MicroRNA (miRNA) deregulation has been implicated in the pathogenesis of mantle cell lymphoma (MCL). Using a high-throughput quantitative real-time PCR platform, we performed miRNA profiling on cyclin D1- positive MCL (n=30) and cyclin D1-negative MCL (n=7) and compared them with small lymphocytic leukemia/lymphoma (SLL, n=12), aggressive B-cell lymphomas (n=138), normal B-cell subsets and stromal cells. We identified a 19-miRNA classifier which included six upregulated miRNAs (miR-135a, miR-708, miR-150, miR-363, miR-184, miR-342-5p) and 13 downregulated miRNAs, that was able to distinguish MCL from other aggressive lymphomas with \u3e90% probability. Some of these upregulated miRNAs are highly expressed in naïve B-cells. MicroRNA classifier showed consistent results in FFPE tissues and was able to distinguish cyclin D1-negative MCL from other lymphomas. A 26-miRNA classifier could distinguish MCL from SLL, dominated by 23 upregulated miRNAs in MCL. Unsupervised hierarchical clustering of MCL cases demonstrated a cluster characterized by high expression of miRNAs from polycistronic miR17~92 cluster and its paralogs miR-106a-363 and miR-106b-25, which was distinct from the other clusters showing enrichment of stroma associated miRNAs. The corresponding gene-expressionprofiling (GEP) data showed that the former cluster of MCL had significantly higher proliferation genesignature (PS), while the other subsets had higher expression of stroma associated genes. Clinical outcome analysis suggests that miRNAs can serve as prognosticators
