title: The miR-17-92 microRNA cluster: a novel diagnostic tool in large B-cell malignancies.
abstract: Diffuse large B-cell lymphoma (DLBCL) can present as de novo or can arise through the transformation of many indolent lymphomas, including follicular lymphoma (FL). The morphological differentiation between germinal center-DLBCL (GC-DLBCL) and high-grade (grade 3) FL could be challenging; the accurate sub-classification of large B-cell lymphomas is mandatory in order to select the most appropriate among the new-targeted therapies. Recent expression profiling studies reported microRNAs (miRNAs) (and miR-17-92 cluster, in particular) as useful tools in differentiating DLBCL and FL. However, these preliminary results are based on cell line-derived data or did not consider grade 3 FL cases. To investigate this point, 36 cases of GC-DLBCL and 18 cases of grade 3 non-transforming FL were considered. All diagnoses were based on the World Health Organization criteria and were confirmed by clinical, histological, and immunohistochemical data. Six members of the miR-17-92 cluster (ie, miR-18b, miR-19b, miR-20a, miR-92, miR-93, and miR-106a) and two control miRNAs (ie, miR-150 and miR-210) were quantified by quantitative reverse transcription-polymerase chain reaction. All the considered miR-17-92 cluster miRNAs were significantly overexpressed in GC-DLBCL, being miR-20a and miR-106a the most dysregulated (P<0.001). Receiver operating characteristics (ROCs) analysis was used to find the optimal cut-off in distinguishing the two histotypes. The ROC estimated thresholds for miR-18b, miR-19b, miR-20a, miR-92, and miR-106a displayed a sensitivity level higher than 0.80 in achieving the GC-DLBCL diagnosis. The classification tree built on the six thresholds allowed the correct identification of 35/36 GC-DLBCL (97.2%). Profiling the miR-17-92 cluster is a promising investigative method for differentiating GC-DLBCL from high-grade FL. Subject to the validation of these findings in further larger studies; miR-17-92 cluster could represent a reliable, standardizable diagnostic tool for the sub-classification of large B-cell lymphoid neoplasm.
authors.affiliation: Surgical Pathology and Cytopathology Unit, Department of Medicine, University of Padua, Padua, Italy.
authors.forename: Ambrogio
authors.initials: A
authors.lastname: Fassina
authors.forename: Filippo
authors.initials: F
authors.lastname: Marino
authors.forename: Maayan
authors.initials: M
authors.lastname: Siri
authors.forename: Renato
authors.initials: R
authors.lastname: Zambello
authors.forename: Laura
authors.initials: L
authors.lastname: Ventura
authors.forename: Matteo
authors.initials: M
authors.lastname: Fassan
authors.forename: Francesca
authors.initials: F
authors.lastname: Simonato
authors.forename: Rocco
authors.initials: R
authors.lastname: Cappellesso
mesh_terms: D000328:Adult; D000368:Aged; D014408:Biomarkers, Tumor / Q000378:metabolism*; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D008221:Lymphoid Tissue / Q000378:metabolism; D008224:Lymphoma, Follicular / Q000175:diagnosis* / Q000378:metabolism; D016403:Lymphoma, Large B-Cell, Diffuse / Q000175:diagnosis* / Q000378:metabolism; D008297:Male; D035683:MicroRNAs / Q000378:metabolism*; D008875:Middle Aged; D062085:RNA, Long Noncoding; D055815:Young Adult
chemical_list: D014408:Biomarkers, Tumor; C568997:MIR17HG, human; D035683:MicroRNAs; D062085:RNA, Long Noncoding