Biology subjects

Steidl, C.

Publications and source records attributed to Steidl, C..

18 recordsLinked to original sources

bioRxiv2026

Developmental origins of thymic B-cell lymphomas

The thymus provides a specialized niche for lymphocyte differentiation, yet the developmental trajectories of its rare B-cell population and their relationship to thymic B-cell lymphomagenesis remain poorly understood. Here, we integrate single-cell multiomics and spatial profiling across human tissues to delineate a B-cell differentiation program selectively represented in the human thymus. This program links CCL17 and germinal center-like B-cell states along a trajectory distinct from canonical germinal center differentiation and can be recapitulated in vitro by signals operating in the thymic medulla. Extending this framework across human B-cell lymphomas, we identify an inherent malignant cell state in PMBCL that shares transcriptional and epigenetic features with CCL17 thymic B cells. This malignant state associates with early clonal positions in reconstructed B-cell receptor phylogenies and persists within tumor microenvironments distinct from the thymic niche. Together, these findings support a model in which thymus-specific B-cell differentiation programs are redeployed during thymic B-cell lymphomagenesis.

cancer biology↗

bioRxiv2026

Single-cell spatial multi-omic characterization of the tumour microenvironment in transformed follicular lymphoma

Histological examination of follicular lymphoma (FL) biopsies remains the cornerstone for diagnostic grading of FL. Single-cell sequencing approaches, while transcriptomically rich, require tissue dissociation and lose the native spatial context that underpins FL transformation to diffuse large B-cell lymphoma (DLBCL). To investigate the spatial interplay between malignant B-cells and the tumour microenvironment (TME) across disease states, we performed subcellular single-cell spatial transcriptomics and spatial proteomics on 12 paired pre/post-transformation samples and 10 non-transforming FL controls, integrated with matched single-cell whole genome sequencing (scWGS). Our analysis reveals that transformation is accompanied by a shift toward B-cell-predominant stromal and immunosuppressive cellular neighbourhoods, where the magnitude of expansion correlates with time to transformation. Prior to transformation, immunomodulatory Galectin-9 interactions move from the intra-follicular core to the extra-follicular space. Integration with scWGS demonstrates that high copy-number instability in malignant B-cells is associated with reduced supportive T-cell niches and intensified immunoregulatory crosstalk at the transformed state. Collectively, our multi-omic analysis characterizes TME remodeling during FL transformation, contributing to a refined disease evolution model.

bioinformatics↗

bioRxiv2026

Spatial Proteomics Reveals Dual-Compartment Immune Evasion Architecture and Core Lymphomagenic Stromal Niches in Follicular Lymphoma

Follicular lymphomas (FL) depend on microenvironmental signals for survival, and the composition of the tumor microenvironment may influence clinical outcome. How it is spatially organized, and how that organization drives immune evasion, has not been established. We applied two complementary 39-marker imaging mass cytometry panels to 156 follicular lymphoma tumor cores, generating a spatial atlas of 4.2 million cells resolved into nine tissue compartments. FL follicles operated as immune-privileged zones: CD8 T cells were largely excluded, and those that did infiltrate were exhausted in a gradient that peaked at the GC core and dissolved at the follicle boundary. A Treg-enriched barrier at that boundary separated the intrafollicular program from an effector-rich interfollicular compartment. Within follicles, CD14-high follicular dendritic cells defined an activated stromal niche that supported tumor B cell proliferation and predicted shorter progression-free and overall survival. Across patients, per-cell CD14 intensity was the strongest predictor of progression, remaining prognostic independently of FLIPI, grade, and stage. VISTA, not PD-L1, dominated checkpoint expression across all myeloid subtypes in both follicular and interfollicular zones, and was further amplified on M2 macrophages in patients carrying EP300 mutations. S100A9+ MDSC-like cells were the strongest myeloid predictor of histologic transformation. Agent-based modeling of this architecture predicted synergistic tumor clearance when anti-VISTA was combined with a CD20-CD3 bispecific antibody. These findings establish that FL uses tissue architecture as an immune evasion mechanism and identify VISTA and CD14-high follicular dendritic cells as candidate therapeutic targets.

