Clinical and Biological Subtypes of B-cell Lymphoma Revealed by Microenvironmental Signatures

Dynamic change of soluble interleukin-2 receptor distinguished molecular heterogeneity and microenvironment alterations in diffuse large B-cell lymphoma

Diffuse large B-cell lymphoma (DLBCL) is an aggressive lymphoma with variable clinical outcomes and prediction of prognosis remains important for long-term remission. We performed serial serum soluble interleukin-2 receptor (sIL-2R) measurement pretreatment and before each cycle of the treatment in 599 patients with de novo DLBCL. Genomic and transcriptomic features were analyzed by 223 DNA- and 227 RNA-sequencing, respectively. Applying the cut-off value to sIL-2R pretreatment and cycle 2 (C2) level, patients were classified into FINE subtype (pretreatment low level) with good prognosis, RES subtype (pretreatment high level and C2 low level) with intermediate prognosis, and RET subtype (pretreatment high level and C2 high level) with poor prognosis, independent of International Prognostic Index. In “others” genetic subtype, dynamic change of sIL-2R showed prognostic significance and genetic features. Compared with FINE subtype, RES subtype had increased ARID1A and MYD88 mutations, and RET subtype had increased KMT2D, LYN and SOCS1 mutations. RES and RET subtypes showed significant enrichment in oncogenic pathways, such as ERK, NF-κB, JAK-STAT, and immune-associated pathways. As for tumor microenvironment, RES subtype exhibited increased recruiting activity of CD8 + T, T helper 1, and natural killer cells, and RET subtype with increased recruiting activity of CD4 + T and regulatory T cells in silico. There was a positive correlation between transcripts of IL-2R and immune checkpoint expressions including PD-1 and CTLA-4. Our findings identified that dynamic change of sIL-2R, with this simple and easy detection method in peripheral blood, had long-term prognostic effect and specific relation to microenvironment alterations in DLBCL.

Classifying Germinal Center Derived Lymphomas-Navigate a Complex Transcriptional Landscape

Classification of lymphoid neoplasms is based mainly on histologic, immunologic, and (rarer) genetic features. It has been supplemented by gene expression profiling (GEP) in the last decade. Despite the considerable success, particularly in associating lymphoma subtypes with specific transcriptional programs and classifier signatures of up- or downregulated genes, competing molecular classifiers were often proposed in the literature by different groups for the same classification tasks to distinguish, e.g., BL versus DLBCL or different DLBCL subtypes. Moreover, rarer sub-entities such as MYC and BCL2 "double hit lymphomas" (DHL), IRF4-rearranged large cell lymphoma (IRF4-LCL), and Burkitt-like lymphomas with 11q aberration pattern (mnBLL-11q) attracted interest while their relatedness regarding the major classes is still unclear in many respects. We explored the transcriptional landscape of 873 lymphomas referring to a wide spectrum of subtypes by applying self-organizing maps (SOM) machine learning. The landscape reveals a continuum of transcriptional states activated in the different subtypes without clear-cut borderlines between them and preventing their unambiguous classification. These states show striking parallels with single cell gene expression of the active germinal center (GC), which is characterized by the cyclic progression of B-cells. The expression patterns along the GC trajectory are discriminative for distinguishing different lymphoma subtypes. We show that the rare subtypes take intermediate positions between BL, DLBCL, and FL as considered by the 5th edition of the WHO classification of haemato-lymphoid tumors in 2022. Classifier gene signatures extracted from these states as modules of coregulated genes are competitive with literature classifiers. They provide functional-defined classifiers with the option of consenting redundant classifiers from the literature. We discuss alternative classification schemes of different granularity and functional impact as possible avenues toward personalization and improved diagnostics of GC-derived lymphomas.

Tyramide-conjugated DNA barcodes enable signal amplification for multiparametric CODEX imaging

Multiparametric imaging allows researchers to measure the expression of many biomarkers simultaneously, allowing detailed characterization of cell microenvironments. One such technique, CODEX, allows fluorescence imaging of >30 proteins in a single tissue section. In the commercial CODEX system, primary antibodies are conjugated to DNA barcodes. This modification can result in antibody dysfunction, and development of a custom antibody panel can be very costly and time consuming as trial and error of modified antibodies proceeds. To address these challenges, we developed novel tyramide-conjugated DNA barcodes that can be used with primary antibodies via peroxidase-conjugated secondary antibodies. This approach results in signal amplification and imaging without the need to conjugate primary antibodies. When combined with commercially available barcode-conjugated primary antibodies, we can very quickly develop working antibody panels. We also present methods to perform antibody staining using a commercially available automated tissue stainer and in situ hybridization imaging on a CODEX platform. Future work will include application of the combined tyramide-based and regular CODEX approach to image specific tumors with their immune cell infiltrates, including biomarkers that are currently difficult to image by regular CODEX.

CAR T-cell Therapy in Highly-Aggressive B-Cell Lymphoma: Emerging Biological and Clinical Insights

Recently, significant progress has been made in identifying novel therapies, beyond conventional immunochemotherapy strategies, with efficacy in B-cell lymphomas. One such approach involves targeting the CD19 antigen on B-cells with autologous-derived chimeric antigen receptor (CAR) cells. This strategy is highly effective in patients with relapsed and refractory diffuse large B-cell lymphoma (DLBCL) as evidenced by recent regulatory approvals. Recent reports suggest that this is an effective strategy for high-grade B-cell. The biological underpinnings of these entities and how they overlap with each other and DLBCL continue to be areas of intense investigation. Therefore, as more experience with CAR T-cell approaches is examined, it is interesting to consider how both tumor-cell specific and microenvironment factors that define these highly aggressive subsets influence susceptibility to this approach.

