TBL1XR1 Mutations Drive Extranodal Lymphoma by Inducing a Pro-tumorigenic Memory Fate.

The most aggressive B cell lymphomas frequently manifest extranodal distribution and carry somatic mutations in the poorly characterized gene TBL1XR1. Here, we show that TBL1XR1 mutations skew the humoral immune response toward generating abnormal immature memory B cells (MB), while impairing plasma cell differentiation. At the molecular level, TBL1XR1 mutants co-opt SMRT/HDAC3 repressor complexes toward binding the MB cell transcription factor (TF) BACH2 at the expense of the germinal center (GC) TF BCL6, leading to pre-memory transcriptional reprogramming and cell-fate bias. Upon antigen recall, TBL1XR1 mutant MB cells fail to differentiate into plasma cells and instead preferentially reenter new GC reactions, providing evidence for a cyclic reentry lymphomagenesis mechanism. Ultimately, TBL1XR1 alterations lead to a striking extranodal immunoblastic lymphoma phenotype that mimics the human disease. Both human and murine lymphomas feature expanded MB-like cell populations, consistent with a MB-cell origin and delineating an unforeseen pathway for malignant transformation of the immune system.

Motive and Opportunity: MYC rearrangements in high-grade B-cell lymphoma with MYC and BCL2 rearrangements-an LLMPP study.

Rearrangements that place the oncogenes MYC, BCL2, or BCL6 adjacent to superenhancers are common in mature B-cell lymphomas. Lymphomas with diffuse large B-cell lymphoma (DLBCL) or high-grade morphology with both MYC and BCL2 rearrangements are classified as high-grade B-cell lymphoma with MYC and BCL2 rearrangements ("double hit": HGBCL-DH-BCL2) and are associated with aggressive disease and poor outcomes. Although it is established that MYC rearrangements involving immunoglobulin (IG) loci are associated with inferior outcomes relative to those involving other non-IG superenhancers, the frequency of, and mechanisms driving, IG vs non-IG MYC rearrangements have not been elucidated. Here we used custom targeted capture and/or whole genome sequencing to characterize oncogene rearrangements across 883 mature B-cell lymphomas including Burkitt lymphoma, follicular lymphoma, DLBCL, and HGBCL-DH-BCL2 tumors. We demonstrate that, while BCL2 rearrangement topology is consistent across entities, HGBCL-DH-BCL2 have distinct MYC rearrangement architecture relative to tumors with single MYC rearrangements or with both MYC and BCL6 rearrangements (HGBCL-DH-BCL6), including both a higher frequency of non-IG rearrangements and different architecture of MYC::IGH rearrangements. The distinct MYC rearrangement patterns in HGBCL-DH-BCL2 occur on the background of high levels of somatic hypermutation across MYC partner loci in HGBCL-DH-BCL2, creating more opportunity to form these rearrangements. Furthermore, because one IGH allele is already disrupted by the existing BCL2 rearrangement, the MYC rearrangement architecture in HGBCL-DH-BCL2 likely reflects selective pressure to preserve both BCL2 and B cell receptor expression. These data provide new mechanistic explanations for the distinct patterns of MYC rearrangements observed across different lymphoma entities.

Noncanonical ß-catenin interactions promote leukemia-initiating activity in early T-cell acute lymphoblastic leukemia.

T-cell acute lymphoblastic leukemia (T-ALL) is a T-cell malignancy characterized by cell subsets and enriched with leukemia-initiating cells (LICs). ß-Catenin modulates LIC activity in T-ALL. However, its role in maintaining established leukemia stem cells remains largely unknown. To identify functionally relevant protein interactions of ß-catenin in T-ALL, we performed coimmunoprecipitation followed by liquid chromatography-mass spectrometry. Here, we report that a noncanonical functional interaction of ß-catenin with the Forkhead box O3 (FOXO3) transcription factor positively regulates LIC-related genes, including the cyclin-dependent kinase 4, which is a crucial modulator of cell cycle and tumor maintenance. We also confirm the relevance of these findings using stably integrated fluorescent reporters of ß-catenin and FOXO3 activity in patient-derived xenografts, which identify minor subpopulations with enriched LIC activity. In addition, gene expression data at the single-cell level of leukemic cells of primary patients at the time of diagnosis and minimal residual disease (MRD) up to 30 days after the standard treatments reveal that the expression of ß-catenin- and FOXO3-dependent genes is present in the CD82+CD117+ cell fraction, which is substantially enriched with LICs in MRD as well as in early T-cell precursor ALL. These findings highlight key functional roles for ß-catenin and FOXO3 and suggest novel therapeutic strategies to eradicate aggressive cell subsets in T-ALL.

