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Here, we report recurrent focal deletions of the chr14q32.31-32 locus, including TRAF3, a negative regulator of NF-κB signaling, in de novo diffuse large B cell lymphoma (DLBCL) (24/324 cases). Integrative analysis revealed an association between TRAF3 copy number loss with accumulation of NIK, the central noncanonical (NC) NF-κB kinase, and increased NC NF-κB pathway activity. Accordingly, TRAF3 genetic ablation in isogenic DLBCL model systems caused upregulation of NIK and enhanced NC NF-κB downstream signaling. Knockdown or pharmacological inhibition of NIK in TRAF3-deficient cells differentially impaired their proliferation and survival, suggesting an acquired onco-addiction to NC NF-κB. TRAF3 ablation also led to exacerbated secretion of the immunosuppressive cytokine IL-10. Coculturing of TRAF3-deficient DLBCL cells with CD8+ T cells impaired the induction of Granzyme B and interferon (IFN) γ, which were restored following neutralization of IL-10. Our findings corroborate a direct relationship between TRAF3 genetic alterations and NC NF-κB activation, and highlight NIK as a potential therapeutic target in a defined subset of DLBCL.
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Linfoma Difuso de Grandes Células B , NF-kappa B , Transdução de Sinais , Fator 3 Associado a Receptor de TNF , Fator 3 Associado a Receptor de TNF/metabolismo , Fator 3 Associado a Receptor de TNF/genética , Linfoma Difuso de Grandes Células B/genética , Linfoma Difuso de Grandes Células B/metabolismo , Humanos , NF-kappa B/metabolismo , Quinase Induzida por NF-kappaB , Linhagem Celular Tumoral , Linfócitos T CD8-Positivos/imunologia , Linfócitos T CD8-Positivos/metabolismo , Proteínas Serina-Treonina Quinases/metabolismo , Proteínas Serina-Treonina Quinases/genética , Proliferação de CélulasRESUMO
Fluorescence in situ hybridization (FISH) using break-apart probes is recommended for identifying high-grade B-cell lymphoma with MYC and BCL2 rearrangements (HGBCL-DH-BCL2). Unbalanced MYC break-apart patterns, where the red or green signal is lost, are commonly reported as an equivocal result by clinical laboratories. In a cohort of 297 HGBCL-DH-BCL2, 13% of tumors had unbalanced MYC break-apart patterns with loss of red (LR: 2%) or green (LG: 11%) signal. To determine the significance of these patterns, MYC rearrangements were characterized by sequencing in 130 HGBCL-DH-BCL2, including 3 LR and 14 LG tumors. A MYC rearrangement was identified for 71% of tumors with LR or LG patterns, with the majority involving immunoglobulin loci or other recurrent MYC rearrangement partners. The architecture of these rearrangements consistently preserved the rearranged MYC allele, with the MYC gene predicted to be on the derivative chromosome containing the signal that is still present in nearly all cases. MYC protein expression, MYC mRNA expression, and the proportion of tumors expressing the dark zone signature was not significantly different between balanced and unbalanced groups. These results support a recommendation that unbalanced MYC break-apart FISH patterns be reported as positive for MYC rearrangement in the context of diagnosing HGBCL-DH-BCL2.
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While initial therapy of mantle cell lymphoma (MCL) is not standardized, bendamustine-rituximab (BR) is commonly used in older patients. Rituximab (R) maintenance following induction is often utilized. Thus, the open-label, randomized phase II ECOG-ACRIN Cancer Research Group E1411 trial was designed to test two questions: 1) Does addition of bortezomib to BR induction (BVR) and/or 2) addition of lenalidomide to rituximab (LR) maintenance improve progression-free survival (PFS) in patients with treatment-naïve MCL? From 2012-2016, 373 previously untreated patients, 87% ≥ 60 years old, were enrolled in this trial. At a median follow up of 7.5 years, there is no difference in the median PFS of BR compared to BVR (5.5 yrs vs. 6.4 yrs, HR 0.90, 90% CI 0.70, 1.16). There were no unexpected additional toxicities with BVR treatment compared to BR, with no impact on total dose/duration of treatment received. Independent of the induction treatment, addition of lenalidomide to rituximab did not significantly improve PFS, with median PFS in R vs LR (5.9 yrs vs 7.2 yrs, HR 0.84 90% CI 0.62, 1.15). The majority of patients completed the planned 24 cycles of LR at the scheduled dose. In summary, adding bortezomib to BR induction does not prolong PFS in treatment-naïve MCL, and LR maintenance was not associated with longer PFS compared with rituximab alone following BR. Nonetheless, the > 5 year median PFS outcomes in this prospective cooperative group trial indicate the efficacy of BR followed by rituximab maintenance as highly effective initial therapy for older MCL patients. (NCT01415752).
