Precision medicine in diffuse large B-cell lymphoma: hitting the target

Superior survival in diffuse large B cell lymphoma of the bone with immune rich tumor microenvironment

With tumor genomic and gene-expression profiling (GEP), this study investigated the immune-molecular signatures of a unique cohort of diffuse large B-cell lymphoma of the bone (bone-DLBCL), including primary bone (PB-DLBCL, n = 52) and polyostotic-DLBCL (n = 20), in comparison to nodal DLBCLs with germinal center B-cell (GCB) phenotype (nodal-DLBCL-GCB, n = 34). PB-DLBCL and polyostotic-DLBCL shared similar genomic profiles and transcriptomic signatures, justifying their collective analysis as bone-DLBCL. Differential incidences of EZH2, HIST1H1E, and MYC aberrations (p < 0.05) confirmed the distinct oncogenic evolution between bone-DLBCL and nodal-DLBCL-GCB. Differentially expressed genes were identified between bone-DLBCL and nodal-DLBCL-GCB (p < 0.001), substantiated by distinct gene-set enrichment analysis (GSEA). In contrast to a more 'depleted' phenotype for nodal-DLBCL-GCB, bone-DLBCL primarily exhibited an 'intermediate/rich' tumor microenvironment (TME) signature (p = 0.001), as determined by a previously published gene set. Unsupervised clustering defined two distinct groups that aligned with previously reported immune-enriched TME clusters: an 'immune-rich' cluster largely consisting of bone-DLBCLs (75%, p = 0.002) with superior survival (p = 0.030), and a poor-prognostic 'immune-low' cluster, including mostly nodal-DLBCL-GCB (61%). Single-sample (ss)GSEA showed higher scores for regulatory T cells, immunosuppressive/prolymphoma cytokines, and vascular endothelial cells in immune-rich samples (p < 0.001). Additionally, CIBERSORTx revealed a higher abundance of regulatory T cells and activated mast cells in the immune-rich cluster (p < 0.001). These findings were confirmed at protein level, where CD3 and FOXP3 immunochemistry showed significant overlap with the gene-expression data (p < 0.001). Conclusively, PB-DLBCL and polyostotic-DLBCL share immune-molecular TME characteristics, supporting their classification as a unified bone-DLBCL entity. The distinct immune-rich TME profile of bone-DLBCL associated with superior survival potentially shapes emerging immunomodulatory strategies.

Extracellular vesicles as source of biomarkers in hematological malignancies: looking towards clinical applications

INTRODUCTION

Extracellular vesicles are membranous particles released by cells in physiological and pathological conditions. Their cargo is heterogeneous since it includes different biomolecules such as nucleic acids and proteins. Oncogenic alterations affect the composition of extracellular vesicles and model their content during cancer evolution.

AREAS COVERED

This review provides an overview of the studies focused on extracellular vesicles as source of biomarkers in hematological malignancies. A special insight into extracellular vesicles-derived biomarkers as tools for evaluating the prognosis of hematological malignancies and their response to treatment is given.

EXPERT OPINION

Extracellular vesicles are a valuable source of biomarkers in hematological malignancies. However, the translation from the bench to the bedside is challenged by the lack of standardization of the preanalytical variables of the experimental workflow. The release of standard operating procedures and the validation of the extracellular vesicles-derived biomarkers in large cohort of patients will help in exploiting the potential of extracellular vesicles in the clinical setting.

Real-world routine diagnostic molecular analysis for TP53 mutational status is recommended over p53 immunohistochemistry in B-cell lymphomas

