Transcriptome analysis reveals molecular profiles associated with evolving steps of monoclonal gammopathies

转录组分析揭示了与单克隆丙种球蛋白病演变步骤相关的分子特征

阅读:1

Abstract

A multistep model has been proposed of disease progression starting in monoclonal gammopathy of undetermined significance continuing through multiple myeloma, sometimes with an intermediate entity called smoldering myeloma, and ending in extramedullary disease. To gain further insights into the role of the transcriptome deregulation in the transition from a normal plasma cell to a clonal plasma cell, and from an indolent clonal plasma cell to a malignant plasma cell, we performed gene expression profiling in 20 patients with monoclonal gammopathy of undetermined significance, 33 with high-risk smoldering myeloma and 41 with multiple myeloma. The analysis showed that 126 genes were differentially expressed in monoclonal gammopathy of undetermined significance, smoldering myeloma and multiple myeloma as compared to normal plasma cell. Interestingly, 17 and 9 out of the 126 significant differentially expressed genes were small nucleolar RNA molecules and zinc finger proteins. Several proapoptotic genes (AKT1 and AKT2) were down-regulated and antiapoptotic genes (APAF1 and BCL2L1) were up-regulated in multiple myeloma, both symptomatic and asymptomatic, compared to monoclonal gammopathy of undetermined significance. When we looked for those genes progressively modulated through the evolving stages of monoclonal gammopathies, eight snoRNA showed a progressive increase while APAF1, VCAN and MEGF9 exhibited a progressive downregulation. In conclusion, our data show that although monoclonal gammopathy of undetermined significance, smoldering myeloma and multiple myeloma are not clearly distinguishable groups according to their gene expression profiling, several signaling pathways and genes were significantly deregulated at different steps of the transformation process.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。