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

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

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.

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

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

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.

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.

Mass Spectrometry Acquisition and Fractionation Recommendations for TMT11 and TMT16 Labeled Samples.

Proteome coverage and accurate protein quantification are both important for evaluating biological systems; however, compromises between quantification, coverage, and mass spectrometry (MS) resources are often necessary. Consequently, experimental parameters that impact coverage and quantification must be adjusted, depending on experimental goals. Among these parameters is offline prefractionation, which is utilized in MS-based proteomics to decrease sample complexity resulting in higher overall proteome coverage upon MS analysis. Prefractionation leads to increases in required MS analysis time, although this is often mitigated by isobaric labeling using tandem-mass tags (TMT), which allow samples to be multiplexed. Here we evaluate common prefractionation schemes, TMT variants, and MS acquisition methods and their impact on protein quantification and coverage. Furthermore, we provide recommendations for experimental design depending on the experimental goals.

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.

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.

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.

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.

Evolutionary conservation of systemic and reversible amyloid aggregation.

In response to environmental stress, human cells have been shown to form reversible amyloid aggregates within the nucleus, termed amyloid bodies (A-bodies). These protective physiological structures share many of the biophysical characteristics associated with the pathological amyloids found in Alzheimer's and Parkinson's disease. Here, we show that A-bodies are evolutionarily conserved across the eukaryotic domain, with their detection in Drosophila melanogaster and Saccharomyces cerevisiae marking the first examples of these functional amyloids being induced outside of a cultured cell setting. The conditions triggering amyloidogenesis varied significantly among the species tested, with results indicating that A-body formation is a severe, but sublethal, stress response pathway that is tailored to the environmental norms of an organism. RNA-sequencing analyses demonstrate that the regulatory low-complexity long non-coding RNAs that drive A-body aggregation are both conserved and essential in human, mouse and chicken cells. Thus, the identification of these natural and reversible functional amyloids in a variety of evolutionarily diverse species highlights the physiological significance of this protein conformation, and will be informative in advancing our understanding of both functional and pathological amyloid aggregation events. This article has an associated First Person interview with the first author of the paper.

Characterization of DLBCL with a PMBL gene expression signature.

Primary mediastinal large B-cell lymphoma (PMBL) is a type of aggressive B-cell lymphoma that typically affects young adults, characterized by presence of a bulky anterior mediastinal mass. Lymphomas with gene expression features of PMBL have been described in nonmediastinal sites, raising questions about how these tumors should be classified. Here, we investigated whether these nonmediastinal lymphomas are indeed PMBLs or instead represent a distinct group within diffuse large B-cell lymphoma (DLBCL). From a cohort of 325 de novo DLBCL cases, we identified tumors from patients without evidence of anterior mediastinal involvement that expressed a PMBL expression signature (nm-PMBLsig+; n = 16; 5%). A majority of these tumors expressed MAL and CD23, proteins typically observed in bona fide PMBL (bf-PMBL). Evaluation of clinical features of nm-PMBLsig+ cases revealed close associations with DLBCL, and a majority displayed a germinal center B cell-like cell of origin (GCB). In contrast to patients with bf-PMBL, patients with nm-PMBLsig+ presented at an older age and did not show pleural disease, and bone/bone marrow involvement was observed in 3 cases. However, although clinically distinct from bf-PMBL, nm-PMBLsig+ tumors resembled bf-PMBL at the molecular level, with upregulation of immune response, JAK-STAT, and NF-κB signatures. Mutational analysis revealed frequent somatic gene mutations in SOCS1, IL4R, ITPKB, and STAT6, as well as CD83 and BIRC3, with the latter genes significantly more frequently affected than in GCB DLBCL or bf-PMBL. Our data establish nm-PMBLsig+ lymphomas as a group within DLBCL with distinct phenotypic and genetic features. These findings may have implications for gene expression- and mutation-based subtyping of aggressive B-cell lymphomas and related targeted therapies.

The impact of MYC and BCL2 structural variants in tumors of DLBCL morphology and mechanisms of false-negative MYC IHC.