Spatial transcriptome of a germinal center plasmablastic burst hints at MYD88/CD79B mutants-enriched diffuse large B-cell lymphomas

The GC reaction results in the selection of B cells acquiring effector Ig secreting ability by progressing toward plasmablastic differentiation. This transition is associated with exclusion from the GC microenvironment. The aberrant expansion of plasmablastic elements within the GC fringes configures an atypical condition, the biological characteristics of which have not been defined yet. We investigated the in situ immunophenotypical and transcriptional characteristics of a nonclonal germinotropic expansion of plasmablastic elements (GEx) occurring in the tonsil of a young patient. Compared to neighboring GC and perifollicular regions, the GEx showed a distinctive signature featuring key regulators of plasmacytic differentiation, cytokine signaling, and cell metabolism. The GEx signature was tested in the setting of diffuse large B‐cell lymphoma (DLBCL) as a prototypical model of lymphomagenesis encompassing transformation at different stages of GC and post‐GC functional differentiation. The signature outlined DLBCL clusters with different immune microenvironment composition and enrichment in genetic subtypes. This report represents the first insight into the transcriptional features of a germinotropic plasmablastic burst, shedding light into the molecular hallmarks of B cells undergoing plasmablastic differentiation and aberrant expansion within the noncanonical setting of the GC microenvironment.

Single-Cell RNA-Seq and Bulk RNA-Seq Reveal Intratumoral Heterogeneity and Tumor Microenvironment Characteristics in Diffuse Large B-Cell Lymphoma

Background: Diffuse large B-cell lymphoma (DLBCL) is the most common histologic subtype of non-Hodgkin’s lymphoma (NHL) with highly heterogeneous genetic and phenotypic features. Therefore, a comprehensive understanding of cellular diversity and intratumoral heterogeneity is essential to elucidate the mechanisms driving DLBCL progression and to develop new therapeutic approaches.

Methods: We analyzed single-cell transcriptomic data from 2 reactive lymph node tissue samples and 2 DLBCL lymph node biopsy tissue samples to explore the transcriptomic landscape of DLBCL. In addition, we constructed a prognostic model based on the genes obtained from differential analysis.

Results: Based on gene expression profiles at the single cell level, we identified and characterized different subpopulations of malignant and immune cells. Malignant cells exhibited a high degree of inter-tumor heterogeneity. Tumor-infiltrating regulatory CD4⁺ T cells showed highly immunosuppressive properties and exhausted cytotoxic CD8⁺ T cells were highly expressed with markers of exhaustion. Cell communication analysis identified complex interactions between malignant cells and other cell subpopulations. In addition, the prognostic model we constructed allows for monitoring the prognosis of DLBCL patients.

Conclusion: This study provides an in-depth dissection of the transcriptional features of malignant B cells and tumor microenvironment (TME) in DLBCL and provides new insights into the tumor heterogeneity of DLBCL.

Molecular Diagnostic Review of Diffuse Large B-Cell Lymphoma and Its Tumor Microenvironment

Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma. It is a clinically and morphologically heterogeneous entity that has continued to resist complete subtyping. Molecular subtyping efforts emerged in earnest with the advent of gene expression profiling (GEP). This molecular subtyping approach has continued to evolve simultaneously with others including immunohistochemistry and more modern genomic approaches. Recently, the veritable explosion of genomic data availability and evolving computational methodologies have provided additional avenues, by which further understanding and subclassification of DBLCLs is possible. The goal of this review is to provide a historical overview of the major classification timepoints in the molecular subtyping of DLBCL, from gene expression profiling to present day understanding.

Biological and Clinical Implications of Gene-Expression Profiling in Diffuse Large B-Cell Lymphoma: A Proposal for a Targeted BLYM-777 Consortium Panel as Part of a Multilayered Analytical Approach

Gene-expression profiling (GEP) is used to study the molecular biology of lymphomas. Here, advancing insights from GEP studies in diffuse large B-cell lymphoma (DLBCL) lymphomagenesis are discussed. GEP studies elucidated subtypes based on cell-of-origin principles and profoundly changed the biological understanding of DLBCL with clinical relevance. Studies integrating GEP and next-generation DNA sequencing defined different molecular subtypes of DLBCL entities originating at specific anatomical localizations. With the emergence of high-throughput technologies, the tumor microenvironment (TME) has been recognized as a critical component in DLBCL pathogenesis. TME studies have characterized so-called "lymphoma microenvironments" and "ecotypes". Despite gained insights, unexplained chemo-refractoriness in DLBCL remains. To further elucidate the complex biology of DLBCL, we propose a novel targeted GEP consortium panel, called BLYM-777. This knowledge-based biology-driven panel includes probes for 777 genes, covering many aspects regarding B-cell lymphomagenesis (f.e., MYC signature, TME, immune surveillance and resistance to CAR T-cell therapy). Regarding lymphomagenesis, upcoming DLBCL studies need to incorporate genomic and transcriptomic approaches with proteomic methods and correlate these multi-omics data with patient characteristics of well-defined and homogeneous cohorts. This multilayered methodology potentially enhances diagnostic classification of DLBCL subtypes, prognostication, and the development of novel targeted therapeutic strategies.