Previous studies in patients with mature B-cell lymphomas (MBCL) have shown that pathogenic TP53 aberrations are associated with inferior chemotherapeutic efficacy and survival outcomes. In solid malignancies, p53 immunohistochemistry is commonly used as a surrogate marker to assess TP53 mutations, but this correlation is not yet well-established in lymphomas. This study evaluated the accuracy of p53 immunohistochemistry as a surrogate marker for TP53 mutational analysis in a large real-world patient cohort of 354 MBCL patients within routine diagnostic practice. For each case, p53 IHC was assigned to one of three categories: wild type (staining 1-50% of tumor cells with variable nuclear staining), abnormal complete absence or abnormal overexpression (strong and diffuse staining > 50% of tumor cells). Pathogenic variants of TP53 were identified with a targeted next generation sequencing (tNGS) panel. Wild type p53 expression was observed in 267 cases (75.4%), complete absence in twenty cases (5.7%) and the overexpression pattern in 67 cases (18.9%). tNGS identified a pathogenic TP53 mutation in 102 patients (29%). The overall accuracy of p53 IHC was 84.5% (95% CI 80.3-88.1), with a robust specificity of 92.1% (95% CI 88.0- 95.1), but a low sensitivity of 65.7% (95% CI 55.7-74.8). These results suggest that the performance of p53 IHC is insufficient as a surrogate marker for TP53 mutations in our real-world routine diagnostic workup of MBCL patients. By using p53 immunohistochemistry alone, there is a significant risk a TP53 mutation will be missed, resulting in misevaluation of a high-risk patient. Therefore, molecular analysis is recommended in all MBCL patients, especially for further development of risk-directed therapies based on TP53 mutation status.

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.

Frequent mutated B2M, EZH2, IRF8, and TNFRSF14 in primary bone diffuse large B-cell lymphoma reflect a GCB phenotype

Primary bone diffuse large B-cell lymphoma (PB-DLBCL) is a rare extranodal lymphoma subtype. This retrospective study elucidates the currently unknown genetic background of a large clinically well-annotated cohort of DLBCL with osseous localizations (O-DLBCL), including PB-DLBCL. A total of 103 patients with O-DLBCL were included and compared with 63 (extra)nodal non-osseous (NO)-DLBCLs with germinal center B-cell phenotype (NO-DLBCL-GCB). Cell-of-origin was determined by immunohistochemistry and gene-expression profiling (GEP) using (extended)-NanoString/Lymph2Cx analysis. Mutational profiles were identified with targeted next-generation deep sequencing, including 52 B-cell lymphoma-relevant genes. O-DLBCLs, including 34 PB-DLBCLs, were predominantly classified as GCB phenotype based on immunohistochemistry (74%) and NanoString analysis (88%). Unsupervised hierarchical clustering of an extended-NanoString/Lymph2Cx revealed significantly different GEP clusters for PB-DLBCL as opposed to NO-DLBCL-GCB (P < .001). Expression levels of 23 genes of 2 different targeted GEP panels indicated a centrocyte-like phenotype for PB-DLBCL, whereas NO-DLBCL-GCB exhibited a centroblast-like constitution. PB-DLBCL had significantly more frequent mutations in four GCB-associated genes (ie, B2M, EZH2, IRF8, TNFRSF14) compared with NO-DLBCL-GCB (P = .031, P = .010, P = .047, and P = .003, respectively). PB-DLBCL, with its corresponding specific mutational profile, was significantly associated with a superior survival compared with equivalent Ann Arbor limited-stage I/II NO-DLBCL-GCB (P = .016). This study is the first to show that PB-DLBCL is characterized by a GCB phenotype, with a centrocyte-like GEP pattern and a GCB-associated mutational profile (both involved in immune surveillance) and a favorable prognosis. These novel biology-associated features provide evidence that PB-DLBCL represents a distinct extranodal DLBCL entity, and its specific mutational landscape offers potential for targeted therapies (eg, EZH2 inhibitors).

