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Item does not contain fulltext, Despite high cure rates in classic Hodgkin lymphoma (cHL), relapses are observed. Whether relapsed cHL represents second primary lymphoma or an underlying T-cell lymphoma (TCL) mimicking cHL is underinvestigated. To analyze the nature of cHL recurrences, in-depth clonality testing of immunoglobulin (Ig) and T-cell receptor (TCR) rearrangements was performed in paired cHL diagnoses and recurrences among 60 patients, supported by targeted mutation analysis of lymphoma-associated genes. Clonal Ig rearrangements were detected by next-generation sequencing (NGS) in 69 of 120 (58%) diagnoses and recurrence samples. The clonal relationship could be established in 34 cases, identifying clonally related relapsed cHL in 24 of 34 patients (71%). Clonally unrelated cHL was observed in 10 of 34 patients (29%) as determined by IG-NGS clonality assessment and confirmed by the identification of predominantly mutually exclusive gene mutations in the paired cHL samples. In recurrences of >2 years, ∼60% of patients with cHL for whom the clonal relationship could be established showed a second primary cHL. Clonal TCR gene rearrangements were identified in 14 of 125 samples (11%), and TCL-associated gene mutations were detected in 7 of 14 samples. Retrospective pathology review with integration of the molecular findings were consistent with an underlying TCL in 5 patients aged >50 years. This study shows that cHL recurrences, especially after 2 years, sometimes represent a new primary cHL or TCL mimicking cHL, as uncovered by NGS-based Ig/TCR clonality testing and gene mutation analysis. Given the significant therapeutic consequences, molecular testing of a presumed relapse in cHL is crucial for subsequent appropriate treatment strategies adapted to the specific lymphoma presentation.

Contains fulltext : 251604.pdf (Publisher’s version ) (Open Access), Gene-expression profiling (GEP) is used to study the molecular biology of lymphomas. Here, advancing insights from GEP studies in diffuse large B-cell lymphoma (DLBCL) lymphomagenesis are discussed. GEP studies elucidated subtypes based on cell-of-origin principles and profoundly changed the biological understanding of DLBCL with clinical relevance. Studies integrating GEP and next-generation DNA sequencing defined different molecular subtypes of DLBCL entities originating at specific anatomical localizations. With the emergence of high-throughput technologies, the tumor microenvironment (TME) has been recognized as a critical component in DLBCL pathogenesis. TME studies have characterized so-called "lymphoma microenvironments" and "ecotypes". Despite gained insights, unexplained chemo-refractoriness in DLBCL remains. To further elucidate the complex biology of DLBCL, we propose a novel targeted GEP consortium panel, called BLYM-777. This knowledge-based biology-driven panel includes probes for 777 genes, covering many aspects regarding B-cell lymphomagenesis (f.e., MYC signature, TME, immune surveillance and resistance to CAR T-cell therapy). Regarding lymphomagenesis, upcoming DLBCL studies need to incorporate genomic and transcriptomic approaches with proteomic methods and correlate these multi-omics data with patient characteristics of well-defined and homogeneous cohorts. This multilayered methodology potentially enhances diagnostic classification of DLBCL subtypes, prognostication, and the development of novel targeted therapeutic strategies.

Contains fulltext : 232033.pdf (Publisher’s version ) (Open Access), Acute myeloid leukemia (AML) is caused by genetic aberrations that also govern the prognosis of patients and guide risk-adapted and targeted therapy. Genetic aberrations in AML are structurally diverse and currently detected by different diagnostic assays. This study sought to establish whole transcriptome RNA sequencing as single, comprehensive, and flexible platform for AML diagnostics. We developed HAMLET (Human AML Expedited Transcriptomics) as bioinformatics pipeline for simultaneous detection of fusion genes, small variants, tandem duplications, and gene expression with all information assembled in an annotated, user-friendly output file. Whole transcriptome RNA sequencing was performed on 100 AML cases and HAMLET results were validated by reference assays and targeted resequencing. The data showed that HAMLET accurately detected all fusion genes and overexpression of EVI1 irrespective of 3q26 aberrations. In addition, small variants in 13 genes that are often mutated in AML were called with 99.2% sensitivity and 100% specificity, and tandem duplications in FLT3 and KMT2A were detected by a novel algorithm based on soft-clipped reads with 100% sensitivity and 97.1% specificity. In conclusion, HAMLET has the potential to provide accurate comprehensive diagnostic information relevant for AML classification, risk assessment and targeted therapy on a single technology platform.