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ABSTRACT: 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, although 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 1 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.
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Rearranjo Gênico , Proteínas Proto-Oncogênicas c-bcl-2 , Proteínas Proto-Oncogênicas c-myc , Humanos , Proteínas Proto-Oncogênicas c-bcl-2/genética , Proteínas Proto-Oncogênicas c-myc/genética , Linfoma de Células B/genética , Linfoma de Células B/patologia , Linfoma Difuso de Grandes Células B/genética , Linfoma Difuso de Grandes Células B/patologiaRESUMO
MOTIVATION: Single 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 a unified approach to evaluating segmentation accuracy. RESULTS: In this article, 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 IMPLEMENTATION: Source code is available on Github at: https://github.com/Roth-Lab/ESQmodel.
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Software , Células Secretoras de Somatostatina , Teorema de Bayes , Entropia , Processamento de Imagem Assistida por ComputadorRESUMO
BACKGROUND: Somatic hypermutation (SHM) status of the immunoglobulin heavy variable (IGHV) gene plays a crucial role in determining the prognosis and treatment of patients with chronic lymphocytic leukemia (CLL). A common approach for determining SHM status is multiplex polymerase chain reaction and Sanger sequencing of the immunoglobin heavy locus; however, this technique is low throughput, is vulnerable to failure, and does not allow multiplexing with other diagnostic assays. METHODS: Here we designed and validated a DNA targeted capture approach to detect immunoglobulin heavy variable somatic hypermutation (IGHV SHM) status as a submodule of a larger next-generation sequencing (NGS) panel that also includes probes for ATM, BIRC3, CHD2, KLHL6, MYD88, NOTCH1, NOTCH2, POT1, SF3B1, TP53, and XPO1. The assay takes as input FASTQ files and outputs a report containing IGHV SHM status and V allele usage following European Research Initiative on CLL guidelines. RESULTS: We validated the approach on 35 CLL patient samples, 34 of which were characterized using Sanger sequencing. The NGS panel identified the IGHV SHM status of 34 of 35 CLL patients. We showed 100% sensitivity and specificity among the 33 CLL samples with both NGS and Sanger sequencing calls. Furthermore, we demonstrated that this panel can be combined with additional targeted capture panels to detect prognostically important CLL single nucleotide variants, insertions/deletions, and copy number variants (TP53 copy number loss). CONCLUSIONS: A targeted capture approach to IGHV SHM detection can be integrated into broader sequencing panels, allowing broad CLL prognostication in a single molecular assay.
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Leucemia Linfocítica Crônica de Células B , Hipermutação Somática de Imunoglobulina , Humanos , Alelos , Sequenciamento de Nucleotídeos em Larga Escala , Imunoglobulinas , Leucemia Linfocítica Crônica de Células B/diagnóstico , Leucemia Linfocítica Crônica de Células B/genética , Fatores de TranscriçãoRESUMO
Successful employment of 3D printing for delivery of therapeutic biomolecules requires protection of their bioactivity on exposure to potentially inactivating conditions. Although intermediary encapsulation of the biomolecules in polymeric particulate delivery vehicles is a promising strategy for this objective, the inclusion of such particles in 3D printing formulations may critically impact the accuracy or precision of 3D printed scaffolds relative to their intended designed architectures, as well as the degradation behavior of both the scaffolds and the included particles. The present work aimed to elucidate the effect of poly(d,l-lactic-co-glycolic acid) particle size and loading concentration on material accuracy, machine precision, and degradation of 3D printed poly(É-caprolactone)-based scaffolds. Using a main effects analysis, the sizes and loading concentrations of particle delivery vehicles investigated were found to have neither a beneficial nor disadvantageous influence on the metrics of printing quality such as material accuracy and machine precision. Meanwhile, particle loading concentration was determined to influence degradation rate, whereas printing temperature affected the trends in composite weight-average molecular weight. Neither of the two particle-related parameters (concentration nor diameter) was found to exhibit a significant effect on intra-fiber nor inter-fiber porosity. These findings evidence the capacity for controlled loading of particulate delivery vehicles in 3D printed scaffolds while preserving construct accuracy and precision, and with predictable dictation of composite degradation behavior for potential controlled release of encapsulated biomolecules.