Mutational Profile and Clonal Evolution of Relapsed/Refractory Diffuse Large B-Cell Lymphoma

Primary refractory/relapsed diffuse large B-cell lymphoma (rrDLBCL) is an unresolved issue for DLBCL treatment and new treatments to overcome resistance is required. To explore the genetic mechanisms underlying treatment resistance in rrDLBCL and to identify candidate genes, we performed targeted deep sequencing of 430 lymphoma-related genes from 58 patients diagnosed with rrDLBCL. Genetic alterations found between the initial biopsy and biopsy at recurrence or refractory disease were investigated. The genes most frequently altered (> 20%) were (in decreasing order of frequency) CDKN2A, PIM1, CD79B, TP53, MYD88, MYC, BTG2, BTG1, CDKN2B, DTX1, CD58, ETV6, and IRF4. Genes mutation of which in pretreatment sample were associated with poor overall survival included NOTCH1, FGFR2, BCL7A, BCL10, SPEN and TP53 (P < 0.05). FGFR2, BCL2, BCL6, BCL10, and TP53 were associated with poor progression-free survival (P < 0.05). Most mutations were truncal and were maintained in both the initial biopsy and post-treatment biopsy with high dynamics of subclones. Immune-evasion genes showed increased overall mutation frequency (CD58, B2M) and variant allele fraction (CD58), and decreased copy number (B2M, CD70) at the post-treatment biopsy. Using the established mutational profiles and integrative analysis of mutational evolution, we identified information about candidate genes that may be useful for the development of future treatment strategies.

Using Informatics Tools to Identify Opportunities for Precision Medicine in Diffuse Large B-cell Lymphoma

INTRODUCTION

Diffuse large B-cell lymphoma (DLBCL) is genetically and clinically heterogeneous. Despite advances in genomic subtyping, standard frontline chemoimmunotherapy has remained unchanged for years. As high-throughput analysis becomes more accessible, characterizing drug-gene interactions in DLBCL could support patient-specific treatment strategies.

MATERIALS AND METHODS

From our systematic literature review, we compiled a comprehensive list of somatic mutations implicated in DLBCL. We extracted reported and primary sequencing data for these mutations and assessed their association with signaling pathways, cell-of-origin subtypes, and clinical outcomes.

RESULTS

Twenty-two targetable mutations present in ≥ 5% of patients with DLBCL were associated with unfavorable outcomes, yielding a predicted population of 31.7% of DLBCL cases with poor-risk disease and candidacy for targeted therapy. A second review identified 256 studies that had characterized the drug-gene interactions for these mutations via in vitro studies, mouse models, and/or clinical trials.

CONCLUSIONS

Our novel approach linking the data from our systematic reviews with informatics tools identified high-risk DLBCL subgroups, DLBCL-specific drug-gene interactions, and potential populations for precision medicine trials.

MYD88 mutations identify a molecular subgroup of diffuse large B-cell lymphoma with an unfavorable prognosis

The 2016 World Health Organization classification defines diffuse large B-cell lymphoma (DLBCL) subtypes based on Epstein-Barr virus (EBV) infection and oncogenic rearrangements of MYC/BCL2/BCL6 as drivers of lymphomagenesis. A subset of DLBCL, however, is characterized by activating mutations in MYD88/CD79B We investigated whether MYD88/CD79B mutations could improve the classification and prognostication of DLBCL. In 250 primary DLBCL, MYD88/CD79B mutations were identified by allele-specific polymerase chain reaction or next-generation-sequencing, MYC/BCL2/BCL6 rearrangements were analyzed by fluorescence in situ hybridization, and EBV was studied by EBV-encoded RNA in situ hybridization. Associations of molecular features with clinicopathologic characteristics, outcome, and prognosis according to the International Prognostic Index (IPI) were investigated. MYD88 and CD79B mutations were identified in 29.6% and 12.3%, MYC, BCL2, and BCL6 rearrangements in 10.6%, 13.6%, and 20.3%, and EBV in 11.7% of DLBCL, respectively. Prominent mutual exclusivity between EBV positivity, rearrangements, and MYD88/CD79B mutations established the value of molecular markers for the recognition of biologically distinct DLBCL subtypes. MYD88-mutated DLBCL had a significantly inferior 5-year overall survival than wild-type MYD88 DLBCL (log-rank; P=0.019). DLBCL without any of the studied aberrations had superior overall survival compared to cases carrying ≥1 aberrancy (log-rank; P=0.010). MYD88 mutations retained their adverse prognostic impact upon adjustment for other genetic and clinical variables by multivariable analysis and improved the prognostic performance of the IPI. This study demonstrates the clinical utility of defining MYD88-mutated DLBCL as a distinct molecular subtype with adverse prognosis. Our data call for sequence analysis of MYD88 in routine diagnostics of DLBCL to optimize classification and prognostication, and to guide the development of improved treatment strategies.