When the World Health Organization defined high-grade B-cell lymphoma with MYC and BCL2 and/or BCL6 rearrangements (HGBL-DH/TH) as a clinical category, rearrangements were the only structural variant (SV) incorporated. An "atypical double-hit" category has been proposed, encompassing tumors with concurrent MYC and BCL2 SVs other than cooccurring translocations (ie, copy number variations [CNVs]). Although the identification of a gene expression signature (DHITsig) shared among tumors harboring MYC and BCL2 rearrangements (HGBL-DH/TH-BCL2) has confirmed a common underlying biology, the biological implication of MYC and BCL2 CNVs requires further elucidation. We performed a comprehensive analysis of MYC and BCL2 SVs, as determined by fluorescent in situ hybridization (FISH), in a cohort of 802 de novo tumors with diffuse large B-cell lymphoma morphology. Although BCL2 CNVs were associated with increased expression, MYC CNVs were not. Furthermore, MYC and BCL2 CNVs, in the context of atypical double-hit, did not confer a similar gene expression profile as HGBL-DH/TH-BCL2. Finally, although MYC immunohistochemistry (IHC) has been proposed as a screening tool for FISH testing, 2 mechanisms were observed that uncoupled MYC rearrangement from IHC positivity: (1) low MYC messenger RNA expression; and (2) false-negative IHC staining mediated by a single-nucleotide polymorphism resulting in an asparagine-to-serine substitution at the 11th amino acid residue of MYC (MYC-N11S). Taken together, these results support the current exclusion of MYC and BCL2 CNVs from HGBL-DH/TH and highlight the ability of a molecular-based classification system to identify tumors with shared biology that FISH and IHC fail to fully capture.

Molecular profiling in diffuse large B-cell lymphoma: why so many types of subtypes?

The term diffuse large B-cell lymphoma (DLBCL) includes a heterogeneous collection of biologically distinct tumours. This heterogeneity currently presents a barrier to the successful deployment of novel, biologically targeted therapies. Molecular profiling studies have recently proposed new molecular classification systems. These have the potential to resolve the biological heterogeneity of DLBCL into manageable subgroups of tumours that rely on shared oncogenic programmes. In many cases these biological programmes straddle the boundaries of our existing systems for classifying B-cell lymphomas. Here we review the findings from these major molecular profiling studies with a specific focus on those that propose new genetic subgroups of DLBCL. We highlight the areas of consensus and discordance between these studies and discuss the implications for current clinical practice and for clinical trials. Finally, we address the outstanding challenges and solutions to the introduction of genomic subtyping and precision medicine in DLBCL.

Coding and noncoding drivers of mantle cell lymphoma identified through exome and genome sequencing.

Mantle cell lymphoma (MCL) is an uncommon B-cell non-Hodgkin lymphoma (NHL) that is incurable with standard therapies. The genetic drivers of this cancer have not been firmly established, and the features that contribute to differences in clinical course remain limited. To extend our understanding of the biological pathways involved in this malignancy, we performed a large-scale genomic analysis of MCL using data from 51 exomes and 34 genomes alongside previously published exome cohorts. To confirm our findings, we resequenced the genes identified in the exome cohort in 191 MCL tumors, each having clinical follow-up data. We confirmed the prognostic association of TP53 and NOTCH1 mutations. Our sequencing revealed novel recurrent noncoding mutations surrounding a single exon of the HNRNPH1gene. In RNA-seq data from 103 of these cases, MCL tumors with these mutations had a distinct imbalance of HNRNPH1 isoforms. This altered splicing of HNRNPH1 was associated with inferior outcomes in MCL and showed a significant increase in protein expression by immunohistochemistry. We describe a functional role for these recurrent noncoding mutations in disrupting an autoregulatory feedback mechanism, thereby deregulating HNRNPH1 protein expression. Taken together, these data strongly imply a role for aberrant regulation of messenger RNA processing in MCL pathobiology.

In vitro analyses of suspected arrhythmogenic thin filament variants as a cause of sudden cardiac death in infants.

Sudden unexpected death of an infant (SUDI) is a devastating occurrence for families. To investigate the genetic pathogenesis of SUDI, we sequenced >70 genes from 191 autopsy-negative SUDI victims. Ten infants sharing a previously unknown variant in troponin I (TnI) were identified. The mutation (TNNI1 R37C+/-) is in the fetal/neonatal paralog of TnI, a gene thought to be expressed in the heart up to the first 24 months of life. Using phylogenetic analysis and molecular dynamics simulations, it was determined that arginine at residue 37 in TNNI1 may play a critical functional role, suggesting that the variant may be pathogenic. We investigated the biophysical properties of the TNNI1 R37C mutation in human reconstituted thin filaments (RTFs) using fluorometry. RTFs reconstituted with the mutant R37C TnI exhibited reduced Ca2+-binding sensitivity due to an increased Ca2+ off-rate constant. Furthermore, we generated TNNI1 R37C+/- mutants in human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs) using CRISPR-Cas9. In monolayers of hiPSC-CMs, we simultaneously monitored voltage and Ca2+ transients through optical mapping and compared them to their isogenic controls. We observed normal intrinsic beating patterns under control conditions in TNNI1 R37C+/- at stimulation frequencies of 55 beats/min (bpm), but these cells showed no restitution with increased stimulation frequency to 65 bpm and exhibited alternans at >75 bpm. The WT hiPSC-CMs did not exhibit any sign of arrhythmogenicity even at stimulation frequencies of 120 bpm. The approach used in this study provides critical physiological and mechanistic bases to investigate sarcomeric mutations in the pathogenesis of SUDI.