Transforming Growth Factor-Beta Orchestrates Tumour and Bystander Cells in B-Cell Non-Hodgkin Lymphoma

Transforming growth factor-beta (TGFB) is a critical regulator of normal haematopoiesis. Dysregulation of the TGFB pathway is associated with numerous haematological malignancies including myelofibrosis, acute myeloid leukaemia, and lymphoid disorders. TGFB has classically been seen as a negative regulator of proliferation in haematopoiesis whilst stimulating differentiation and apoptosis, as required to maintain homeostasis. Tumours frequently develop intrinsic resistant mechanisms to homeostatic TGFB signalling to antagonise its tumour-suppressive functions. Furthermore, elevated levels of TGFB enhance pathogenesis through modulation of the immune system and tumour microenvironment. Here, we review recent advances in the understanding of TGFB signalling in B-cell malignancies with a focus on the tumour microenvironment. Malignant B-cells harbour subtype-specific alterations in TGFB signalling elements including downregulation of surface receptors, modulation of SMAD signalling proteins, as well as genetic and epigenetic aberrations. Microenvironmental TGFB generates a protumoural niche reprogramming stromal, natural killer (NK), and T-cells. Increasingly, evidence points to complex bi-directional cross-talk between cells of the microenvironment and malignant B-cells. A greater understanding of intercellular communication and the context-specific nature of TGFB signalling may provide further insight into disease pathogenesis and future therapeutic strategies.

Phase 1 study of oral azacitidine (CC-486) plus R-CHOP in previously untreated intermediate- to high-risk DLBCL

Resistance to standard immunochemotherapy remains an unmet challenge in diffuse large B-cell lymphoma (DLBCL), and aberrant DNA methylation may contribute to chemoresistance. Promising early-phase results were reported with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) plus subcutaneous azacitidine, a hypomethylating agent. In this phase 1 study, we evaluated CC-486 (oral azacitidine) plus 6 cycles of R-CHOP in patients with previously untreated intermediate- to high-risk DLBCL or grade 3B/transformed follicular lymphoma. CC-486 doses of 100, 150, 200, or 300 mg given 7 days before cycle 1 and on days 8-21 of cycles 1-5 were evaluated; additional patients were enrolled in the expansion phase to examine preliminary efficacy. The primary objectives were to determine the safety and the maximum tolerated dose (MTD) of CC-486 in combination with R-CHOP. The most common grade 3/4 toxicities were hematologic, including neutropenia (62.7%) and febrile neutropenia (25.4%); grade 3/4 nonhematologic toxicities were uncommon (<7%). The MTD was not established; 2 patients had dose-limiting toxicities (1 with grade 4 febrile neutropenia; 1 with grade 4 prolonged neutropenia). The recommended phase 2 dose was established as 300 mg. The overall response rate was 94.9%, with 52 patients (88.1%) achieving complete responses. With a median follow-up of 28.9 months, estimated 1- and 2-year progression-free survival rates were 84.1% and 78.6%, respectively. Overall, epigenetic priming with CC-486 before R-CHOP can be delivered with acceptable safety to patients with previously untreated intermediate- to high-risk DLBCL or grade 3B/transformed follicular lymphoma. ClinicalTrials.gov: NCT02343536.

Clinical Impact of Immune Cells and Their Spatial Interactions in Diffuse Large B-Cell Lymphoma Microenvironment

PURPOSE

Tumor-infiltrating immune cells have prognostic significance and are attractive therapeutic targets. Yet, the clinical significance of their spatial organization and phenotype in diffuse large B-cell lymphoma (DLBCL) is unclear.

EXPERIMENTAL DESIGN

We characterized T cells, macrophages, and their spatial interactions by multiplex IHC (mIHC) in 178 patients with DLBCL and correlated the data with patient demographics and survival. We validated the findings on gene expression data from two external DLBCL cohorts comprising 633 patients.

RESULTS

Macrophage and T-cell contents divided the samples into T cell-inflamed (60%) and noninflamed (40%) subgroups. The T cell-inflamed lymphoma microenvironment (LME) was also rich in other immune cells, defining immune hot phenotype, which did not as such correlate with outcome. However, when we divided the patients according to T-cell and macrophage contents, LME characterized by high T-cell/low macrophage content or a corresponding gene signature was associated with superior survival [5-year overall survival (OS): 92.3% vs. 74.4%, P = 0.036; 5-year progression-free survival (PFS): 92.6% vs. 69.8%, P = 0.012]. High proportion of PD-L1- and TIM3-expressing CD163- macrophages in the T cell-inflamed LME defined a group of patients with poor outcome [OS: HR = 3.22, 95% confidence interval (CI), 1.63-6.37, Padj = 0.011; PFS: HR = 2.76, 95% CI, 1.44-5.28, Padj = 0.016]. Furthermore, PD-L1 and PD-1 were enriched on macrophages interacting with T cells.

CONCLUSIONS

Our data demonstrate that the interplay between macrophages and T cells in the DLBCL LME is immune checkpoint dependent and clinically meaningful.

Immune Epigenetic Crosstalk Between Malignant B Cells and the Tumor Microenvironment in B Cell Lymphoma

Epigenetic reprogramming is a hallmark of lymphomagenesis, however its role in reshaping the tumor microenvironment is still not well understood. Here we review the most common chromatin modifier mutations in B cell lymphoma and their effect on B cells as well as on T cell landscape. We will also discuss precision therapy strategies to reverse their aberrant signaling by targeting mutated proteins or counterbalance epigenetic mechanisms.

All roads lead to targeted diffuse large B-cell lymphoma approaches

Two recent reports in the New England Journal of Medicine highlight the successful application of novel targeted therapies to improve the clinical outcomes of diffuse large B-cell lymphoma (DLBCL). These findings encourage us to pursue further mechanism-based therapeutic uses to make DLBCL curable in the era of precision medicine.

