment analysis (GSEA), functional and pathway enrichment analyses were performed for DEGs. Then, the protein-protein interaction (PPI) network was constructed via the Search Tool for the Retrieval of Interacting Genes (STRING) database. The module analysis of the PPI network and hub

SUBMITTER: Song Y 

PROVIDER: S-EPMC7518102 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature