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Increased Expression of SETDB1 Predicts Poor Prognosis in Multiple Myeloma
Jing Xiang1, Xiaotong Chen1, Mengping Chen1
1Department of Hematology, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Abstract:
Several genes on chromosome 1q21 region predict a high risk of multiple myeloma (MM); however, the underlying molecular pathology remains elusive. Overexpression, amplification, or activation of SET Domain Bifurcated 1 (SETDB1), which is located on 1q21, is closely associated with poor prognosis of many human solid malignancies. In our study, upregulation of SETDB1 might indicate an unfavorable prognosis of MM using bioinformatics analysis from GEO databases and MMRF-CoMMpass. Here, increased SETDB1 expression was observed in the plasma cells from newly diagnosed multiple myeloma patients compared to those from the normal controls. Meanwhile, SETDB1 overexpression was the result of increased copy numbers of SETDB1 gene. In MM patients, the Kaplan-Meier analysis was employed to demonstrate that increased SETDB1 expression was associated with shorter overall survival (OS) and event-free survival (EFS). Besides, we conducted multifactorial cox regression analysis to state that SETDB1 expression was an independent biomarker for OS and EFS. MM patients with higher SETDB1 expression showed higher levels of beta-2 microglobulin (β2M), lactate dehydrogenase (LDH), and bone marrow biopsy plasma cells (BMPC) and lower levels of haemoglobin (HGB). Functional enrichment analysis suggested that SETDB1 could promote cell cycle progression in myeloma. Finally, we observed that SETDB1 was distinctly correlated with tumor immunity in MM. SETDB1 expression in myeloma cells was positively correlated with CD56dim natural killer cells but negatively correlated with infiltrating levels of type17 T helper cells, effector memory CD8 T cells, activated dendritic cells, and natural killer T cells from whole bone marrow (WBM) biopsies. Taken together, these results indicated that SETDB1 could be used as a novel biomarker for predicting the prognosis of MM patients.
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