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OBJECTIVES: Accurate outcome prediction is important for making informed clinical decisions in cancer treatment. In this study, we assessed the feasibility of using changes in radiomic features over time (Delta radiomics: absolute and relative) following chemotherapy, to predict relapse/progression and time to progression (TTP) of primary mediastinal large B-cell lymphoma (PMBCL) patients. MATERIAL AND METHODS: Given the lack of standard staging PET scans until 2011, only 31 out of 103 PMBCL patients in our retrospective study had both pre-treatment and end-of-treatment (EoT) scans. Consequently, our radiomics analysis focused on these 31 patients who underwent [18F]FDG PET-CT scans before and after R-CHOP chemotherapy. Expert manual lesion segmentation was conducted on their scans for delta radiomics analysis, along with an additional 19 EoT scans, totaling 50 segmented scans for single time point analysis. Radiomics features (on PET and CT), along with maximum and mean standardized uptake values (SUVmax and SUVmean), total metabolic tumor volume (TMTV), tumor dissemination (Dmax), total lesion glycolysis (TLG), and the area under the curve of cumulative standardized uptake value-volume histogram (AUC-CSH) were calculated. We additionally applied longitudinal analysis using radial mean intensity (RIM) changes. For prediction of relapse/progression, we utilized the individual coefficient approximation for risk estimation (ICARE) and machine learning (ML) techniques (K-Nearest Neighbor (KNN), Linear Discriminant Analysis (LDA), and Random Forest (RF)) including sequential feature selection (SFS) following correlation analysis for feature selection. For TTP, ICARE and CoxNet approaches were utilized. In all models, we used nested cross-validation (CV) (with 10 outer folds and 5 repetitions, along with 5 inner folds and 20 repetitions) after balancing the dataset using Synthetic Minority Oversampling TEchnique (SMOTE). RESULTS: To predict relapse/progression using Delta radiomics between the baseline (staging) and EoT scans, the best performances in terms of accuracy and F1 score (F1 score is the harmonic mean of precision and recall, where precision is the ratio of true positives to the sum of true positives and false positives, and recall is the ratio of true positives to the sum of true positives and false negatives) were achieved with ICARE (accuracy = 0.81 ± 0.15, F1 = 0.77 ± 0.18), RF (accuracy = 0.89 ± 0.04, F1 = 0.87 ± 0.04), and LDA (accuracy = 0.89 ± 0.03, F1 = 0.89 ± 0.03), that are higher compared to the predictive power achieved by using only EoT radiomics features. For the second category of our analysis, TTP prediction, the best performer was CoxNet (LASSO feature selection) with c-index = 0.67 ± 0.06 when using baseline + Delta features (inclusion of both baseline and Delta features). The TTP results via Delta radiomics were comparable to the use of radiomics features extracted from EoT scans for TTP analysis (c-index = 0.68 ± 0.09) using CoxNet (with SFS). The performance of Deauville Score (DS) for TTP was c-index = 0.66 ± 0.09 for n = 50 and 0.67 ± 03 for n = 31 cases when using EoT scans with no significant differences compared to the radiomics signature from either EoT scans or baseline + Delta features (p-value> 0.05). CONCLUSION: This work demonstrates the potential of Delta radiomics and the importance of using EoT scans to predict progression and TTP from PMBCL [18F]FDG PET-CT scans.
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AIMS: Genomic sequencing of lymphomas is under-represented in routine clinical testing despite having prognostic and predictive value. Clinical implementation is challenging due to a lack of consensus on reportable targets and a paucity of reference samples. We organised a cross-validation study of a lymphoma-tailored next-generation sequencing panel between two College of American Pathologists (CAP)-accredited clinical laboratories to mitigate these challenges. METHODS: A consensus for the genomic targets was discussed between the two institutes based on recurrence in diffuse large B-cell lymphoma, follicular lymphoma, mantle cell lymphoma, chronic lymphocytic leukaemia and T-cell lymphomas. Using the same genomic targets, each laboratory ordered libraries independently and a cross-validation study was designed to exchange samples (8 cell lines and 22 clinical samples) and their FASTQ files. RESULTS: The sensitivity of the panel when comparing different library preparation and bioinformatic workflows was between 97% and 99% and specificity was 100% when a 5% limit of detection cut-off was applied. To evaluate how the current standards for variant classification of tumours apply to lymphomas, the Association for Molecular Pathology/American Society of Clinical Oncology/CAP and OncoKB classification systems were applied to the panel. The majority of variants were assigned a possibly actionable class or likely pathogenic due to more limited evidence in the literature. CONCLUSIONS: The cross-validation study highlights the benefits of sample and data exchange for clinical validation and provided a framework for reporting the findings in lymphoid malignancies.
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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.