Cancer Biology↗

bioRxiv2025

LCR-modules: a collection of workflows for cancer genome analysis

The surge of genomic data from advanced sequencing technologies is outpacing current analytical pipelines. We introduce LCR-modules, an open-source suite of bioinformatics tools designed for flexible and automated cancer genome data analysis. LCR-modules enables reproducible analysis of diverse cancer genomics data at scale. The suite comprises 49 Snakemake-based workflows organized into three levels, facilitating tasks from low-level quality control to complex cohort-level analyses. LCR-modules supports various sequencing types and integrates pipelines such as mutation calling, expression quantification, and cohort-level aggregation, ensuring flexibility and reproducibility. LCR-modules represents a significant advancement in genomic data analysis, reducing barriers in reproducibility and scalability and has already been applied to a combination of exomes and genomes from over 10,800 samples.

bioinformatics↗

bioRxiv2025

Prognostically favorable immune responses to ovarian cancer are distinguished by self-reactive intra-epithelial plasma cells

Tumor-infiltrating B cells (TIL-Bs) are strongly associated with patient survival; however, the underlying mechanisms are poorly understood. Using integrated single-cell and spatial biology approaches, we defined at clonal resolution the molecular phenotypes, tumor reactivity patterns, and microenvironmental locations of TIL-Bs in high-grade serous ovarian cancer (HGSC). Prognostic benefit was associated with a TIL-B-rich tumor microenvironment with marked infiltration of malignant epithelium by plasma cells (PCs). PCs spanned five molecular phenotypes; exhibited high rates of somatic hypermutation and clonal expansion; and expressed predominantly IgG1 antibodies recognizing broadly expressed nuclear, cytoplasmic, and cell surface self-antigens. Many PC-derived antibodies were polyreactive. Self- and poly-reactive TIL-Bs penetrated tumor epithelium and stroma and expressed interferon-stimulated genes, indicating strong in situ activation. The self- and poly-reactive nature of TIL-B responses, reminiscent of autoimmune disease, may provide a means for the immune system to combat tumor heterogeneity and could potentially be harnessed for more effective immunotherapy.

cancer biology↗

bioRxiv2025

Multidimensional characterization of cellular ecosystems in Hodgkin lymphoma

The tissue architecture of classic Hodgkin Lymphoma (CHL) is unique among cancers and characterized by rare malignant Hodgkin and Reed-Sternberg cells that co-evolve with a complex ecosystem of immune cells in the tumor microenvironment (TME). The lack of a comprehensive systems-level interrogation has hindered the description of disease heterogeneity and clinically relevant molecular subtypes. Here, we employed an integrative, multimodal approach to characterize CHL tumors using malignant cell sequencing, spatial transcriptomics and imaging mass cytometry. We identified four molecular subtypes (CST, CN913, STB, and CN2P), each characterized by distinct clinical features, mutational patterns, malignant cell gene expression profiles, and spatial architecture involving immune cell populations. Functional modeling of CSF2RB mutations, a characteristic feature of the CST subtype, revealed dysregulated oncogenic signaling and unique TME crosstalk. These findings highlight the significance of multi-dimensional profiling in elucidating patterns of molecular alterations that drive immune ecosystems and underlie therapeutically exploitable vulnerabilities.

cancer biology↗

bioRxiv2024

Integrative genomic analysis identifies unique immune environments associated with immunotherapy response in diffuse large B cell lymphoma

Most diffuse large B-cell lymphoma (DLBCL) patients treated with bispecific antibodies (BsAb) or chimeric antigen receptor (CAR) T cells fail to achieve durable treatment responses, underscoring the need for a deeper understanding of mechanisms that regulate the immune environment and response to treatment. Here, an integrative, multi-omic approach was employed to characterize DLBCL immune environments, which effectively segregated DLBCLs into four quadrants - termed DLBCL-immune quadrants (IQ) - defined by cell-of-origin and immune-related gene set expression scores. Recurrent genomic alterations were enriched in each IQ, suggesting that lymphoma cell-intrinsic alterations contribute to orchestrating unique DLBCL immune environments. In relapsed/refractory DLBCL patients, DLBCL-IQ assignment correlated significantly with clinical benefit with the CD20 x CD3 BsAb, mosunetuzumab, but not with CD19-directed CAR T cells. DLBCL-IQ provides a new framework to conceptualize the DLBCL immune landscape and uncovers the differential impact of the endogenous immune environment on outcomes to BsAb and CAR T cell treatment.

