STAT6 mutations enriched at diffuse large B-cell lymphoma relapse reshape the tumor microenvironment.

Diffuse large B-cell lymphoma (DLBCL) relapses in approximately 40% of patients following frontline therapy. We reported that STAT6D419 mutations are enriched in relapsed/refractory DLBCL (rrDLBCL) samples, suggesting that JAK/STAT signaling plays a role in therapeutic resistance. We hypothesized that STAT6D419 mutations can improve DLBCL cell survival by reprogramming the microenvironment to sustain STAT6 activation. Thus, we investigated the role of STAT6D419 mutations on DLBCL cell growth and its microenvironment. We found that phospho-STAT6D419N was retained in the nucleus longer than phospho-STAT6WT following IL-4 stimulation, and STAT6D419N recognized a more restricted DNA-consensus sequence than STAT6WT. Upon IL-4 induction, STAT6D419N expression led to a higher magnitude of gene expression changes, but in a more selective list of gene targets compared with STATWT. The most significantly expressed genes induced by STAT6D419N were those implicated in survival, proliferation, migration, and chemotaxis, in particular CCL17. This chemokine, also known as TARC, attracts helper T-cells to the tumor microenvironment, especially in Hodgkin's lymphoma. To this end, in DLBCL, phospho-STAT6+ rrDLBCL cells had a greater proportion of infiltrating CD4+ T-cells than phospho-STAT6- tumors. Our findings suggest that STAT6D419 mutations in DLBCL lead to cell autonomous changes, enhanced signaling, and altered composition of the tumor microenvironment.

Biological heterogeneity in diffuse large B-cell lymphoma.

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.

Relapse Timing Is Associated With Distinct Evolutionary Dynamics in Diffuse Large B-Cell Lymphoma.

PURPOSE: Diffuse large B-cell lymphoma (DLBCL) is cured in more than 60% of patients, but outcomes remain poor for patients experiencing disease progression or relapse (refractory or relapsed DLBCL [rrDLBCL]), particularly if these events occur early. Although previous studies examining cohorts of rrDLBCL have identified features that are enriched at relapse, few have directly compared serial biopsies to uncover biological and evolutionary dynamics driving rrDLBCL. Here, we sought to confirm the relationship between relapse timing and outcomes after second-line (immuno)chemotherapy and determine the evolutionary dynamics that underpin that relationship. PATIENTS AND METHODS: Outcomes were examined in a population-based cohort of 221 patients with DLBCL who experienced progression/relapse after frontline treatment and were treated with second-line (immuno)chemotherapy with an intention-to-treat with autologous stem-cell transplantation (ASCT). Serial DLBCL biopsies from a partially overlapping cohort of 129 patients underwent molecular characterization, including whole-genome or whole-exome sequencing in 73 patients. RESULTS: Outcomes to second-line therapy and ASCT are superior for late relapse (>2 years postdiagnosis) versus primary refractory (<9 months) or early relapse (9-24 months). Diagnostic and relapse biopsies were mostly concordant for cell-of-origin classification and genetics-based subgroup. Despite this concordance, the number of mutations exclusive to each biopsy increased with time since diagnosis, and late relapses shared few mutations with their diagnostic counterpart, demonstrating a branching evolution pattern. In patients with highly divergent tumors, many of the same genes acquired new mutations independently in each tumor, suggesting that the earliest mutations in a shared precursor cell constrain tumor evolution toward the same genetics-based subgroups at both diagnosis and relapse. CONCLUSION: These results suggest that late relapses commonly represent genetically distinct and chemotherapy-naïve disease and have implications for optimal patient management.

Genetic subdivisions of follicular lymphoma defined by distinct coding and noncoding mutation patterns.

Follicular lymphoma (FL) accounts for ∼20% of all new lymphoma cases. Increases in cytological grade are a feature of the clinical progression of this malignancy, and eventual histologic transformation (HT) to the aggressive diffuse large B-cell lymphoma (DLBCL) occurs in up to 15% of patients. Clinical or genetic features to predict the risk and timing of HT have not been described comprehensively. In this study, we analyzed whole-genome sequencing data from 423 patients to compare the protein coding and noncoding mutation landscapes of untransformed FL, transformed FL, and de novo DLBCL. This revealed 2 genetically distinct subgroups of FL, which we have named DLBCL-like (dFL) and constrained FL (cFL). Each subgroup has distinguishing mutational patterns, aberrant somatic hypermutation rates, and biological and clinical characteristics. We implemented a machine learning-derived classification approach to stratify patients with FL into cFL and dFL subgroups based on their genomic features. Using separate validation cohorts, we demonstrate that cFL status, whether assigned with this full classifier or a single-gene approximation, is associated with a reduced rate of HT. This implies distinct biological features of cFL that constrain its evolution, and we highlight the potential for this classification to predict HT from genetic features present at diagnosis.