Pharmacodynamics and molecular correlates of response to glofitamab in relapsed/refractory non-Hodgkin lymphoma

Glofitamab, a novel CD20xCD3, T-cell-engaging bispecific antibody, exhibited single-agent activity in Study NP30179, a first-in-human, phase 1 trial in relapsed/refractory B-cell non-Hodgkin lymphoma. Preclinical studies showed that glofitamab leads to T-cell activation, proliferation, and tumor cell killing upon binding to CD20 on malignant cells. Here, we provide evidence of glofitamab's clinical activity, including pharmacodynamic profile, mode of action, and factors associated with clinical response, by evaluating biomarkers in patient samples from the dose-escalation part of this trial. Patients enrolled in Study NP30179 received single-dose obinutuzumab pretreatment (1000 mg) 7 days before IV glofitamab (5 µg-25 mg). Glofitamab treatment lasted ≤12 cycles once every 2 or 3 weeks. Blood samples were collected at predefined time points per the clinical protocol; T-cell populations were evaluated centrally by flow cytometry, and cytokine profiles were analyzed. Immunohistochemical and genomic biomarker analyses were performed on tumor biopsy samples. Pharmacodynamic modulation was observed with glofitamab treatment, including dose-dependent induction of cytokines, and T-cell margination, proliferation, and activation in peripheral blood. Gene expression analysis of pretreatment tumor biopsy samples indicated that tumor cell intrinsic factors such as TP53 signaling are associated with resistance to glofitamab, but they may also be interlinked with a diminished effector T-cell profile in resistant tumors and thus represent a poor prognostic factor per se. This integrative biomarker data analysis provides clinical evidence regarding glofitamab's mode of action, supports optimal biological dose selection, and will further guide clinical development. This trial was registered at www.clinicaltrials.gov as #NCT03075696.

Genetic and phenotypic attributes of splenic marginal zone lymphoma

Splenic marginal zone B-cell lymphoma (SMZL) is a heterogeneous clinico-biological entity. The clinical course is variable, multiple genes are mutated with no unifying mechanism, and essential regulatory pathways and surrounding microenvironments are diverse. We sought to clarify the heterogeneity of SMZL by resolving different subgroups and their underlying genomic abnormalities, pathway signatures, and microenvironment compositions to uncover biomarkers and therapeutic vulnerabilities. We studied 303 SMZL spleen samples collected through the IELSG46 multicenter international study (NCT02945319) by using a multiplatform approach. We carried out genetic and phenotypic analyses, defined self-organized signatures, validated the findings in independent primary tumor metadata and in genetically modified mouse models, and determined correlations with outcome data. We identified 2 prominent genetic clusters in SMZL, termed NNK (58% of cases, harboring NF-κB, NOTCH, and KLF2 modules) and DMT (32% of cases, with DNA-damage response, MAPK, and TLR modules). Genetic aberrations in multiple genes as well as cytogenetic and immunogenetic features distinguished NNK- from DMT-SMZLs. These genetic clusters not only have distinct underpinning biology, as judged by differences in gene-expression signatures, but also different outcomes, with inferior survival in NNK-SMZLs. Digital cytometry and in situ profiling segregated 2 basic types of SMZL immune microenvironments termed immune-suppressive SMZL (50% of cases, associated with inflammatory cells and immune checkpoint activation) and immune-silent SMZL (50% of cases, associated with an immune-excluded phenotype) with distinct mutational and clinical connotations. In summary, we propose a nosology of SMZL that can implement its classification and also aid in the development of rationally targeted treatments.

Epigenetic, Metabolic, and Immune Crosstalk in Germinal-Center-Derived B-Cell Lymphomas: Unveiling New Vulnerabilities for Rational Combination Therapies

B-cell non-Hodgkin lymphomas (B-NHLs) are highly heterogenous by genetic, phenotypic, and clinical appearance. Next-generation sequencing technologies and multi-dimensional data analyses have further refined the way these diseases can be more precisely classified by specific genomic, epigenomic, and transcriptomic characteristics. The molecular and genetic heterogeneity of B-NHLs may contribute to the poor outcome of some of these diseases, suggesting that more personalized precision-medicine approaches are needed for improved therapeutic efficacy. The germinal center (GC) B-cell like diffuse large B-cell lymphomas (GCB-DLBCLs) and follicular lymphomas (FLs) share specific epigenetic programs. These diseases often remain difficult to treat and surprisingly do not respond advanced immunotherapies, despite arising in secondary lymphoid organs at sites of antigen recognition. Epigenetic dysregulation is a hallmark of GCB-DLBCLs and FLs, with gain-of-function (GOF) mutations in the histone methyltransferase EZH2, loss-of-function (LOF) mutations in histone acetyl transferases CREBBP and EP300, and the histone methyltransferase KMT2D representing the most prevalent genetic lesions driving these diseases. These mutations have the common effect to disrupt the interactions between lymphoma cells and the immune microenvironment, via decreased antigen presentation and responsiveness to IFN-γ and CD40 signaling pathways. This indicates that immune evasion is a key step in GC B-cell lymphomagenesis. EZH2 inhibitors are now approved for the treatment of FL and selective HDAC3 inhibitors counteracting the effects of CREBBP LOF mutations are under development. These treatments can help restore the immune control of GCB lymphomas, and may represent optimal candidate agents for more effective combination with immunotherapies. Here, we review recent progress in understanding the impact of mutant chromatin modifiers on immune evasion in GCB lymphomas. We provide new insights on how the epigenetic program of these diseases may be regulated at the level of metabolism, discussing the role of metabolic intermediates as cofactors of epigenetic enzymes. In addition, lymphoma metabolic adaptation can negatively influence the immune microenvironment, further contributing to the development of immune cold tumors, poorly infiltrated by effector immune cells. Based on these findings, we discuss relevant candidate epigenetic/metabolic/immune targets for rational combination therapies to investigate as more effective precision-medicine approaches for GCB lymphomas.

