MicroRNAs as predictors for CNS relapse of systemic diffuse large B-cell lymphoma

// Nir Pillar 1 , Osnat Bairey 1, 2 , Neta Goldschmidt 3 , Yakov Fellig 4 , Yevgenia Rosenblat 5 , Itchak Shehtman 6 , Danielle Haguel 1 , Pia Raanani 1, 2 , Noam Shomron 1, * and Tali Siegal 7, * 1 Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel 2 Institute of Hemathology, Davidoff Institute of Oncology, Rabin Medical Center, Petach Tikva, Israel 3 Department of Hemathology, Hadassah Hebrew University Medical Center, Jerusalem, Israel 4 Department of Pathology, Hadassah Hebrew University Medical Center, Jerusalem, Israel 5 Department of Pathology, Rabin Medical Center, Petach Tikva, Israel 6 Department of Pathology, Meir Medical Center, Kefar Saba, Israel 7 Neuro-Oncology Center, Davidoff Institute of Oncology, Rabin Medical Center, Petach Tikva, Israel * These authors have contributed equally to this work Correspondence to: Tali Siegal, email: talisi1@clalit.org.il Noam Shomron, email: nshomron@post.tau.ac.il Keywords: systemic DLBCL, CNS relapse prediction, microRNA, miR-20a, miR-30d Received: June 06, 2017     Accepted: August 04, 2017     Published: September 15, 2017 ABSTRACT Systemic diffuse large B-cell lymphoma (DLBCL) is a potentially curable disease using current regimen of immunochemotherapy. Central nervous system (CNS) relapse is a complication that occurs in approximately 5% of DLBCL patients and is associated with a high fatality rate. Early identification of molecular markers for CNS involvement may serve for the highly needed accurate stratification of patients into risk groups regarding CNS relapse. MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate gene expression at the post-transcriptional level and are known to be involved in DLBCL pathophysiology. In this study, we utilized miRNA multiplex reading of systemic newly diagnosed DLBCL samples obtained from patients with clinical risk factors for CNS involvement whose disease course was distinguished by the presence or absence of subsequent CNS relapse. The analysis detected two differentially expressed miRNAs, miR-20a and miR-30d, that predict for CNS involvement. Replication of these results in different samples was used for validation. We performed bioinformatics miRNA-target enrichment analysis to reveal a number of putative mechanisms for these miRNAs regulation of CNS relapse, including neuronal plasticity and WNT signaling pathway. Altogether, we show that the expression level of two miRNAs may have valuable information that may refine stratification for patients-at-risk for relapse with CNS involvement in DLBCL. Further larger scale studies are needed to shed light on the pathways involved in this disease.