cancer biology↗

bioRxiv2023

ESQmodel: biologically informed evaluation of 2-D cell segmentation quality in multiplexed tissue images

MotivationSingle cell segmentation is critical in the processing of spatial omics data to accurately perform cell type identification and analyze spatial expression patterns. Segmentation methods often rely on semi-supervised annotation or labeled training data which are highly dependent on user expertise. To ensure the quality of segmentation, current evaluation strategies quantify accuracy by assessing cellular masks or through iterative inspection by pathologists. While these strategies each address either the statistical or biological aspects of segmentation, there lacks an unified approach to evaluating segmentation accuracy. ResultsIn this paper, we present ESQmodel, a Bayesian probabilistic method to evaluate single cell segmentation using expression data. By using the extracted cellular data from segmentation and a prior belief of cellular composition as input, ESQmodel computes per cell entropy to assess segmentation quality by how consistent cellular expression profiles match with cell type expectations. Availability and implementationSource code is available on Github at: https://github.com/Roth-Lab/ESQmodel under the MIT license.

bioinformatics↗

bioRxiv2023

Imaging Mass Cytometry-Driven Spatial Analysis and Biomarker Discovery in Hodgkin Lymphoma

The biology of tumors is suffused with spatial interactions, such as tumor-immune signaling through localized cytokine/ligand secretion, cell-cell contacts, and checkpoint ligand/receptor signaling. Hodgkin Lymphoma (HL) can serve as a study paradigm for tumor microenvironment (TME) architecture as the defining pathological feature is the scarcity of the malignant Hodgkin and Reed Sternberg (HRS) cells, leaving a diverse and predominantly immune cell rich tumor microenvironment (TME) with complex tumor-immune interactions. Previous studies have identified TME features that are prognostic and predictive, however these studies did not consider the entirety of TME cellular ecosystems, including precisely defined immune cell subsets with opposing inflammatory and immune-suppressive effects, as a determinant for differential clinical course of HL patients. Here we use Imaging Mass Cytometry (IMC) with 42 antibody markers to profile tumors from 93 patients with HL. Our cohort consists of relapsed/refractory HL with matched diagnostic and relapsed biopsies, and we present a bioinformatic pipeline to profile 10 major cell lineages and their subtypes including spatial interaction mapping. Our pipeline identifies putative biomarker candidates with a focus on "rosettes" - local aggregates of immune cells around single tumor cells. In addition to validating existing biomarkers centered on CD68+ macrophages, GranzymeB+CD8+ T cells, and others in HL, we propose new biomarkers based on localized interactions between HRS cells and aggregating CD4+ and CD8+ T cells and macrophages involving the immune checkpoints PD1/PDL1, LAG3, and Galectin9. This study serves as a broad tissue imaging resource for multi-timepoint biopsies in HL, and a computational resource and pipeline for users of IMC and other multiplexed imaging studies to perform tissue analysis and biomarker candidate testing with any tissue type.

cancer biology↗

bioRxiv2023

The spatially resolved tumor microenvironment predicts treatment outcome in relapsed/refractory Hodgkin lymphoma

