Identification of potential biomarkers for multiple myeloma using bioinformatics analysis of microarray data

Multiple myeloma (MM) is a cancer that forms in a type of white blood cell called a plasma cell. Rather than produce helpful antibodies, the cancer cells produce abnormal proteins that can cause complications. The interaction between myeloma cells and the bone microenvironment ultimately leads to the activation of osteoclasts and suppression of osteoblasts, resulting in bone loss. The purpose of this study was how interactions between myeloma cells and osteoclasts that might affect the clinical course of myeloma. We selected microarray datasets GSE۳۱۱۵۴ from the GEO database. Differential expressed genes (DEGs) were investigated with GEO۲R (with p values <۰.۰۵ and │logFC│≥±۱.۵). Functional enrichment analysis of the Gene Ontology (GO) and pathways associated with DEGs were analyzed by GO and Kyoto Encyclopedia of Genes and Genomes (KEGG), respectively. To find the Transcription Factors (TFs) controlling the expression of upregulate genes, ChEA was used. Finally, we constructed the protein-protein interaction network (PPI) between TFs and upregulated genes using STRING and Cytoscape.It was found that ۲۵۷ and ۷۳۷ genes were upregulated and downregulated, respectively. GO analysis revealed that DEGs were extensively involved in various biological process (BP), such as cellular glucuronidation, glucuronate metabolic process and retinoic acid metabolic process. Nuclear nucleosome, centriole were significantly enriched for cellular components (CC) and for molecular function, glucuronosyltransferase activity, retinoic acid binding and monocarboxylic acid binding were the highly enriched GO terms. KEEG pathway analysis show Alcoholism, Ascorbate and Retinol metabolism were indicated in multiple myeloma. ChEA showed that POU۵F۱, EZH۲, SMAD۴ and BACH۱ were the top TFs controlling the upregulated genes in Plasma cell myeloma .Moreover, HIST۱H۴A, HIST۱H۴C, HIST۱H۴B and HIST۱H۴H were selected as hub genes in the module constructed using upregulated genes. Our analysis showed that histone genes sets may be used as prognostic factors for survival prediction for MM patients.

کلیدواژه ها:

microarray ، unregulated ، hub genes