Cost burden of diffuse large B-cell lymphoma

Introduction: Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma and is a clinically heterogeneous disease. Treatment pathways for DLBCL are diverse and integrate established and novel therapies.Areas covered: We review the cost burden of DLBCL and the cost-effectiveness of DLBCL management including precision and cellular medicine. We utilized Medical Subject Heading (MeSH) terms and keywords to search the National Library of Medicine online MEDLINE database (PubMed) for articles related to cost, cost burden, and cost-of-illness of DLBCL and cost-effectiveness of DLBCL management strategies published in English as of June 2019.Expert commentary: Available and developing DLBCL therapies offer improved outcomes and often curative treatment at considerable financial expense, and the total cost burden for DLBCL management is substantial for patients and the healthcare system. In the era of personalized medicine, CAR T cells and targeted therapies provide exciting avenues for current and future DLBCL care and can further increase treatment cost. Determinations of cost and cost-effectiveness in DLBCL treatment pathways should continue to guide care providers and systems in identifying cost reduction strategies to provide appropriate therapies to the greatest number of patients in treating DLBCL.

MYD88 in the driver's seat of B-cell lymphomagenesis: from molecular mechanisms to clinical implications

More than 50 subtypes of B-cell non-Hodgkin lymphoma (B-NHL) are recognized in the most recent World Health Organization classification of 2016. The current treatment paradigm, however, is largely based on 'one-size-fits-all' immune-chemotherapy. Unfortunately, this therapeutic strategy is inadequate for a significant number of patients. As such, there is an indisputable need for novel, preferably targeted, therapies based on a biologically driven classification and risk stratification. Sequencing studies identified mutations in the MYD88 gene as an important oncogenic driver in B-cell lymphomas. MYD88 mutations constitutively activate NF-κB and its associated signaling pathways, thereby promoting B-cell proliferation and survival. High frequencies of the hotspot MYD88(L265P) mutation are observed in extranodal diffuse large B-cell lymphoma and Waldenström macroglobulinemia, thereby demonstrating this mutation's potential as a disease marker. In addition, the presence of mutant MYD88 predicts survival outcome in B-NHL subtypes and it provides a therapeutic target. Early clinical trials targeting MYD88 have shown encouraging results in relapsed/refractory B-NHL. Patients with these disorders can benefit from analysis for the MYD88 hotspot mutation in liquid biopsies, as a minimally invasive method to demonstrate treatment response or resistance. Given these clear clinical implications and the crucial role of MYD88 in lymphomagenesis, we expect that analysis of this gene will increasingly be used in routine clinical practice, not only as a diagnostic classifier, but also as a prognostic and therapeutic biomarker directing precision medicine. This review focuses on the pivotal mechanistic role of mutated MYD88 and its clinical implications in B-NHL.

Remaining challenges in predicting patient outcomes for diffuse large B-cell lymphoma

Introduction: Diffuse large B-cell lymphoma (DLBCL) is the most common non-Hodgkin lymphoma and is an aggressive malignancy with heterogeneous outcomes. Diverse methods for DLBCL outcomes assessment ranging from clinical to genomic have been developed with variable predictive and prognostic success.Areas covered: The authors provide an overview of the various methods currently used to estimate prognosis in DLBCL patients. Models incorporating cell of origin, genomic features, sociodemographic factors, treatment effectiveness measures, and machine learning are described.Expert opinion: The clinical and genetic heterogeneity of DLBCL presents distinct challenges in predicting response to therapy and overall prognosis. Successful integration of predictive and prognostic tools in clinical trials and in a standard clinical workflow for DLBCL will likely require a combination of methods incorporating clinical, sociodemographic, and molecular factors with the aid of machine learning and high-dimensional data analysis.