SpatialSort: a Bayesian model for clustering and cell population annotation of spatial proteomics data.

MOTIVATION: Recent advances in spatial proteomics technologies have enabled the profiling of dozens of proteins in thousands of single cells in situ. This has created the opportunity to move beyond quantifying the composition of cell types in tissue, and instead probe the spatial relationships between cells. However, most current methods for clustering data from these assays only consider the expression values of cells and ignore the spatial context. Furthermore, existing approaches do not account for prior information about the expected cell populations in a sample. RESULTS: To address these shortcomings, we developed SpatialSort, a spatially aware Bayesian clustering approach that allows for the incorporation of prior biological knowledge. Our method is able to account for the affinities of cells of different types to neighbour in space, and by incorporating prior information about expected cell populations, it is able to simultaneously improve clustering accuracy and perform automated annotation of clusters. Using synthetic and real data, we show that by using spatial and prior information SpatialSort improves clustering accuracy. We also demonstrate how SpatialSort can perform label transfer between spatial and nonspatial modalities through the analysis of a real world diffuse large B-cell lymphoma dataset. AVAILABILITY AND IMPLEMENTATION: Source code is available on Github at: https://github.com/Roth-Lab/SpatialSort.

Tcf1 is essential for initiation of oncogenic Notch1-driven chromatin topology in T-ALL.

NOTCH1 is a well-established lineage specifier for T cells and among the most frequently mutated genes throughout all subclasses of T cell acute lymphoblastic leukemia (T-ALL). How oncogenic NOTCH1 signaling launches a leukemia-prone chromatin landscape during T-ALL initiation is unknown. Here we demonstrate an essential role for the high-mobility-group transcription factor Tcf1 in orchestrating chromatin accessibility and topology, allowing aberrant Notch1 signaling to convey its oncogenic function. Although essential, Tcf1 is not sufficient to initiate leukemia. The formation of a leukemia-prone epigenetic landscape at the distal Notch1-regulated Myc enhancer, which is fundamental to this disease, is Tcf1-dependent and occurs within the earliest progenitor stage even before cells adopt a T lymphocyte or leukemic fate. Moreover, we discovered a unique evolutionarily conserved Tcf1-regulated enhancer element in the distal Myc-enhancer, which is important for the transition of preleukemic cells to full-blown disease.

Single-cell profiling reveals the importance of CXCL13/CXCR5 axis biology in lymphocyte-rich classic Hodgkin lymphoma.

Lymphocyte-rich classic Hodgkin lymphoma (LR-CHL) is a rare subtype of Hodgkin lymphoma. Recent technical advances have allowed for the characterization of specific cross-talk mechanisms between malignant Hodgkin Reed-Sternberg (HRS) cells and different normal immune cells in the tumor microenvironment (TME) of CHL. However, the TME of LR-CHL has not yet been characterized at single-cell resolution. Here, using single-cell RNA sequencing (scRNA-seq), we examined the immune cell profile of 8 cell suspension samples of LR-CHL in comparison to 20 samples of the mixed cellularity (MC, 9 cases) and nodular sclerosis (NS, 11 cases) subtypes of CHL, as well as 5 reactive lymph node controls. We also performed multicolor immunofluorescence (MC-IF) on tissue microarrays from the same patients and an independent validation cohort of 31 pretreatment LR-CHL samples. ScRNA-seq analysis identified a unique CD4+ helper T cell subset in LR-CHL characterized by high expression of Chemokine C-X-C motif ligand 13 (CXCL13) and PD-1. PD-1+CXCL13+ T cells were significantly enriched in LR-CHL compared to other CHL subtypes, and spatial analyses revealed that in 46% of the LR-CHL cases these cells formed rosettes surrounding HRS cells. MC-IF analysis revealed CXCR5+ normal B cells in close proximity to CXCL13+ T cells at significantly higher levels in LR-CHL. Moreover, the abundance of PD-1+CXCL13+ T cells in the TME was significantly associated with shorter progression-free survival in LR-CHL (P = 0.032). Taken together, our findings strongly suggest the pathogenic importance of the CXCL13/CXCR5 axis and PD-1+CXCL13+ T cells as a treatment target in LR-CHL.

Probabilistic cell-type assignment of single-cell RNA-seq for tumor microenvironment profiling.

