Genome-wide identification of potential biomarkers in multiple myeloma using meta-analysis of mRNA and miRNA expression data

Abstract Multiple myeloma (MM) is a plasma cell malignancy with diverse clinical phenotypes and molecular heterogeneity not completely understood. Differentially expressed genes (DEGs) miRNAs (DEMs) in MM may influence disease pathogenesis, presentation / drug sensitivities. But these signatures overlap meagrely plausibly due to complexity of genome, diversity primary cells studied, technologies/ analytical tools utilized. This warrants further investigations since DEGs/DEMs can impact outcomes guide personalized therapy. We have conducted genome-wide meta-analysis versus Normal Plasma Cells (NPCs) derived unified putative for MM. 100 DEMs 1,362 DEGs were found deranged between NPCs. Signatures 37 (‘Union 37’) 154 154’) deduced that shared 17 22 published prognostic signatures, respectively. Two miRs (miR-16–2-3p, 30d-2-3p) correlated survival outcomes. PPI analysis identified 5 topmost functionally connected hub ( UBC, ITGA4, HSP90AB1, VCAM1, VCP ). Transcription factor regulatory networks determined five seed ? 4 biomarker applications CDKN1A, CDKN2A, MMP9, IGF1, MKI67 ) three up/ down regulated (miR-23b, 195, let7b/ miR-20a, 155, 92a). Further studies are warranted establish translate potential