Gene expression profiling of pediatric mature B-cell non-Hodgkin lymphomas/lymphoproliferative disorders through whole transcriptome analysis

Abstract

Abstract Background: Adult and pediatric mature B-cell non-Hodgkin lymphomas/lymphoproliferative disorders (ped mature B-NHL/LPDs) differ both pathologically and in their clinical courses. While recent studies suggested shared pathogenesis between pediatric and adult Burkitt lymphomas (BLs), others of similar cellular origin and morphologic growth patterns (e.g., pediatric-type and conventional follicular lymphoma) behave very differently. We sought to characterize ped mature B-NHL/LPDs using whole transcriptome analysis to provide a potential framework for molecular pathogenesis and diagnostics. Design: B-cell NHL/LPDs (excluding B-lymphoblastic leukemia/lymphoma) diagnosed between 2003 and 2023 at ≤24 years of age were retrieved from the archive at St. Jude Children's research hospital. Seventy-six samples from 74 patients with available material underwent whole transcriptome analysis. Total RNA was extracted from either fresh/frozen tumor tissue or formalin-fixed paraffin-embedded tissue blocks. RNA-Seq libraries were constructed using the TruSeq Stranded Total RNA Kit (Illumina, CA, USA). Results: Cases occurred at a median age of 13 years old (range <1-24), more commonly in males than females (2.2:1). Geneset enrichment analyses using 17 relevant lymphoma signatures from the signatureDB database identified 3 clusters. Cluster 1 was composed of 37 BLs (1 as monomorphic post-transplant lymphoproliferative disorder (PTLD)). Cluster 2 (n=8) included 2 polymorphic PTLDs, 1 diffuse large B-cell lymphoma (DLBCL) as monomorphic PTLD, 2 large B cell lymphomas (LBCLs) associated with primary immunodeficiency, 1 HIV-associated BL, 1 transformed LBCL arising from nodular lymphocyte predominant Hodgkin lymphoma and 1 mediastinal grey zone lymphoma. Cluster 3 (n=31) mainly consisted of DLCBL, high grade B-cell lymphoma (HGBCL), primary mediastinal large B-cell lymphoma (PMBCL) and LBCL with IRF4 rearrangements. Cluster 3 did not include BL but included 1 case with differentials between BL and HGBCL (workup limited by available material). Preliminary clustering analysis with UMAP (Uniform Manifold Approximation and Projection) using the top 1000 variably expressed protein-coding genes revealed similar clusters that distinguished BLs from non-BLs with a separate cluster enriched in cases with underlying immunodeficiencies. Conclusion: Transcriptome analysis can be used to identify distinct pediatric BL and non-BL clusters. Gene expression profiling additionally characterized cases with underlying immunodeficiencies. Collectively, these techniques offer promising approaches to facilitate more accurate delineation of ped mature B-NHL/LPDs.