74 DLBCL
Diffuse large B-cell lymphoma (DLBCL) is a heterogenous entity, consisting of various subgroups regarding biological background and therapy outcome. Lately, several algorithms achieving robust therapeutically and prognostically relevant DLBCL subclassification have been published. Herein, we attempt to molecularly depict and genetically subclassify 74 DLBCL cases.  A cohort of 74 routine DLBCL cases was broadly characterized by immunohistochemistry (IHC), fluorescence in situ hybridization (FISH) of the BCL2, BCL6 and MYC loci, and comprehensive high throughput sequencing (HTS). The “classical” IHC-based algorithms Hans and Tally were applied. Based on the genetic alterations found, cases were reclassified using two probabilistic tools – LymphGen and Two-step classifier, allowing for comparison of the two models.  Hans and Tally's overall subclassification success rate was 96% and 82%, respectively. FISH analysis revealed translocations in 29/56 investigated cases. HTS and FISH data allowed the LymphGen algorithm to successfully classify 11/55 cases, (1 – BN2, 7 – EZB, 1 – MCD, and 2 – genetically composite EZB/N1). The total subclassification rate was 20%. On the other hand, the Two-step classifier categorized 36/55 cases, with 65.5 % success (9 – BN2, 12 – EZB, 9 – MCD, 2 – N1, and 4 – ST2).  The currently available algorithms for genetic subclassification of DLBCL are user-friendly. The Two-step algorithm has a better success rate at subclassifying DLBCL cases based on genetic differences. Our clinical correlations highlighted MCD as an aggressive subtype associated with higher relapse and mortality. Further improvement of the classifiers is needed to increase the number of classifiable cases and thus prove their applicability in routine diagnostics.