Genetic Subtyping and Phenotypic Characterization of the Immune Microenvironment and MYC/BCL2 Double Expression Reveal Heterogeneity in Diffuse Large B-cell Lymphoma

PURPOSE

Diffuse large B-cell lymphoma (DLBCL) is molecularly and clinically heterogeneous, and can be subtyped according to genetic alterations, cell-of-origin, or microenvironmental signatures using high-throughput genomic data at the DNA or RNA level. Although high-throughput proteomic profiling has not been available for DLBCL subtyping, MYC/BCL2 protein double expression (DE) is an established prognostic biomarker in DLBCL. The purpose of this study is to reveal the relative prognostic roles of DLBCL genetic, phenotypic, and microenvironmental biomarkers.

EXPERIMENTAL DESIGN

We performed targeted next-generation sequencing; IHC for MYC, BCL2, and FN1; and fluorescent multiplex IHC for microenvironmental markers in a large cohort of DLBCL. We performed correlative and prognostic analyses within and across DLBCL genetic subtypes and MYC/BCL2 double expressors.

RESULTS

We found that MYC/BCL2 double-high-expression (DhE) had significant adverse prognostic impact within the EZB genetic subtype and LymphGen-unclassified DLBCL cases but not within MCD and ST2 genetic subtypes. Conversely, KMT2D mutations significantly stratified DhE but not non-DhE DLBCL. T-cell infiltration showed favorable prognostic effects within BN2, MCD, and DhE but unfavorable effects within ST2 and LymphGen-unclassified cases. FN1 and PD-1-high expression had significant adverse prognostic effects within multiple DLBCL genetic/phenotypic subgroups. The prognostic effects of DhE and immune biomarkers within DLBCL genetic subtypes were independent although DhE and high Ki-67 were significantly associated with lower T-cell infiltration in LymphGen-unclassified cases.

CONCLUSIONS

Together, these results demonstrated independent and additive prognostic effects of phenotypic MYC/BCL2 and microenvironment biomarkers and genetic subtyping in DLBCL prognostication, important for improving DLBCL classification and identifying prognostic determinants and therapeutic targets.

Bone Marrow Lymphoid Niche Adaptation to Mature B Cell Neoplasms

B-cell non-Hodgkin lymphoma (B-NHL) evolution and treatment are complicated by a high prevalence of relapses primarily due to the ability of malignant B cells to interact with tumor-supportive lymph node (LN) and bone marrow (BM) microenvironments. In particular, progressive alterations of BM stromal cells sustain the survival, proliferation, and drug resistance of tumor B cells during diffuse large B-cell lymphoma (DLBCL), follicular lymphoma (FL), and chronic lymphocytic leukemia (CLL). The current review describes how the crosstalk between BM stromal cells and lymphoma tumor cells triggers the establishment of the tumor supportive niche. DLBCL, FL, and CLL display distinct patterns of BM involvement, but in each case tumor-infiltrating stromal cells, corresponding to cancer-associated fibroblasts, exhibit specific phenotypic and functional features promoting the recruitment, adhesion, and survival of tumor cells. Tumor cell-derived extracellular vesicles have been recently proposed as playing a central role in triggering initial induction of tumor-supportive niches, notably within the BM. Finally, the disruption of the BM stroma reprogramming emerges as a promising therapeutic option in B-cell lymphomas. Targeting the crosstalk between BM stromal cells and malignant B cells, either through the inhibition of stroma-derived B-cell growth factors or through the mobilization of clonal B cells outside their supportive BM niche, should in particular be further evaluated as a way to avoid relapses by abrogating resistance niches.

Targeting MALT1 for the treatment of diffuse large B-cell lymphoma

The activated B-cell (ABC) subtype of diffuse large B-cell lymphoma (DLBCL) has an aggressive course and is associated with poor prognosis in the relapsed or refractory setting. ABC-DLBCL is characterized by chronic active signaling of NF-κB, which is dependent on the CARD11-BCL10-MALT1 (CBM) complex. MALT1 is a key effector of the CBM complex and activates canonical NF-κB and AP-1 among other transcription factors via distinct protease and scaffold functions. There is therefore growing interest in therapeutic targeting of MALT1 for B-cell malignancies. Here, we review recent advances in therapeutic targeting of MALT1 for ABC-DLBCL. Covalent and allosteric MALT1 protease inhibitors have been developed which inhibit growth of ABC-DLBCL in preclinical models, and two clinical MALT1 protease inhibitors are being developed in phase I clinical trials. Importantly, these compounds can overcome resistance to BTK inhibitors in preclinical models. Alternative compounds blocking the scaffold effect of MALT1 are also in early preclinical development. Blockade of MALT1 protease activity may have important implications for anti-lymphoma immunity by increasing immunogenicity of ABC-DLBCL cells and also by potentiating anti-lymphoma activity of other immune cells in the lymphoma microenvironment. Together, early data suggest that MALT1 is a promising target for ABC-DLBCL and possibly other B-cell malignancies, and can have lymphoma cell-intrinsic as well as immune-mediated therapeutic effects.

International Prognostic Index-Based Immune Prognostic Model for Diffuse Large B-Cell Lymphoma

Background

The International Prognostic Index (IPI) is widely used to discriminate the prognosis of patients with diffuse large B-cell lymphoma (DLBCL). However, there is a significant need to identify novel valuable biomarkers in the context of targeted therapy, such as immune checkpoint blockade (ICB).

Methods

Gene expression data and clinical DLBCL information were obtained from The Cancer Genome Atlas and Gene Expression Omnibus datasets. A total of 371 immune-related genes in DLBCL patients associated with different IPI risk groups were identified by weighted gene co-expression network analysis, and eight genes were selected to construct an IPI-based immune prognostic model (IPI-IPM). Subsequently, we analyzed the somatic mutation and transcription profiles of the IPI-IPM subgroups as well as the potential clinical response to immune checkpoint blockade (ICB) in IPI-IPM subgroups.