Relapse timing is associated with distinct evolutionary dynamics in DLBCL.

Diffuse large B-cell lymphoma (DLBCL) is cured in over 60% of patients, but outcomes are poor for patients with relapsed or refractory disease (rrDLBCL). Here, we performed whole genome/exome sequencing (WGS/WES) on tumors from 73 serially-biopsied patients with rrDLBCL. Based on the observation that outcomes to salvage therapy/autologous stem cell transplantation are related to time-to-relapse, we stratified patients into groups according to relapse timing to explore the relationship to genetic divergence and sensitivity to salvage immunochemotherapy. The degree of mutational divergence increased with time between biopsies, yet tumor pairs were mostly concordant for cell-of-origin, oncogene rearrangement status and genetics-based subgroup. In patients with highly divergent tumors, several genes acquired exclusive mutations independently in each tumor, which, along with concordance of genetics-based subgroups, suggests that the earliest mutations in a shared precursor cell constrain tumor evolution. These results suggest that late relapses commonly represent genetically distinct and chemotherapy-naïve disease.

Emerging roles for heterogeneous ribonuclear proteins in normal and malignant B cells.

Heterogeneous nuclear ribonucleoproteins (hnRNPs) are among the most abundantly expressed RNA binding proteins in the cell and play major roles in all facets of RNA metabolism. hnRNPs are increasingly appreciated as essential for mammalian B cell development by regulating the carefully ordered expression of specific genes. Due to this tight regulation of the hnRNP-RNA network, it is no surprise that a growing number of genes encoding hnRNPs have been causally associated with the onset or progression of many cancers, including B cell neoplasms. Here we discuss our current understanding of hnRNP-driven regulation in normal, perturbed, and malignant B cells, and the most recent and emerging therapeutic innovations aimed at targeting the hnRNP-RNA network in lymphoma.

PeptideRanger: An R Package to Optimize Synthetic Peptide Selection for Mass Spectrometry Applications.

Targeted and semitargeted mass spectrometry-based approaches are reliable methods to consistently detect and quantify low abundance proteins including proteins of clinical significance. Despite their potential, the development of targeted and semitargeted assays is time-consuming and often requires the purchase of costly libraries of synthetic peptides. To improve the efficiency of this rate-limiting step, we developed PeptideRanger, a tool to identify peptides from protein of interest with physiochemical properties that make them more likely to be suitable for mass spectrometry analysis. PeptideRanger is a flexible, extensively annotated, and intuitive R package that uses a random forest model trained on a diverse data set of thousands of MS experiments spanning a variety of sample types profiled with different chromatography setups and instruments. To support a variety of applications and to leverage rapidly growing public MS databases, PeptideRanger can readily be retrained with experiment-specific data sets and customized to prioritize and filter peptides based on selected properties.

Molecular determinants of clinical outcomes in a real-world diffuse large B-cell lymphoma population.

Molecular heterogeneity of diffuse large B-cell lymphoma (DLBCL) underlies the variable outcomes achieved with immunochemotherapy. However, outcomes of gene expression profiling (GEP)-defined molecular subgroups in a real-world DLBCL population remain unknown. Here we examined the prevalence and outcomes of molecular subgroups in an unselected population of 1149 patients with de novo DLBCL in British Columbia, Canada. Evaluable biopsies were profiled by fluorescence in situ hybridization (FISH), immunohistochemistry, and digital GEP to assign cell-of-origin and the so-called "double-hit signature" (DHITsig)-a signature originally described as being characteristic for high-grade B-cell lymphoma with MYC and BCL2 rearrangements (HGBCL-DH-BCL2). DHITsig was expressed in 21% of 431 germinal center B-cell-like (GCB)-DLBCL and all 55 Burkitt lymphomas examined. Reflecting this latter finding, DHITsig has been renamed the "dark zone signature" (DZsig). DZsigpos-DLBCL, non-DZsigpos GCB-DLBCL and activated B-cell-like (ABC)-DLBCL were associated with a 2 year overall survival of 57%, 89%, and 71%, respectively. 62% of DZsigpos tumors were negative for HGBCL-DH-BCL2 by FISH, but were associated with outcomes similar to HGBCL-DH-BCL2. A small group of HGBCL-DH-BCL2 that lacked DZsig expression had different molecular features compared with DZsig-expressing HGBCL-DH-BCL2 and were associated with favorable outcomes comparable to DLBCL, not otherwise specified. DZsigpos and ABC-DLBCL had a shorter diagnosis-to-treatment interval (DTI) than GCB-DLBCL, with this metric being associated with outcome. In conclusion, DZsig expression extends beyond HGBCL-DH-BCL2 and captures a poor-prognosis DLBCL subgroup with short DTI, including patients unidentifiable by routine FISH testing, that should be considered for treatment intensification or novel therapies in prospective trials.

