Gene expression profiling of human plasma cell differentiation and classification of multiple myeloma based on similarities to distinct stages of late-stage B-cell development |
| |
Authors: | Zhan Fenghuang Tian Erming Bumm Klaus Smith Ruston Barlogie Bart Shaughnessy John |
| |
Affiliation: | Donna and Donald Lambert Laboratory of Myeloma Genetics at the Myeloma Institute for Research and Therapy, University of Arkansas for Medical Sciences, Little Rock 72205, USA. |
| |
Abstract: | To identify genes linked to normal plasma cell (PC) differentiation and to classify multiple myeloma (MM) with respect to the expression patterns of these genes, we analyzed global mRNA expression in CD19-enriched B cells (BCs) from 7 tonsils, CD138-enriched PCs from 11 tonsils, 31 normal bone marrow samples, and 74 MM bone marrow samples using microarrays interrogating 6800 genes. Hierarchical clustering analyses with 3288 genes clearly segregated the 4 cell types, and chi-square and Wilcoxin rank sum tests (P <.0005) identified 359 and 500 previously defined and novel genes that distinguish tonsil BCs from tonsil PCs (early differentiation genes [EDGs]), and tonsil PCs from bone marrow PCs (late differentiation genes [LDGs]), respectively. MM as a whole was found to have dramatically variable expression of EDGs and LDGs, and one-way analysis of variance (ANOVA) was used to identify the most variable EDGs (vEDGs) and LDGs (v1LDG and v2LDG). Hierarchical cluster analysis with these genes revealed that previously defined MM gene expression subgroups (MM1-MM4) could be linked to one of the 3 normal cell types. Clustering with 30 vEDGs revealed that 13 of 18 MM4 cases clustered with tonsil BCs (P =.000 05), whereas 14 of 15 MM3 cases clustered with tonsil PCs when using 50 v1LDG (P =.000 008), and 14 of 20 MM2 cases clustered with bone marrow PCs when using 50 v2LDG (P =.000 09). MM1 showed no significant linkage with normal cell types studied. Thus, genes whose expression is linked to distinct transitions in late-stage B-cell differentiation can be used to classify MM. |
| |
Keywords: | |
本文献已被 PubMed 等数据库收录! |
|