PURPOSEAbout a third of relapsed or refractory classic Hodgkin lymphoma (r/r CHL) patients succumb to their disease after high-dose chemotherapy followed by autologous stem cell transplantation (HDC/ASCT). Here, we aimed to describe spatially resolved tumor microenvironment (TME) ecosystems to establish novel biomarkers associated with treatment failure in r/r CHL. METHODSWe performed imaging mass cytometry (IMC) on 169 paired primary diagnostic and relapse biopsies using a marker panel specific for CHL biology. For each cell type in the TME, we calculated a spatial score measuring the distance of nearest neighbor cells to the malignant Hodgkin Reed Sternberg cells within close interaction range. Spatial scores were used as features in prognostic model development for post-ASCT outcomes. RESULTSHighly multiplexed IMC data revealed shared TME patterns in paired diagnostic and early relapse/refractory CHL samples, whereas TME patterns were more divergent in pairs of diagnostic and late relapse samples. Integrated analysis of IMC and single cell RNA sequencing data identified unique architecture defined by CXCR5+ HRS cells and their strong spatial relationship with CXCL13+ macrophages in the TME. We developed a prognostic assay ( RHL4S) using four spatially resolved parameters, CXCR5+ HRS cells, PD1+CD4+ T cells, tumor-associated macrophages, and CXCR5+ B cells, which effectively separated patients into high-risk vs low-risk groups with significantly different post-ASCT outcomes. The RHL4S assay was validated in an independent r/r CHL cohort using a multicolor immunofluorescence assay. CONCLUSIONSWe identified the interaction of CXCR5+ HRS cells with ligand-expressing CXCL13+ macrophages as a prominent crosstalk axis in relapsed CHL. Harnessing this TME biology, we developed a novel prognostic model applicable to r/r CHL biopsies, RHL4S, opening new avenues for spatial biomarker development.

cancer biology↗

bioRxiv2023

Cooperative super-enhancer inactivation caused by heterozygous loss of CREBBP and KMT2D skews B cell fate decisions and yields T cell-depleted lymphomas

Mutations affecting enhancer chromatin regulators CREBBP and KMT2D are highly co-occurrent in germinal center (GC)-derived lymphomas and other tumors, even though regulating similar pathways. Herein, we report that combined haploinsufficiency of Crebbp and Kmt2d (C+K) indeed accelerated lymphomagenesis. C+K haploinsufficiency induced GC hyperplasia by altering cell fate decisions, skewing B cells away from memory and plasma cell differentiation. C+K deficiency particularly impaired enhancer activation for immune synapse genes involved in exiting the GC reaction. This effect was especially severe at super-enhancers for immunoregulatory and differentiation genes. Mechanistically, CREBBP and KMT2D formed a complex, were highly co-localized on chromatin, and were required for each-others stable recruitment to enhancers. Notably, C+K lymphomas in mice and humans manifested significantly reduced CD8+ T-cell abundance. Hence, deficiency of C+K cooperatively induced an immune evasive phenotype due at least in part to failure to activate key immune synapse super-enhancers, associated with altered immune cell fate decisions. SIGNIFICANCEAlthough CREBBP and KMT2D have similar enhancer regulatory functions, they are paradoxically co-mutated in lymphomas. We show that their combined loss causes specific disruption of super-enhancers driving immune synapse genes. Importantly, this leads to reduction of CD8 cells in lymphomas, linking super-enhancer function to immune surveillance, with implications for immunotherapy resistance.

cancer biology↗

bioRxiv2022

Integrated single cell analysis reveals co-evolution of malignant B cells and the tumor microenvironment in transformed follicular lymphoma

Follicular lymphoma (FL) is the most common indolent form of non-Hodgkin lymphoma. Histological transformation of FL to a more aggressive form of lymphoma occurs with a linear incidence of 2-3% per year and is associated with poor outcome. Divergent clonal evolution and an altered tumour microenvironment (TME) have both been implicated in the transformation process. However, the phenotypic consequences of this evolution and its implication in reshaping the TME remain unknown. To address this knowledge gap we performed single cell whole genome (scWGS) and single cell whole transcriptome sequencing (scWTS) of paired pre/post transformation samples of 11 FL patients. We further performed scWTS analysis of additional 11 FL samples from patients that had not undergone transformation within 7 years. Our comprehensive single cell analysis revealed the evolutionary dynamics of transformation at unprecedented resolution. Computational integration of scWGS and scWTS allowed us to identify gene programs upregulated and positively selected during evolution. Furthermore, our scWTS analysis revealed a shifting TME landscape, with an exhausted CD8 T cell signature emerging during transformation. Using multi-color immunofluorescence we transferred these findings to a novel TME based biomarker of transformation, subsequently validated in 2 independent cohorts of pretreatment FL samples. Taken together, our results provide a comprehensive view of the combined genomic and phenotypic evolution of malignant cells during transformation, and the shifting cross-talk between malignant cells and the TME. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=98 SRC="FIGDIR/small/516951v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@92abf7org.highwire.dtl.DTLVardef@157f2c2org.highwire.dtl.DTLVardef@102a879org.highwire.dtl.DTLVardef@182daec_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2021

