Coordinated expression of microRNA-155 and predicted target genes in diffuse large B-cell lymphoma

• Published in: Cancer genetics and cytogenetics 2008-02, Vol.181 (1), p.8-15
• Main Authors: Rai, Deepak, Karanti, Shailaja, Jung, Inkyung, Dahia, Patricia L.M, Aguiar, Ricardo C.T
• Format: Article
• Language: English
• Subjects: Blotting, Northern; Cell Line, Tumor; Culture Media; Gene Expression Regulation; Hematology, Oncology and Palliative Medicine; Humans; Lymphoma, Large B-Cell, Diffuse - genetics; Medical Education; MicroRNAs - genetics; MicroRNAs - isolation & purification; NF-kappa B - metabolism; Reverse Transcriptase Polymerase Chain Reaction; RNA Probes; RNA, Neoplasm - genetics; RNA, Neoplasm - isolation & purification; Transcription, Genetic
• ISSN: 0165-4608; 1873-4456
• DOI: 10.1016/j.cancergencyto.2007.10.008

Abstract MicroRNAs (miRNAs) attenuate gene expression by pairing to the 3′UTR of target transcripts inducing RNA cleavage or translational inhibition. Overexpression of microRNA-155 (miR-155), measured either at the primary ( BIC gene) or mature transcript level, was recently described in diffuse large B-cell lymphomas (DLBCL). These studies have been limited in size, however, and have not attempted to link miR-155 expression to that of putative target genes. To start to address these issues, we examined a collection of 22 well-characterized DLBCL cell lines. The expression of miR-155 is heterogeneous in these cell lines and associates with NF-κB activity. We found that the expression of the primary miR-155 transcript reliably reflects that of the functional mature miR-155. Because many gene array platforms include probe sets for the primary miR-155 sequences, these findings allowed us to confidently examine large array-based expression datasets of primary DLBCLs in the context of miR-155 levels. Our investigation revealed that miR-155 expression segregates with specific molecular subgroups of DLBCL and it is highest in activated B-cell (ABC)-type lymphomas. These tumors are characterized by constitutive activation of NF-κB signals, which supports the data derived from our cell lines. More importantly, using supervised learning algorithms, we identified a robust gene signature driven by the differential expression of miR-155. These profiles contained several gene markers, including predicted targets, consistently downregulated in tumors expressing high levels of miR-155. Our data start to unveil the genome-wide effects of miR-155 expression in DLBCL and indicate the utility of this strategy in the identification and validation of miRNA target genes.