Single-cell RNA sequencing has enabled the decomposition of complex tissues into functionally distinct cell types. Often, investigators wish to assign cells to cell types through unsupervised clustering followed by manual annotation or via 'mapping' to existing data. However, manual interpretation scales poorly to large datasets, mapping approaches require purified or pre-annotated data and both are prone to batch effects. To overcome these issues, we present CellAssign, a probabilistic model that leverages prior knowledge of cell-type marker genes to annotate single-cell RNA sequencing data into predefined or de novo cell types. CellAssign automates the process of assigning cells in a highly scalable manner across large datasets while controlling for batch and sample effects. We demonstrate the advantages of CellAssign through extensive simulations and analysis of tumor microenvironment composition in high-grade serous ovarian cancer and follicular lymphoma.

MYC-induced human acute myeloid leukemia requires a continuing IL-3/GM-CSF costimulus.

Hematopoietic clones with leukemogenic mutations arise in healthy people as they age, but progression to acute myeloid leukemia (AML) is rare. Recent evidence suggests that the microenvironment may play an important role in modulating human AML population dynamics. To investigate this concept further, we examined the combined and separate effects of an oncogene (c-MYC) and exposure to interleukin-3 (IL-3), granulocyte-macrophage colony-stimulating factor (GM-CSF), and stem cell factor (SCF) on the experimental genesis of a human AML in xenografted immunodeficient mice. Initial experiments showed that normal human CD34+ blood cells transduced with a lentiviral MYC vector and then transplanted into immunodeficient mice produced a hierarchically organized, rapidly fatal, and serially transplantable blast population, phenotypically and transcriptionally similar to human AML cells, but only in mice producing IL-3, GM-CSF, and SCF transgenically or in regular mice in which the cells were exposed to IL-3 or GM-CSF delivered using a cotransduction strategy. In their absence, the MYC+ human cells produced a normal repertoire of lymphoid and myeloid progeny in transplanted mice for many months, but, on transfer to secondary mice producing the human cytokines, the MYC+ cells rapidly generated AML. Indistinguishable diseases were also obtained efficiently from both primitive (CD34+CD38-) and late granulocyte-macrophage progenitor (GMP) cells. These findings underscore the critical role that these cytokines can play in activating a malignant state in normally differentiating human hematopoietic cells in which MYC expression has been deregulated. They also introduce a robust experimental model of human leukemogenesis to further elucidate key mechanisms involved and test strategies to suppress them.

Avadomide monotherapy in relapsed/refractory DLBCL: safety, efficacy, and a predictive gene classifier.

Treatment options for relapsed/refractory (R/R) diffuse large B-cell lymphoma (DLBCL) are limited, with no standard of care; prognosis is poor, with 4- to 6-month median survival. Avadomide (CC-122) is a cereblon-modulating agent with immunomodulatory and direct antitumor activities. This phase 1 dose-expansion study assessed safety and clinical activity of avadomide monotherapy in patients with de novo R/R DLBCL and transformed lymphoma. Additionally, a novel gene expression classifier, which identifies tumors with a high immune cell infiltration, was shown to enrich for response to avadomide in R/R DLBCL. Ninety-seven patients with R/R DLBCL, including 12 patients with transformed lymphoma, received 3 to 5 mg avadomide administered on continuous or intermittent schedules until unacceptable toxicity, disease progression, or withdrawal. Eighty-two patients (85%) experienced ≥1 grade 3/4 treatment-emergent adverse events (AEs), most commonly neutropenia (51%), infections (24%), anemia (12%), and febrile neutropenia (10%). Discontinuations because of AEs occurred in 10% of patients. Introduction of an intermittent 5/7-day schedule improved tolerability and reduced frequency and severity of neutropenia, febrile neutropenia, and infections. Among 84 patients with de novo R/R DLBCL, overall response rate (ORR) was 29%, including 11% complete response (CR). Responses were cell-of-origin independent. Classifier-positive DLBCL patients (de novo) had an ORR of 44%, median progression-free survival (mPFS) of 6 months, and 16% CR vs an ORR of 19%, mPFS of 1.5 months, and 5% CR in classifier-negative patients (P = .0096). Avadomide is being evaluated in combination with other antilymphoma agents. This trial was registered at www.clinicaltrials.gov as #NCT01421524.

Single Cell Phenotypic Profiling of 27 DLBCL Cases Reveals Marked Intertumoral and Intratumoral Heterogeneity.