Single-cell profiling reveals a memory B cell-like subtype of follicular lymphoma with increased transformation risk.

Follicular lymphoma (FL) is an indolent cancer of mature B-cells but with ongoing risk of transformation to more aggressive histology over time. Recurrent mutations associated with transformation have been identified; however, prognostic features that can be discerned at diagnosis could be clinically useful. We present here comprehensive profiling of both tumor and immune compartments in 155 diagnostic FL biopsies at single-cell resolution by mass cytometry. This revealed a diversity of phenotypes but included two recurrent patterns, one which closely resembles germinal center B-cells (GCB) and another which appears more related to memory B-cells (MB). GCB-type tumors are enriched for EZH2, TNFRSF14, and MEF2B mutations, while MB-type tumors contain increased follicular helper T-cells. MB-type and intratumoral phenotypic diversity are independently associated with increased risk of transformation, supporting biological relevance of these features. Notably, a reduced 26-marker panel retains sufficient information to allow phenotypic profiling of future cohorts by conventional flow cytometry.

Minimal information for reporting a genomics experiment.

Exome and genome sequencing has facilitated the identification of hundreds of genes and other regions that are recurrently mutated in hematologic neoplasms. The data sets from these studies theoretically provide opportunities. Quality differences between data sets can confound secondary analyses. We explore the consequences of these on the conclusions from some recent studies of B-cell lymphomas. We highlight the need for a minimum reporting standard to increase transparency in genomic research.

Molecular determinants of outcomes in relapsed or refractory mantle cell lymphoma treated with ibrutinib or temsirolimus in the MCL3001 (RAY) trial.

Mantle cell lymphoma (MCL) is a rare, incurable lymphoma subtype characterized by heterogeneous outcomes. To better understand the clinical behavior and response to treatment, predictive biomarkers are needed. Using residual archived material from patients enrolled in the MCL3001 (RAY) study, we performed detailed analyses of gene expression and targeted genetic sequencing. This phase III clinical trial randomized patients with relapsed or refractory MCL to treatment with either ibrutinib or temsirolimus. We confirmed the prognostic capability of the gene expression proliferation assay MCL35 in this cohort treated with novel agents; it outperformed the simplified MCL International Prognostic Index in discriminating patients with different outcomes. Regardless of treatment arm, our data demonstrated that this assay captures the risk conferred by known biological factors, including increased MYC expression, blastoid morphology, aberrations of TP53, and truncated CCND1 3' untranslated region. We showed the negative impact of BIRC3 mutations/deletions on outcomes in this cohort and identified that deletion of chromosome 8p23.3 also negatively impacts survival. Restricted to patients with deletions/alterations in TP53, ibrutinib appeared to abrogate the deleterious impact on outcome. These data illustrate the potential to perform a molecular analysis of predictive biomarkers on routine patient samples that can meaningfully inform clinical practice.

Genomic profiling for clinical decision making in lymphoid neoplasms.

With the introduction of large-scale molecular profiling methods and high-throughput sequencing technologies, the genomic features of most lymphoid neoplasms have been characterized at an unprecedented scale. Although the principles for the classification and diagnosis of these disorders, founded on a multidimensional definition of disease entities, have been consolidated over the past 25 years, novel genomic data have markedly enhanced our understanding of lymphomagenesis and enriched the description of disease entities at the molecular level. Yet, the current diagnosis of lymphoid tumors is largely based on morphological assessment and immunophenotyping, with only few entities being defined by genomic criteria. This paper, which accompanies the International Consensus Classification of mature lymphoid neoplasms, will address how established assays and newly developed technologies for molecular testing already complement clinical diagnoses and provide a novel lens on disease classification. More specifically, their contributions to diagnosis refinement, risk stratification, and therapy prediction will be considered for the main categories of lymphoid neoplasms. The potential of whole-genome sequencing, circulating tumor DNA analyses, single-cell analyses, and epigenetic profiling will be discussed because these will likely become important future tools for implementing precision medicine approaches in clinical decision making for patients with lymphoid malignancies.