A B-cell-associated gene signature classification of diffuse large B-cell lymphoma by NanoString technology

Gene expression profiling (GEP) by microarrays of diffuse large B-cell lymphoma (DLBCL) has enabled the categorization of DLBCL into activated B-cell-like and germinal center B-cell-like subclasses. However, as this does not fully embrace the great diversity of B-cell subtypes, we recently developed a gene expression assay for B-cell-associated gene signature (BAGS) classification. To facilitate quick and easy-to-use BAGS profiling, we developed in this study the NanoString-based BAGS2Clinic assay. Microarray data from 4 different cohorts (n = 970) were used to select genes and train the assay. The locked assay was validated in an independent cohort of 88 sample biopsies. The assay showed good correspondence with the original BAGS classifier, with an overall accuracy of 84% (95% confidence interval, 72% to 93%) and a subtype-specific accuracy ranging between 80% and 99%. BAGS classification has the potential to provide valuable insight into tumor biology as well as differences in resistance to immuno- and chemotherapy that can lead to novel treatment strategies for DLBCL patients. BAGS2Clinic can facilitate this and the implementation of BAGS classification as a routine clinical tool to improve prognosis and treatment guidance for DLBCL patients.

Integrating genomic alterations in diffuse large B-cell lymphoma identifies new relevant pathways and potential therapeutic targets

Genome studies of diffuse large B-cell lymphoma (DLBCL) have revealed a large number of somatic mutations and structural alterations. However, the clinical significance of these alterations is still not well defined. In this study, we have integrated the analysis of targeted next-generation sequencing of 106 genes and genomic copy number alterations (CNA) in 150 DLBCL. The clinically significant findings were validated in an independent cohort of 111 patients. Germinal center B-cell and activated B-cell DLBCL had a differential profile of mutations, altered pathogenic pathways and CNA. Mutations in genes of the NOTCH pathway and tumor suppressor genes (TP53/CDKN2A), but not individual genes, conferred an unfavorable prognosis, confirmed in the independent validation cohort. A gene expression profiling analysis showed that tumors with NOTCH pathway mutations had a significant modulation of downstream target genes, emphasizing the relevance of this pathway in DLBCL. An in silico drug discovery analysis recognized 69 (46%) cases carrying at least one genomic alteration considered a potential target of drug response according to early clinical trials or preclinical assays in DLBCL or other lymphomas. In conclusion, this study identifies relevant pathways and mutated genes in DLBCL and recognizes potential targets for new intervention strategies.

Klotho, an anti-aging gene, acts as a tumor suppressor and inhibitor of IGF-1R signaling in diffuse large B cell lymphoma

Background

Klotho, is a transmembrane protein, performs as a circulating hormone and upstream modulator of the insulin-like growth factor-1 receptor (IGF-1R), fibroblast growth factor (FGF), and Wnt signaling pathways. These pathways are involved in the development and progression of B cell lymphoma. We aimed to explore the expression pattern and functional mechanism of Klotho in diffuse large B cell lymphoma (DLBCL).

Methods

Immunohistochemistry (IHC) and western blotting were performed to detect the expression level of Klotho in DLBCL patients and cell lines. Tumor suppressive effect of Klotho was determined by both in vitro and in vivo studies. Signaling pathway activity was assessed by western blotting.

Results

Remarkable lower expression levels of Klotho were observed in DLBCL patients and cell lines. Enforced expression of Klotho could significantly induce cell apoptosis and inhibit tumor growth in DLBCL. Upregulation of Klotho resulted in declined activation of IGF-1R signaling, accompanied with decreased phosphorylation of its downstream targets, including AKT and ERK1/2. Moreover, xenograft model treated with either Klotho overexpression vector or recombinant human Klotho administration presented restrained tumor growth and lower Ki67 staining.

Conclusions

Our findings establish that Klotho performs as a tumor suppressor and modulator of IGF-1R signaling in DLBCL. Targeting Klotho may provide novel strategies for future therapeutic intervention.