Diffuse large B-cell lymphoma (DLBCL) is the most common histologic subtype of non-Hodgkin lymphoma and is notorious for its clinical heterogeneity. Patient outcomes can be predicted by cell-of-origin (COO) classification, demonstrating that the underlying transcriptional signature of malignant B-cells informs biological behavior in the context of standard combination chemotherapy regimens. In the current study, we used mass cytometry (CyTOF) to examine tumor phenotypes at the protein level with single cell resolution in a collection of 27 diagnostic DLBCL biopsy specimens from treatment naïve patients. We found that malignant B-cells from each patient occupied unique regions in 37-dimensional phenotypic space with no apparent clustering of samples into discrete subtypes. Interestingly, variable MHC class II expression was found to be the greatest contributor to phenotypic diversity. Within individual tumors, a subset of cases showed multiple phenotypic subpopulations, and in one case, we were able to demonstrate direct correspondence between protein-level phenotypic subsets and DNA mutation-defined subclones. In summary, CyTOF analysis can resolve both intertumoral and intratumoral heterogeneity among primary samples and reveals that each case of DLBCL is unique and may be comprised of multiple, genetically distinct subclones. © 2019 International Society for Advancement of Cytometry.

Targeting transcription regulation in cancer with a covalent CDK7 inhibitor.

Tumour oncogenes include transcription factors that co-opt the general transcriptional machinery to sustain the oncogenic state, but direct pharmacological inhibition of transcription factors has so far proven difficult. However, the transcriptional machinery contains various enzymatic cofactors that can be targeted for the development of new therapeutic candidates, including cyclin-dependent kinases (CDKs). Here we present the discovery and characterization of a covalent CDK7 inhibitor, THZ1, which has the unprecedented ability to target a remote cysteine residue located outside of the canonical kinase domain, providing an unanticipated means of achieving selectivity for CDK7. Cancer cell-line profiling indicates that a subset of cancer cell lines, including human T-cell acute lymphoblastic leukaemia (T-ALL), have exceptional sensitivity to THZ1. Genome-wide analysis in Jurkat T-ALL cells shows that THZ1 disproportionally affects transcription of RUNX1 and suggests that sensitivity to THZ1 may be due to vulnerability conferred by the RUNX1 super-enhancer and the key role of RUNX1 in the core transcriptional regulatory circuitry of these tumour cells. Pharmacological modulation of CDK7 kinase activity may thus provide an approach to identify and treat tumour types that are dependent on transcription for maintenance of the oncogenic state.

Defining the clonality of peripheral T cell lymphomas using RNA-seq.

Motivation: In T-cell lymphoma, malignant T cells arising from a founding clone share an identical T cell receptor (TCR) and can be identified by the over-representation of this TCR relative to TCRs from the patient's repertoire of normal T cells. Here, we demonstrate that TCR information extracted from RNA-seq data can provide a higher resolution view of peripheral T cell lymphomas (PTCLs) than that provided by conventional methods. Results: For 60 subjects with PTCL, flow cytometry/FACS was used to identify and sort aberrant T cell populations from diagnostic lymph node cell suspensions. For samples that did not appear to contain aberrant T cell populations, T helper (T H ), T follicular helper (T FH ) and cytotoxic T lymphocyte (CTL) subsets were sorted. RNA-seq was performed on sorted T cell populations, and TCR alpha and beta chain sequences were extracted and quantified directly from the RNA-seq data. 96% of the immunophenotypically aberrant samples had a dominant T cell clone readily identifiable by RNA-seq. Of the samples where no aberrant population was found by flow cytometry, 80% had a dominant clone by RNA-seq. This demonstrates the increased sensitivity and diagnostic ability of RNA-seq over flow cytometry and shows that the presence of a normal immunophenotype does not exclude clonality. Availability and Implementation: R scripts used in the processing of the data are available online at https://www.github.com/scottdbrown/RNAseq-TcellClonality. Contacts: rholt@bcgsc.ca or ksavage@bccancer.bc.ca. Supplementary information: Supplementary data are available at Bioinformatics online.

Leukemia stem cells in T-ALL require active Hif1α and Wnt signaling.

