Identification of potential biomarkers in myelodysplastic syndromes by weighted gene co-expression network analysis

Abstract

Abstract MDS is characterized by great heterogeneity in clinical manifestations, cytogenetic and molecular biological manifestations, therapeutic options and efficacy. The lack of specific molecular mechanism discovery and effective targeted therapy is a well-known problem of MDS. Therefore, finding critical target molecules and therapeutic targets is at the forefront of current research. Using data from the Gene Expression Omnibus (GEO), we performed a thorough investigation of the mRNA expression profile of MDS in this work. Three mRNA microarray datasets (GSE58831, GSE4619, GSE19429) with MDS and control samples were used to creation of co-expression networks by using weighted correlation network analysis (WGCNA). A total of 15 key apoptosis-related differentially expressed genes (ARDEGs) genes were obtained by performing weighted gene co-expression network analysis (WGCNA) analysis. The GO analyses indicated that key genes are mainly enriched in B cell activation, beta-catenin-TCF complex, and DNA-binding transcription repressor activity. The GSEA and GSVA suggested that hypoxia, TGF-β signaling, and IL2 STAT5 signaling are crucial in the gene changes of MDS. Furthermore, A total of 5 differentially expressed genes (VPREB3, LEF1-AS1, PAX5, CD79A, LEF1) were related to the survival of MDS patients. Our findings may provide novel insight into the molecular characteristics of MDS through integrative analysis of GEO data by using weighted gene co-expression network analysis, and suggest potential biomarkers and therapeutic targets for MDS.