Results

The IPI-IPM was constructed based on the expression of CMBL, TLCD3B, SYNDIG1, ESM1, EPHA3, HUNK, PTX3, and IL12A, where high-risk patients had worse overall survival than low-risk patients, consistent with the results in the independent validation cohorts. The comprehensive results showed that high IPI-IPM risk scores were correlated with immune-related signaling pathways, high KMT2D and CD79B mutation rates, and upregulation of inhibitory immune checkpoints, including PD-L1, BTLA, and SIGLEC7, indicating a greater potential response to ICB therapy.

Conclusion

The IPI-IPM has independent prognostic significance for DLBCL patients, which provides an immunological perspective to elucidate the mechanisms of tumor progression and sheds light on the development of immunotherapy for DLBCL.

Helicobacter pylori infection disturbs the tumor immune microenvironment and is associated with a discrepant prognosis in gastric de novo diffuse large B-cell lymphoma

BACKGROUND

Gastric diffuse large B-cell lymphoma (gDLBCL) related to Helicobacter pylori infection exhibits a wide spectrum of prognosis, and the tumor immune microenvironment (TIME) affects tumor progression. However, there are few studies on the correlation between prognosis and changes of TIME induced by H. pylori infection in de novo gDLBCL.

METHODS

A retrospective study was performed to determine the prognostic value of TIME related to H. pylori infection in de novo gDLBCL. A total of 252 patients were included and have been treated with standard rituximab to cyclophosphamide, doxorubicin, vincristine, and prednisone chemotherapy or other similar regimens in addition to H. pylori eradication (HPE). All patients were stratified by H. pylori infection, HPE efficacy, and preliminary TIME evaluation using conventional criteria. Statistical analyses were conducted. To assess the mechanism, 30 subjects were assessed for H. pylori infection. The components and spatial distributions of TIME were analyzed.

RESULTS

The median follow-up of the 252 patients was 66.6 months (range 0.7-119.2), and the 5-year overall survival (OS) was 78.0%. A total of 109 H. pylori-positive cases with pathological complete remission and high tumor-infiltrating T lymphocytes (cohort 1) had significantly higher 5-year progression-free survival (88.1% vs 70.5%, p<0.001) and OS (89.2% vs 76.6%, p<0.001) than the other 143 patients (cohort 2). Among 30 patients, 19 were cytotoxin-associated gene A-marked as the cohort 1 subset. Compared with cohort 2, cohort 1 exhibited increased inflammatory factors (tumor necrosis factor-α, interferon γ, etc) and decreased immunosuppressive components (PD-L1, PD-1, IL-10, etc). There was reduced NF-kB activation. Cancer-promoting immune cells (PD-1hiTim-3+ CTL, Tregs, M2-like macrophages, etc) occupied a minor spatial distribution, while the antitumor subtypes increased, corresponding to favorable survival.

CONCLUSION

H. pylori-evoked inflammatory responses disturb the TIME, causing a differential prognosis in de novo gDLBCL, which can be used to identify patients who could benefit from HPE and immunochemotherapy.

A Germinal Center-Associated Microenvironmental Signature Reflects Malignant Phenotype and Outcome of DLBCL

The DLBCL microenvironment signature scoring system was established using nCounter-based profiling of GC-related microenvironmental genes.

DMS scores stratified DLBCL patients with different prognosis independently of existing prognostic models.

Diffuse large B-cell lymphoma (DLBCL) is the most common B-cell malignancy, with varying prognosis after the gold standard rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP). Several prognostic models have been established by focusing primarily on characteristics of lymphoma cells themselves, including cell-of-origin (COO), genomic alterations, and gene/protein expressions. However, the prognostic impact of the lymphoma microenvironment and its association with characteristics of lymphoma cells are not fully understood. Using the nCounter-based gene expression profiling of untreated DLBCL tissues, we assess the clinical impact of lymphoma microenvironment on the clinical outcomes and pathophysiological, molecular signatures in DLBCL. The presence of normal germinal center (GC)-microenvironmental cells, including follicular T cells, macrophage/dendritic cells, and stromal cells in lymphoma tissue indicates a positive therapeutic response. Our prognostic model, based on quantitation of transcripts from distinct GC-microenvironmental cell markers, clearly identified patients with graded prognosis independently of existing prognostic models. We observed increased incidences of genomic alterations and aberrant gene expression associated with poor prognosis in DLBCL tissues lacking GC-microenvironmental cells relative to those containing these cells. These data suggest that the loss of GC-associated microenvironmental signature dictates clinical outcomes of DLBCL patients reflecting the accumulation of “unfavorable” molecular signatures.

Dissecting bulk transcriptomes of diffuse large B cell lymphoma

Diffuse large B cell lymphoma (DLBCL) is a markedly phenotypically heterogenous disease, frequently assessed using bulk genomic techniques that blur the intrinsic heterogeneity of each tumor. In this issue of Cancer Cell, Steen et al. have utilized a computational framework called EcoTyper to skillfully dissect bulk transcriptomic tumor profiles into different cell type components in an unsupervised manner.