The Wnt signaling pathway has been shown to play important roles in normal hematopoietic stem cell biology and in the development of both acute and chronic myelogenous leukemia. Its role in maintaining established leukemia stem cells, which are more directly relevant to patients with disease, however, is less clear. To address what role Wnt signaling may play in T-cell acute lymphoblastic leukemia (T-ALL), we used a stably integrated fluorescent Wnt reporter construct to interrogate endogenous Wnt signaling activity in vivo. In this study, we report that active Wnt signaling is restricted to minor subpopulations within bulk tumors, that these Wnt-active subsets are highly enriched for leukemia-initiating cells (LICs), and that genetic inactivation of ß-catenin severely reduces LIC frequency. We show further that ß-catenin transcription is upregulated by hypoxia through hypoxia-inducible factor 1α (Hif1α) stabilization, and that deletion of Hif1α also severely reduces LIC frequency. Of note, the deletion of ß-catenin or Hif1α did not impair the growth or viability of bulk tumor cells, suggesting that elements of the Wnt and Hif pathways specifically support leukemia stem cells. We also confirm the relevance of these findings to human disease using cell lines and patient-derived xenografts, suggesting that targeting these pathways could benefit patients with T-ALL.

Modeling de novo leukemogenesis from human cord blood with MN1 and NUP98HOXD13.

Leukemic transformation of human cells is a complex process. Here we show that forced expression of MN1 in primitive human cord blood cells maintained on stromal cells in vitro induces a transient, but not serially transplantable, myeloproliferation in engrafted mice. However, cotransduction of an activated HOX gene (NUP98HOXD13) with MN1 induces a serially transplantable acute myeloid leukemia (AML). Further characterization of the leukemic cells generated from the dually transduced cells showed the activation of stem cell gene expression signatures also found in primary human AML. These findings show a new forward genetic model of human leukemogenesis and further highlight the relevance of homeobox transcription factors in the transformation process.

Focused chemical genomics using zebrafish xenotransplantation as a pre-clinical therapeutic platform for T-cell acute lymphoblastic leukemia.

Cancer therapeutics is evolving to precision medicine, with the goal of matching targeted compounds with molecular aberrations underlying a patient's cancer. While murine models offer a pre-clinical tool, associated costs and time are not compatible with actionable patient-directed interventions. Using the paradigm of T-cell acute lymphoblastic leukemia, a high-risk disease with defined molecular underpinnings, we developed a zebrafish human cancer xenotransplantation model to inform therapeutic decisions. Using a focused chemical genomic approach, we demonstrate that xenografted cell lines harboring mutations in the NOTCH1 and PI3K/AKT pathways respond concordantly to their targeted therapies, patient-derived T-cell acute lymphoblastic leukemia can be successfully engrafted in zebrafish and specific drug responses can be quantitatively determined. Using this approach, we identified a mutation sensitive to γ-secretase inhibition in a xenograft from a child with T-cell acute lymphoblastic leukemia, confirmed by Sanger sequencing and validated as a gain-of-function NOTCH1 mutation. The zebrafish xenotransplantation platform provides a novel cost-effective means of tailoring leukemia therapy in real time.

Whole transcriptome sequencing reveals recurrent NOTCH1 mutations in mantle cell lymphoma.

Mantle cell lymphoma (MCL), an aggressive subtype of non-Hodgkin lymphoma, is characterized by the hallmark translocation t(11;14)(q13;q32) and the resulting overexpression of cyclin D1 (CCND1). Our current knowledge of this disease encompasses frequent secondary cytogenetic aberrations and the recurrent mutation of a handful of genes, such as TP53, ATM, and CCND1. However, these findings insufficiently explain the biologic underpinnings of MCL. Here, we performed whole transcriptome sequencing on a discovery cohort of 18 primary tissue MCL samples and 2 cell lines. We found recurrent mutations in NOTCH1, a finding that we confirmed in an extension cohort of 108 clinical samples and 8 cell lines. In total, 12% of clinical samples and 20% of cell lines harbored somatic NOTCH1 coding sequence mutations that clustered in the PEST domain and predominantly consisted of truncating mutations or small frame-shifting indels. NOTCH1 mutations were associated with poor overall survival (P = .003). Furthermore, we showed that inhibition of the NOTCH pathway reduced proliferation and induced apoptosis in 2 MCL cell lines. In summary, we have identified recurrent NOTCH1 mutations that provide the preclinical rationale for therapeutic inhibition of the NOTCH pathway in a subset of patients with MCL.

MAGIC-DR: An interpretable machine-learning guided approach for acute myeloid leukemia measurable residual disease analysis.