The double-hit signature identifies double-hit diffuse large B-cell lymphoma with genetic events cryptic to FISH.

High-grade B-cell lymphomas with MYC and BCL2 and/or BCL6 rearrangements (HGBL-DH/THs) include a group of diffuse large B-cell lymphomas (DLBCLs) with inferior outcomes after standard chemoimmunotherapy. We recently described a gene expression signature that identifies 27% of germinal center B-cell DLBCLs (GCB-DLBCLs) as having a double-hit-like expression pattern (DHITsig) and inferior outcomes; however, only half of these cases have both MYC and BCL2 translocations identifiable using standard breakapart fluorescence in situ hybridization (FISH). Here, 20 DHITsig+ GCB-DLBCLs apparently lacking MYC and/or BCL2 rearrangements underwent whole-genome sequencing. This revealed 6 tumors with MYC or BCL2 rearrangements that were cryptic to breakapart FISH. Copy-number analysis identified 3 tumors with MYC and 6 tumors with MIR17HG gains or amplifications, both of which may contribute to dysregulation of MYC and its downstream pathways. Focal deletions of the PVT1 promoter were observed exclusively among DHITsig+ tumors lacking MYC translocations; this may also contribute to MYC overexpression. These results highlight that FISH fails to identify all HGBL-DH/THs, while revealing a range of other genetic mechanisms potentially underlying MYC dysregulation in DHITsig+ DLBCL, suggesting that gene expression profiling is more sensitive for identifying the biology underlying poor outcomes in GCB-DLBCL.

Collaborative intra-tumor heterogeneity detection.

MOTIVATION: Despite the remarkable advances in sequencing and computational techniques, noise in the data and complexity of the underlying biological mechanisms render deconvolution of the phylogenetic relationships between cancer mutations difficult. Besides that, the majority of the existing datasets consist of bulk sequencing data of single tumor sample of an individual. Accurate inference of the phylogenetic order of mutations is particularly challenging in these cases and the existing methods are faced with several theoretical limitations. To overcome these limitations, new methods are required for integrating and harnessing the full potential of the existing data. RESULTS: We introduce a method called Hintra for intra-tumor heterogeneity detection. Hintra integrates sequencing data for a cohort of tumors and infers tumor phylogeny for each individual based on the evolutionary information shared between different tumors. Through an iterative process, Hintra learns the repeating evolutionary patterns and uses this information for resolving the phylogenetic ambiguities of individual tumors. The results of synthetic experiments show an improved performance compared to two state-of-the-art methods. The experimental results with a recent Breast Cancer dataset are consistent with the existing knowledge and provide potentially interesting findings. AVAILABILITY AND IMPLEMENTATION: The source code for Hintra is available at https://github.com/sahandk/HINTRA.

SUBSTRA: Supervised Bayesian Patient Stratification.

MOTIVATION: Patient stratification methods are key to the vision of precision medicine. Here, we consider transcriptional data to segment the patient population into subsets relevant to a given phenotype. Whereas most existing patient stratification methods focus either on predictive performance or interpretable features, we developed a method striking a balance between these two important goals. RESULTS: We introduce a Bayesian method called SUBSTRA that uses regularized biclustering to identify patient subtypes and interpretable subtype-specific transcript clusters. The method iteratively re-weights feature importance to optimize phenotype prediction performance by producing more phenotype-relevant patient subtypes. We investigate the performance of SUBSTRA in finding relevant features using simulated data and successfully benchmark it against state-of-the-art unsupervised stratification methods and supervised alternatives. Moreover, SUBSTRA achieves predictive performance competitive with the supervised benchmark methods and provides interpretable transcriptional features in diverse biological settings, such as drug response prediction, cancer diagnosis, or kidney transplant rejection. AVAILABILITY AND IMPLEMENTATION: The R code of SUBSTRA is available at https://github.com/sahandk/SUBSTRA. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.