Identification of potential biomarkers or therapeutic targets of mesenchymal stem cells in multiple myeloma by bioinformatics analysis.

Objectives: Mesenchymal stem cells (MSCs) play important roles in multiple myeloma (MM) pathogenesis. Previous studies have discovered a group of MM-associated potential biomarkers in MSCs derived from bone marrow (BM-MSCs). However, no study of the bioinformatics analysis was conducted to explore the key genes and pathways of MSCs derived from adipose (AD-MSCs) in MM. The aim of this study was to screen potential biomarkers or therapeutic targets of AD-MSCs and BM-MSCs in MM. Methods: The gene expression profiles of AD-MSCs (GSE133346) and BM-MSCs (GSE36474) were downloaded from Gene Expression Omnibus (GEO) database. Gene Oncology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and protein-protein interaction (PPI) network of differentially expressed genes (DEGs) were performed. Results: A total of 456 common downregulated DEGs in two datasets were identified and the remaining DEGs in GSE133346 were further identified as specific DEGs of AD-MSCs. Furthermore, a PPI network of common downregulated DEGs was constructed and seven hub genes were identified. Importantly, cell cycle was the most significantly enrichment pathway both in AD-MSCs and BM-MSCs from MM patients. Conclusion: We identified key genes and pathways closely related with MM progression, which may act as potential biomarkers or therapeutic targets of MM. Keywords: bioinformatics analysis; multiple myeloma; mesenchymal stem cells; differentially expressed genes; biomarkers.