Multiparameter flow cytometry is widely used for acute myeloid leukemia minimal residual disease testing (AML MRD) but is time consuming and demands substantial expertise. Machine learning offers potential advancements in accuracy and efficiency, but has yet to be widely adopted for this application. To explore this, we trained single cell XGBoost classifiers from 98 diagnostic AML cell populations and 30 MRD negative samples. Performance was assessed by cross-validation. Predictions were integrated with UMAP as a heatmap parameter for an augmented/interactive AML MRD analysis framework, which was benchmarked against traditional MRD analysis for 25 test cases. The results showed that XGBoost achieved a median AUC of 0.97, effectively distinguishing diverse AML cell populations from normal cells. When integrated with UMAP, the classifiers highlighted MRD populations against the background of normal events. Our pipeline, MAGIC-DR, incorporated classifier predictions and UMAP into flow cytometry standard (FCS) files. This enabled a human-in-the-loop machine learning guided MRD workflow. Validation against conventional analysis for 25 MRD samples showed 100% concordance in myeloid blast detection, with MAGIC-DR also identifying several immature monocytic populations not readily found by conventional analysis. In conclusion, Integrating a supervised classifier with unsupervised dimension reduction offers a robust method for AML MRD analysis that can be seamlessly integrated into conventional workflows. Our approach can support and augment human analysis by highlighting abnormal populations that can be gated on for quantification and further assessment. This has the potential to speed up MRD analysis, and potentially improve detection sensitivity for certain AML immunophenotypes.

Integrated single cell analysis reveals co-evolution of malignant B cells and tumor micro-environment in transformed follicular lymphoma.

Histological transformation of follicular lymphoma (FL) to aggressive forms is associated with poor outcome. Phenotypic consequences of this evolution and its impact on the tumor microenvironment (TME) remain unknown. We perform single-cell whole genome sequencing (scWGS) and transcriptome sequencing (scWTS) of 11 paired pre/post-transformation patient samples and scWTS of additional samples from patients without transformation. Our analysis reveals evolutionary dynamics of transformation at single-cell resolution, highlighting a shifting TME landscape, with an emerging immune-cell exhaustion signature, co-evolving with the shifting malignant B phenotype in a regulatory ecosystem. Integration of scWGS and scWTS identifies malignant cell pathways upregulated during clonal tumor evolution. Using multi-color immunofluorescence, we transfer these findings to a TME-based transformation biomarker, subsequently validated in two independent pretreatment cohorts. Taken together, our results provide a comprehensive view of the combined genomic and phenotypic evolution of malignant cells during transformation and shifting crosstalk between malignant cells and the TME.

ARID1A orchestrates SWI/SNF-mediated sequential binding of transcription factors with ARID1A loss driving pre-memory B cell fate and lymphomagenesis.

ARID1A, a subunit of the canonical BAF nucleosome remodeling complex, is commonly mutated in lymphomas. We show that ARID1A orchestrates B cell fate during the germinal center (GC) response, facilitating cooperative and sequential binding of PU.1 and NF-kB at crucial genes for cytokine and CD40 signaling. The absence of ARID1A tilts GC cell fate toward immature IgM+CD80-PD-L2- memory B cells, known for their potential to re-enter new GCs. When combined with BCL2 oncogene, ARID1A haploinsufficiency hastens the progression of aggressive follicular lymphomas (FLs) in mice. Patients with FL with ARID1A-inactivating mutations preferentially display an immature memory B cell-like state with increased transformation risk to aggressive disease. These observations offer mechanistic understanding into the emergence of both indolent and aggressive ARID1A-mutant lymphomas through the formation of immature memory-like clonal precursors. Lastly, we demonstrate that ARID1A mutation induces synthetic lethality to SMARCA2/4 inhibition, paving the way for potential precision therapy for high-risk patients.

Spatially Resolved Tumor Microenvironment Predicts Treatment Outcomes in Relapsed/Refractory Hodgkin Lymphoma.

PURPOSE: About a third of patients with relapsed or refractory classic Hodgkin lymphoma (r/r CHL) 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. PATIENTS AND METHODS: We performed imaging mass cytometry (IMC) on 71 paired primary diagnostic and relapse biopsies using a marker panel specific to 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 the close interaction range. Spatial scores were used as features in prognostic model development for post-ASCT outcomes. RESULTS: Highly multiplexed IMC data revealed shared TME patterns in paired diagnostic and early r/r 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+ Hodgkin and Reed Sternberg (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, CD68+ tumor-associated macrophages, and CXCR5+ B cells, which effectively separated patients into high-risk versus 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. CONCLUSION: We 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.