Molecular Characterization and Genetic Subclassification Comparison of Diffuse Large B-Cell Lymphoma: Real-Life Experience with 74 Cases

Abstract

<b><i>Introduction:</i></b> Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous entity. Lately, several algorithms achieving therapeutically and prognostically relevant DLBCL subclassification have been published. <b><i>Methods:</i></b> A cohort of 74 routine DLBCL cases was broadly characterized by immunohistochemistry (IHC), fluorescence in situ hybridization (FISH) of the <i>BCL2</i>, <i>BCL6</i>, and <i>MYC</i> loci, and comprehensive high-throughput sequencing (HTS). 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. <b><i>Results:</i></b> Hans and Tally’s overall IHC-based subclassification success rate was 96% and 82%, respectively. 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). Clinical correlations highlighted MCD as an aggressive subtype associated with higher relapse and mortality. <b><i>Conclusions:</i></b> The Two-step algorithm has a better success rate at subclassifying DLBCL cases based on genetic differences. Further improvement of the classifiers is required to increase the number of classifiable cases and thus prove their applicability in routine diagnostics.