Biology subjects

Scott, D. W.

Publications and source records attributed to Scott, D. W..

13 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

A patient derived xenograft repository capturing clinical and molecular heterogeneity of large B-cell lymphoma

Large B-cell lymphomas (LBCLs) are a clinically and molecularly diverse group of malignancies with a rapidly evolving therapeutic landscape that has introduced new areas of clinical need such as post-CD19 chimeric antigen receptor T (CART19) progression. Patient derived xenograft (PDX) models are an important tool for mechanistic studies and preclinical evaluation of new therapies and can be generated from a variety of clinical contexts that capture tumor-intrinsic resistance mechanisms. We therefore undertook a comprehensive effort to generate PDX models that encompass the molecular landscape of LBCLs and include important clinical scenarios for new drug development. Here we describe the first 48 models within this publicly available repository, capturing the transcriptional and genetic subsets of LBCL. These models also include 23 generated from post-CART progression biopsies which reproduce patterns of progression driven by CD19 mutation or expression loss, as well as tumor cell-intrinsic CART19 resistance that we validate in vivo. STATEMENT OF SIGNIFICANCEYang et al. describe X-LYMPH (Xenografts of Lymphoma), a publicly available and molecularly annotated PDX repository that captures the heterogeneity of large B-cell lymphoma. X-LYMPH includes models of chimeric antigen receptor T cell resistance, providing a shared foundation for mechanistic research and therapeutic development for lymphomas.

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

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↗

bioRxiv2025

The Origin, Diagnosis, and Prognosis of Oligomannose-Type Diffuse Large B Cell Lymphoma

The acquisition of N-glycosylation sites occupied by oligomannose-type glycans in the immunoglobulin complementarity-determining region (CDR) is an early clonal tumor-specific identifier of follicular lymphoma (FL). CDR-located N-glycosylation sites are also acquired in germinal-center-B-cell-like diffuse large B-cell lymphomas (GCB-DLBCL), but their significance is less defined. We used RNA-seq immunoglobulin assembly to determine the frequency and CDR location of the acquired N-glycosylation sites (AGS) in two large independent DLBCL cohorts. Composition of the glycans occupying the AGS was determined using liquid chromatography-mass spectrometry and correlated with cell-of-origin, FL signature (defined by EZB phenotype or BCL2 translocation), transcript profile, and clinical outcome. CDR-located AGS were observed in 41-46% of GCB-DLBCL but were rare in other DLBCL. Only CDR-located AGS of DLBCL with an FL signature were occupied by oligomannose-type glycans. These DLBCL were termed Mann-type DLBCL. Conversely, the AGS of the other DLBCL were either non-glycosylated or occupied by complex-type glycans. Mann-type status was an independent marker of short progression-free survival and overall survival. In contrast, the other GCB-DLBCL cases, including those with an FL signature but without AGS, had the best outcomes. Mann-type DLBCL overexpressed gene-sets of cell growth, survival, and cycling, and underexpressed proinflammatory and apoptotic pathways, irrespective of concomitant MYC translocations. Acquisition of Mann-type glycans is a highly selective environmental pressure, identifying the most aggressive GCB-DLBCL with an origin related to FL. The detection of AGS in the CDR of GCB-DLBCLs with a BCL2 translocation defines Mann-type DLBCLs, refines prognosis and marks a precise tumor interaction to block early therapeutically. Key pointsO_LIAcquisition of Mann-type glycans is a tumor-specific environmental pressure identifying the most aggressive GCB-DLBCL with an origin related to FL. C_LIO_LIMann-type DLBCL can be diagnosed by the concomitant detection of AGS in the CDR and a BCL2 translocation. C_LI

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

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

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↗

bioRxiv2020

Robust gene expression-based classification of cancers without normalization

Binary classification using gene expression data is commonly used to stratify cancers into molecular subgroups that may have distinct prognoses and therapeutic options. A limitation of many such methods is the requirement for comparable training and testing data sets. Here, we describe and demonstrate a self-training implementation of probability ratio-based classification prediction score (PRPS-ST) that facilitates the porting of existing classification models to other gene expression data sets. We demonstrate its robustness through application to two binary classification problems in diffuse large B-cell lymphoma using a diverse variety of gene expression data types and normalization methods.

bioinformatics↗

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↗