Unmasking the cryptic immunopeptidome of EZH2 mutated diffuse large B-cell lymphomas through combination drug treatment

Exploring the repertoire of peptides presented on major histocompatibility complexes (MHC) has been utilized to identify targets for immunotherapy in many hematological malignancies. However, such data have not been described systematically for diffuse large B-cell lymphomas (DLBCL), which might be explained by the profound downregulation of MHC expression in many DLBCLs, and in particular in the EZH2-mutated subgroup. Epigenetic drug treatment, especially in the context of interferon gamma (IFNg), restored MHC expression in DLBCL. DLBCL MHC-presented peptides were identified via mass spectrometry following tazemetostat or decitabine treatments alone, or in combination with IFNg. Such treatment synergistically increased MHC class I surface protein expression up to 50-fold and class II expression up to 3-fold. Peptides presented on MHC complexes increased to a similar extent for MHC class I and remained constant for class II. Overall, these treatments restored the diversity of the immunopeptidome to levels described in healthy B cells and allowed the systematic search for new targets for immunotherapy. Consequently, we identified multiple MHC ligands from regulator of G protein signaling 13 (RGS13) and E2F transcription factor 8 (E2F8) on different MHC alleles, none of which have been described in healthy tissues and therefore represent tumor-specific MHC ligands, which are unmasked only after drug treatment. Overall, our results show that EZH2 inhibition in combination with decitabine and IFNg can expand the repertoire of MHC ligands presented on DLBCLs by revealing cryptic epitopes, thus allowing the systematic analysis and identification of new potential immunotherapy targets. Key pointsO_LICombination therapy of interferon gamma with epigenetic regulators leads to large increases in the immunopeptidome of DLBCL. C_LIO_LIHLA ligands from proteins RGS13 and E2F8 may provide DLBCL-specific targets for immunotherapy. C_LI

immunology↗

bioRxiv2021

Non-coding NFKBIZ 3' UTR mutations promote cell growth and resistance to targeted therapies in diffuse large B-cell lymphoma

Amplifications and non-coding 3' UTR mutations affecting NFKBIZ have been identified as recurrent genetic events in diffuse large B-cell lymphoma (DLBCL). We confirm the prevalence and pattern of NFKBIZ 3' UTR mutations in independent cohorts and determine they are enriched in the ABC subtype as well as the recently described novel BN2/C1/NOTCH2 classes of DLBCL. Presently, the effects of and mechanism by which non-coding mutations can act as cancer drivers has been relatively unexplored. Here, we provide a functional characterization of these non-coding NFKBIZ 3' UTR mutations. We demonstrate that the resulting elevated expression of I{kappa}B-{zeta} confers growth advantage in DLBCL cell lines and primary germinal center B-cells as well as nominate novel I{kappa}B-{zeta} target genes with potential therapeutic implications. The limited responses to targeted treatments in DLBCL, particularly those targeting the NF-{kappa}B axis, led us to investigate and confirm that NFKBIZ 3' UTR mutations affect response to therapeutics and suggest it may be a useful predictive biomarker. Statement of SignificanceThrough functional characterization we reveal that non-coding NFKBIZ 3' UTR mutations are a common driver in DLBCL, and mutation status may be a relevant biomarker to predict poor response to therapeutics targeting the NF-{kappa}B pathway.

cancer biology↗

bioRxiv2019

Coding and regulatory drivers of mantle cell lymphoma identified through exome and genome sequencing

Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established and the features known to contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes alongside previously published exome cohorts. To confirm our findings, we re-sequenced the genes identified in the exome cohort in 212 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations and further nominate two additional genes, EWSR1 and MEF2B, whose mutation respectively associated with poor and good outcome. Our sequencing revealed novel recurrent mutations including a unique missense hot spot in MEF2B and a pattern of non-coding mutations surrounding a single exon of the HNRNPH1 gene. We sequenced the whole genomes of 34 MCLs to confirm the focal nature of HNRNPH1 mutations. Using RNA-seq data from 110 of these cases, we identified a functional role for recurrent non-coding HNRNPH1 mutations in disrupting an auto-regulatory feedback mechanism. Overall, we identified three novel MCL-related genes with roles in RNA trafficking or splicing, namely DAZAP1, EWSR1, and HNRNPH1. Taken together, these data strongly implicate a role for aberrant regulation of splicing in MCL pathobiology.\n\nKey pointsO_LIRNA-binding proteins with roles in regulating alternative splicing, DAZAP1, EWSR1, HNRNPH1, are frequently mutated in MCL\nC_LIO_LIThe majority of recurrent somatic HNRNPH1 mutations are intronic and HNRNPH1 exhibits self-regulation through alternative splicing\nC_LI

genomics↗

bioRxiv2019

Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

Single-cell RNA sequencing (scRNA-seq) has transformed biomedical research, enabling decomposition of complex tissues into disaggregated, functionally distinct cell types. For many applications, investigators wish to identify cell types with known marker genes. Typically, such cell type assignments are performed through unsupervised clustering followed by manual annotation based on these marker genes, or via \"mapping\" procedures to existing data. However, the manual interpretation required in the former case scales poorly to large datasets, which are also often prone to batch effects, while existing data for purified cell types must be available for the latter. Furthermore, unsupervised clustering can be error-prone, leading to under- and over- clustering of the cell types of interest. To overcome these issues we present CellAssign, a probabilistic model that leverages prior knowledge of cell type marker genes to annotate scRNA-seq data into pre-defined and de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while simultaneously controlling for batch and patient effects. We demonstrate the analytical advantages of CellAssign through extensive simulations and exemplify real-world utility to profile the spatial dynamics of high-grade serous ovarian cancer and the temporal dynamics of follicular lymphoma. Our analysis reveals subclonal malignant phenotypes and points towards an evolutionary interplay between immune and cancer cell populations with cancer cells escaping immune recognition.

bioinformatics↗

bioRxiv2018

Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires

Essential features of cancer tissue cellular heterogeneity such as negatively selected genome topologies, sub-clonal mutation patterns and genome replication states can only effectively be studied by sequencing single-cell genomes at scale and high fidelity. Using an amplification-free single-cell genome sequencing approach implemented on commodity hardware (DLP+) coupled with a cloud-based computational platform, we define a resource of 40,000 single-cell genomes characterized by their genome states, across a wide range of tissue types and conditions. We show that shallow sequencing across thousands of genomes permits reconstruction of clonal genomes to single nucleotide resolution through aggregation analysis of cells sharing higher order genome structure. From large-scale population analysis over thousands of cells, we identify rare cells exhibiting mitotic mis-segregation of whole chromosomes. We observe that tissue derived scWGS libraries exhibit lower rates of whole chromosome anueploidy than cell lines, and loss of p53 results in a shift in event type, but not overall prevalence in breast epithelium. Finally, we demonstrate that the replication states of genomes can be identified, allowing the number and proportion of replicating cells, as well as the chromosomal pattern of replication to be unambiguously identified in single-cell genome sequencing experiments. The combined annotated resource and approach provide a re-implementable large scale platform for studying lineages and tissue heterogeneity.

genomics↗

bioRxiv2017

Genome-wide discovery of somatic coding and regulatory variants in Diffuse Large B-cell Lymphoma

Diffuse large B-cell lymphoma (DLBCL) is an aggressive cancer originating from mature B-cells. Many known driver mutations are over-represented in one of its two molecular subgroups, knowledge of which has aided in the development of therapeutics that target these features. The heterogeneity of DLBCL determined through prior genomic analysis suggests an incomplete understanding of its molecular aetiology, with a limited diversity of genetic events having thus far been attributed to the activated B-cell (ABC) subgroup. Through an integrative genomic analysis we uncovered genes and non-coding loci that are commonly mutated in DLBCL including putative regulatory sequences. We implicate recurrent mutations in the 3UTR of NFKBIZ as a novel mechanism of oncogene deregulation and found small amplifications associated with over-expression of FC-{gamma} receptor genes. These results inform on mechanisms of NF-{kappa}B pathway activation in ABC DLBCL and may reveal a high-risk population of patients that might not benefit from standard therapeutics.

genomics↗