Super-enhancer hypermutation alters oncogene expression in B cell lymphoma.

Diffuse large B cell lymphoma (DLBCL) is the most common B cell non-Hodgkin lymphoma and remains incurable in around 40% of patients. Efforts to sequence the coding genome identified several genes and pathways that are altered in this disease, including potential therapeutic targets1-5. However, the non-coding genome of DLBCL remains largely unexplored. Here we show that active super-enhancers are highly and specifically hypermutated in 92% of samples from individuals with DLBCL, display signatures of activation-induced cytidine deaminase activity, and are linked to genes that encode B cell developmental regulators and oncogenes. As evidence of oncogenic relevance, we show that the hypermutated super-enhancers linked to the BCL6, BCL2 and CXCR4 proto-oncogenes prevent the binding and transcriptional downregulation of the corresponding target gene by transcriptional repressors, including BLIMP1 (targeting BCL6) and the steroid receptor NR3C1 (targeting BCL2 and CXCR4). Genetic correction of selected mutations restored repressor DNA binding, downregulated target gene expression and led to the counter-selection of cells containing corrected alleles, indicating an oncogenic dependency on the super-enhancer mutations. This pervasive super-enhancer mutational mechanism reveals a major set of genetic lesions deregulating gene expression, which expands the involvement of known oncogenes in DLBCL pathogenesis and identifies new deregulated gene targets of therapeutic relevance.

BCL10 Mutations Define Distinct Dependencies Guiding Precision Therapy for DLBCL.

Activated B cell-like diffuse large B-cell lymphomas (ABC-DLBCL) have unfavorable outcomes and chronic activation of CARD11-BCL10-MALT1 (CBM) signal amplification complexes that form due to polymerization of BCL10 subunits, which is affected by recurrent somatic mutations in ABC-DLBCLs. Herein, we show that BCL10 mutants fall into at least two functionally distinct classes: missense mutations of the BCL10 CARD domain and truncation of its C-terminal tail. Truncating mutations abrogated a motif through which MALT1 inhibits BCL10 polymerization, trapping MALT1 in its activated filament-bound state. CARD missense mutations enhanced BCL10 filament formation, forming glutamine network structures that stabilize BCL10 filaments. Mutant forms of BCL10 were less dependent on upstream CARD11 activation and thus manifested resistance to BTK inhibitors, whereas BCL10 truncating but not CARD mutants were hypersensitive to MALT1 inhibitors. Therefore, BCL10 mutations are potential biomarkers for BTK inhibitor resistance in ABC-DLBCL, and further precision can be achieved by selecting therapy based on specific biochemical effects of distinct mutation classes. SIGNIFICANCE: ABC-DLBCLs feature frequent mutations of signaling mediators that converge on the CBM complex. We use structure-function approaches to reveal that BCL10 mutations fall into two distinct biochemical classes. Both classes confer resistance to BTK inhibitors, whereas BCL10 truncations confer hyperresponsiveness to MALT1 inhibitors, providing a road map for precision therapies in ABC-DLBCLs. See related commentary by Phelan and Oellerich, p. 1844. This article is highlighted in the In This Issue feature, p. 1825.

Combinatorial and Machine Learning Approaches for Improved Somatic Variant Calling From Formalin-Fixed Paraffin-Embedded Genome Sequence Data.

Formalin fixation of paraffin-embedded tissue samples is a well-established method for preserving tissue and is routinely used in clinical settings. Although formalin-fixed, paraffin-embedded (FFPE) tissues are deemed crucial for research and clinical applications, the fixation process results in molecular damage to nucleic acids, thus confounding their use in genome sequence analysis. Methods to improve genomic data quality from FFPE tissues have emerged, but there remains significant room for improvement. Here, we use whole-genome sequencing (WGS) data from matched Fresh Frozen (FF) and FFPE tissue samples to optimize a sensitive and precise FFPE single nucleotide variant (SNV) calling approach. We present methods to reduce the prevalence of false-positive SNVs by applying combinatorial techniques to five publicly available variant callers. We also introduce FFPolish, a novel variant classification method that efficiently classifies FFPE-specific false-positive variants. Our combinatorial and statistical techniques improve precision and F1 scores compared to the results of publicly available tools when tested individually.