OBJECTIVES: Identifying the specific biomarkers and molecular signatures of MM might provide novel evidence for MM prognosis and targeted therapy. METHODS: Bioinformatic analyses were performed through GEO and TCGA datasets. The differential expression of HIST1H2BH in MM sample was validated by the qRT-PCR. And the CCK-8 assay was performed to detect the proliferation activity of HIST1H2BH on MM cell lines. RESULTS: A total of 793 DEGs were identified between bone marrow plasma cells from newly diagnosed myeloma and normal donors in GSE6477. Among them, four vital genes (HIST1H2AC, HIST1H2BH, CCND1 and TCF7L2) modeling were constructed. The increased HIST1H2BH expression was correlated with worse survival of MM based on TCGA datasets. The transcriptional expression of HIST1H2BH was significantly up-regulated in primary MM patients. And knockdown HIST1H2BH decreased the proliferation of MM cell lines. CONCLUSIONS: We have identified up-regulated HIST1H2BH in MM patients associated with poor prognosis using integrated bioinformatical methods.
Multiple Myeloma , Humans , Bone Marrow Cells , Cell Line , Computational Biology , Multiple Myeloma/genetics , Plasma