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Linfoma Folicular , Análise de Célula Única , Microambiente Tumoral , Humanos , Linfoma Folicular/genética , Linfoma Folicular/patologia , Linfoma Folicular/imunologia , Microambiente Tumoral/genética , Microambiente Tumoral/imunologia , Análise de Célula Única/métodos , Transformação Celular Neoplásica/genética , Linfócitos B/imunologia , Linfócitos B/patologia , Linfócitos B/metabolismo , Regulação Neoplásica da Expressão Gênica , Transcriptoma , Biomarcadores Tumorais/genética , Sequenciamento Completo do Genoma , Perfilação da Expressão Gênica/métodosRESUMO
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.
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Linfoma , Células B de Memória , Animais , Humanos , Camundongos , Proteínas de Ligação a DNA/genética , Linfoma/genética , Mutação , Proteínas Nucleares/genética , Fatores de Transcrição/genética , Fatores de Transcrição/metabolismoRESUMO
Despite regulating overlapping gene enhancers and pathways, CREBBP and KMT2D mutations recurrently co-occur in germinal center (GC) B cell-derived lymphomas, suggesting potential oncogenic cooperation. Herein, we report that combined haploinsufficiency of Crebbp and Kmt2d induces a more severe mouse lymphoma phenotype (vs either allele alone) and unexpectedly confers an immune evasive microenvironment manifesting as CD8+ T-cell exhaustion and reduced infiltration. This is linked to profound repression of immune synapse genes that mediate crosstalk with T-cells, resulting in aberrant GC B cell fate decisions. From the epigenetic perspective, we observe interaction and mutually dependent binding and function of CREBBP and KMT2D on chromatin. Their combined deficiency preferentially impairs activation of immune synapse-responsive super-enhancers, pointing to a particular dependency for both co-activators at these specialized regulatory elements. Together, our data provide an example where chromatin modifier mutations cooperatively shape and induce an immune-evasive microenvironment to facilitate lymphomagenesis.
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Linfoma Difuso de Grandes Células B , Animais , Camundongos , Linfócitos B/metabolismo , Cromatina/genética , Cromatina/metabolismo , Centro Germinativo/metabolismo , Linfoma Difuso de Grandes Células B/genética , Mutação , Microambiente Tumoral/genéticaRESUMO
Progression or relapse in the central nervous system (CNS) remains a rare but mostly fatal event for patients with diffuse large B-cell lymphoma (DLBCL). In a retrospective analysis of 5189 patients treated within 19 prospective German and French phase 2/3 trials, we identified 159 patients experiencing a CNS event (relapse: 62%, progression: 38%). Intracerebral, meningeal, intraspinal, or combined involvement was reported in 44%, 31%, 3%, and 22% of patients, respectively. 62 of 155 evaluable patients (40%) showed concurrent systemic progression/ relapse. 82% of all CNS events occurred within two years after study inclusion or randomization. 87% of patients showed extranodal involvement outside the CNS. Patients generally had poor outcomes with a median overall survival (OS) of 3.4 months (95% CI 2.9-4.2) and a 2-year OS of 15% (10-22%). Outcomes did not differ depending on the site or time point of CNS events. Patients with isolated CNS events demonstrated significantly better OS (p = 0.023). Twenty-five patients were consolidated with autologous or allogeneic stem cell transplantation and achieved a 3-year OS of 36% (20-66%). This large study including more than 5000 DLBCL patients highlights the unmet medical need to improve the outcome of DLBCL patients suffering from CNS relapse.
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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.
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Doença de Hodgkin , Humanos , Doença de Hodgkin/tratamento farmacológico , Microambiente Tumoral , Ecossistema , Recidiva Local de Neoplasia , Resultado do Tratamento , RecidivaRESUMO
Diffuse large B-cell lymphoma (DLBCL) is heterogeneous both in clinical outcomes and the underlying disease biology. Over the last 2 decades, several different approaches for dissecting biological heterogeneity have emerged. Gene expression profiling (GEP) stratifies DLBCL into 3 broad groups (ABC, GCB, and DZsig/MHG), each with parallels to different normal mature B cell developmental states and prognostic implications. More recently, several different genomic approaches have been developed to categorize DLBCL based on the co-occurrence of tumor somatic mutations, identifying more granular biologically unified subgroups that complement GEP-based approaches. We review the molecular approaches and clinical evidence supporting the stratification of DLBCL patients based on tumor biology. By offering a platform for subtype-guided therapy, these divisions remain a promising avenue for improving patient outcomes, especially in subgroups with inferior outcomes with current standard-of-care therapy.