The landscape of tumor cell states and ecosystems in diffuse large B cell lymphoma

Biological heterogeneity in diffuse large B cell lymphoma (DLBCL) is partly driven by cell-of-origin subtypes and associated genomic lesions, but also by diverse cell types and cell states in the tumor microenvironment (TME). However, dissecting these cell states and their clinical relevance at scale remains challenging. Here, we implemented EcoTyper, a machine-learning framework integrating transcriptome deconvolution and single-cell RNA sequencing, to characterize clinically relevant DLBCL cell states and ecosystems. Using this approach, we identified five cell states of malignant B cells that vary in prognostic associations and differentiation status. We also identified striking variation in cell states for 12 other lineages comprising the TME and forming cell state interactions in stereotyped ecosystems. While cell-of-origin subtypes have distinct TME composition, DLBCL ecosystems capture clinical heterogeneity within existing subtypes and extend beyond cell-of-origin and genotypic classes. These results resolve the DLBCL microenvironment at systems-level resolution and identify opportunities for therapeutic targeting (https://ecotyper.stanford.edu/lymphoma).

The PD-1/PD-L1 Checkpoint in Normal Germinal Centers and Diffuse Large B-Cell Lymphomas

Besides a recognized role of PD-1/PD-L1 checkpoint in anti-tumour immune evasion, there is accumulating evidence that PD-1/PD-L1 interactions between B and T cells also play an important role in normal germinal center (GC) reactions. Even when smaller in number, T follicular helper cells (TFH) and regulatory T (TFR) or B (Breg) cells are involved in positive selection of GC B cells and may result critical in the lymphoma microenvironment. Here, we discuss a role of PD-1/PD-L1 during tumour evolution in diffuse large B cell lymphoma (DLBCL), a paradigm of GC-derived lymphomagenesis. We depict a progression model, in two phases, where malignant B cells take advantage of positive selection signals derived from correct antigen-presentation and PD-1/PD-L1 inter-cellular crosstalks to survive and initiate tumour expansion. Later, a constant pressure for the accumulation of genetic/epigenetic alterations facilitates that DLBCL cells exhibit higher PD-L1 levels and capacity to secrete IL-10, resembling Breg-like features. As a result, a complex immunosuppressive microenvironment is established where DLBCL cells sustain proliferation and survival by impairing regulatory control of TFR cells and limiting IL-21-mediated anti-tumour functions of TFH cells and maximize the use of PD-1/PD-L1 signaling to escape from CD8+ cytotoxic activity. Integration of these molecular and cellular addictions into a framework may contribute to the better understanding of the lymphoma microenvironment and contribute to the rationale for novel PD-1/PD-L1-based combinational immunotherapies in DLBCL.

SPARC-positive macrophages are the superior prognostic factor in the microenvironment of diffuse large B-cell lymphoma and independent of MYC rearrangement and double-/triple-hit status

BACKGROUND

Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous disease with respect to outcome. Features of the tumor microenvironment (TME) are associated with prognosis when assessed by gene expression profiling. However, it is uncertain whether assessment of the microenvironment can add prognostic information to the most relevant and clinically well-established molecular subgroups when analyzed by immunohistochemistry (IHC).

PATIENTS AND METHODS

We carried out a histopathologic analysis of biomarkers related to TME in a very large cohort (n = 455) of DLBCL treated in prospective trials and correlated with clinicopathologic and molecular data, including chromosomal rearrangements and gene expression profiles for cell-of-origin and TME.

RESULTS

The content of PD1+, FoxP3+ and CD8+, as well as vessel density, was not associated with outcome. However, we found a low content of CD68+ macrophages to be associated with inferior progression-free survival (PFS) and overall survival (OS; P = 0.023 and 0.040, respectively) at both univariable and multivariable analyses, adjusted for the factors of the International Prognostic Index (IPI), MYC break and BCL2/MYC and BCL6/MYC double-hit status. The subgroup of PDL1+ macrophages was not associated with survival. Instead, secreted protein acidic and cysteine rich (SPARC)-positive macrophages were identified as the subtype of macrophages most associated with survival. SPARC-positive macrophages and stromal cells directly correlated with favorable PFS and OS (both, P[log rank] <0.001, P[trend] < 0.001). The association of SPARC with prognosis was independent of the factors of the IPI, MYC double-/triple-hit status, Bcl2/c-myc double expression, cell-of-origin subtype and a recently published gene expression signature [lymphoma-associated macrophage interaction signature (LAMIS)].

CONCLUSIONS

SPARC expression in the TME detected by a single IHC staining with fair-to-good interobserver reproducibility is a powerful prognostic parameter. Thus SPARC expression is a strong candidate for risk assessment in DLBCL in daily practice.

Human B Lymphomas Reveal Their Secrets Through Genetic Mouse Models

Lymphomas are cancers deriving from lymphocytes, arising preferentially in secondary lymphoid organs, and represent the 6th cancer worldwide and the most frequent blood cancer. The majority of B cell Non-Hodgkin lymphomas (B-NHL) develop from germinal center (GC) experienced mature B cells. GCs are transient structures that form in lymphoid organs in response to antigen exposure of naive B cells, and where B cell receptor (BCR) affinity maturation occurs to promote B cell differentiation into memory B and plasma cells producing high-affinity antibodies. Genomic instability associated with the somatic hypermutation (SHM) and class-switch recombination (CSR) processes during GC transit enhance susceptibility to malignant transformation. Most B cell differentiation steps in the GC are at the origin of frequent B cell malignant entities, namely Follicular Lymphoma (FL) and GCB diffuse large B cell lymphomas (GCB-DLBCL). Over the past decade, large sequencing efforts have provided a great boost in the identification of candidate oncogenes and tumor suppressors involved in FL and DLBCL oncogenesis. Mouse models have been instrumental to accurately mimic in vivo lymphoma-specific mutations and interrogate their normal function in the GC context and their oncogenic function leading to lymphoma onset. The limited access of biopsies during the initiating steps of the disease, the cellular and (epi)genetic heterogeneity of individual tumors across and within patients linked to perturbed dynamics of GC ecosystems make the development of genetically engineered mouse models crucial to decipher lymphomagenesis and disease progression and eventually to test the effects of novel targeted therapies. In this review, we provide an overview of some of the important genetically engineered mouse models that have been developed to recapitulate lymphoma-associated (epi)genetic alterations of two frequent GC-derived lymphoma entities: FL and GCB-DLCBL and describe how those mouse models have improved our knowledge of the molecular processes supporting GC B cell transformation.

Integrative Analysis of Next-Generation Sequencing for Next-Generation Cancer Research toward Artificial Intelligence

The rapid improvement of next-generation sequencing (NGS) technologies and their application in large-scale cohorts in cancer research led to common challenges of big data. It opened a new research area incorporating systems biology and machine learning. As large-scale NGS data accumulated, sophisticated data analysis methods became indispensable. In addition, NGS data have been integrated with systems biology to build better predictive models to determine the characteristics of tumors and tumor subtypes. Therefore, various machine learning algorithms were introduced to identify underlying biological mechanisms. In this work, we review novel technologies developed for NGS data analysis, and we describe how these computational methodologies integrate systems biology and omics data. Subsequently, we discuss how deep neural networks outperform other approaches, the potential of graph neural networks (GNN) in systems biology, and the limitations in NGS biomedical research. To reflect on the various challenges and corresponding computational solutions, we will discuss the following three topics: (i) molecular characteristics, (ii) tumor heterogeneity, and (iii) drug discovery. We conclude that machine learning and network-based approaches can add valuable insights and build highly accurate models. However, a well-informed choice of learning algorithm and biological network information is crucial for the success of each specific research question.

An Overview on Diffuse Large B-Cell Lymphoma Models: Towards a Functional Genomics Approach

Simple Summary

Lymphoma research is a paradigm of integrating basic and applied research within the fields of molecular marker-based diagnosis and therapy. In recent years, major advances in next-generation sequencing have substantially improved the understanding of the genomics underlying diffuse large B-cell lymphoma (DLBCL), the most frequent type of B-cell lymphoma. This review addresses the various approaches that have helped unveil the biology and intricate alterations in this pathology, from cell lines to more sophisticated last-generation experimental models, such as organoids. We also provide an overview of the most recent findings in the field, their potential relevance for designing targeted therapies and the corresponding applicability to personalized medicine.

Abstract

Lymphoma research is a paradigm of the integration of basic and clinical research within the fields of diagnosis and therapy. Clinical, phenotypic, and genetic data are currently used to predict which patients could benefit from standard treatment. However, alternative therapies for patients at higher risk from refractoriness or relapse are usually empirically proposed, based on trial and error, without considering the genetic complexity of aggressive B-cell lymphomas. This is primarily due to the intricate mosaic of genetic and epigenetic alterations in lymphomas, which are an obstacle to the prediction of which drug will work for any given patient. Matching a patient’s genes to drug sensitivity by directly testing live tissues comprises the “precision medicine” concept. However, in the case of lymphomas, this concept should be expanded beyond genomics, eventually providing better treatment options for patients in need of alternative therapeutic approaches. We provide an overview of the most recent findings in diffuse large B-cell lymphomas genomics, from the classic functional models used to study tumor biology and the response to experimental treatments using cell lines and mouse models, to the most recent approaches with spheroid/organoid models. We also discuss their potential relevance and applicability to daily clinical practice.

Prognostic molecular biomarkers in diffuse large B-cell lymphoma in the rituximab era and their therapeutic implications

Diffuse large B-cell lymphoma (DLBCL) represents a group of tumors characterized by substantial heterogeneity in terms of their pathological and biological features, a causal factor of their varied clinical outcome. This variation has persisted despite the implementation of rituximab in treatment regimens over the last 20 years. In this context, prognostic biomarkers are of great importance in order to identify high-risk patients that might benefit from treatment intensification or the introduction of novel therapeutic agents. Herein, we review current knowledge on specific immunohistochemical or genetic biomarkers that might be useful in clinical practice. Gene-expression profiling is a tool of special consideration in this effort, as it has enriched our understanding of DLBCL biology and has allowed for the classification of DLBCL by cell-of-origin as well as by more elaborate molecular signatures based on distinct gene-expression profiles. These subgroups might outperform individual biomarkers in terms of prognostication; however, their use in clinical practice is still limited. Moreover, the underappreciated role of the tumor microenvironment in DLBCL prognosis is discussed in terms of prognostic gene-expression signatures, as well as in terms of individual biomarkers of prognostic significance. Finally, the efficacy of novel therapeutic agents for the treatment of DLBCL patients are discussed and an evidence-based therapeutic approach by specific genetic subgroup is suggested.

Predictive and Prognostic Molecular Factors in Diffuse Large B-Cell Lymphomas

Diffuse large B-cell lymphoma (DLBCL) is the commonest form of lymphoid malignancy, with a prevalence of about 40% worldwide. Its classification encompasses a common form, also termed as “not otherwise specified” (NOS), and a series of variants, which are rare and at least in part related to viral agents. Over the last two decades, DLBCL-NOS, which accounts for more than 80% of the neoplasms included in the DLBCL chapter, has been the object of an increasing number of molecular studies which have led to the identification of prognostic/predictive factors that are increasingly entering daily practice. In this review, the main achievements obtained by gene expression profiling (with respect to both neoplastic cells and the microenvironment) and next-generation sequencing will be discussed and compared. Only the amalgamation of molecular attributes will lead to the achievement of the long-term goal of using tailored therapies and possibly chemotherapy-free protocols capable of curing most (if not all) patients with minimal or no toxic effects.