Prognostic impact of epigenetic classification in chronic lymphocytic leukemia: The case of subset #2

Biological, prognostic, and therapeutic impact of the epigenome in CLL

Chronic lymphocytic leukemia (CLL) is characterized by widespread alterations in the genetic and epigenetic landscapes which seem to underlie the variable clinical manifestations observed in patients. Over the last decade, epigenomic studies have described the whole-genome maps of DNA methylation and chromatin features of CLL and normal B cells, identifying distinct epigenetic mechanisms operating in tumoral cells. DNA methylation analyses have identified that the CLL methylome contains imprints of the cell of origin, as well as of the proliferative history of the tumor cells, with both being strong independent prognostic predictors. Moreover, single-cell analysis revealed a higher degree of DNA methylation noise in CLL cells, which associates with transcriptional plasticity and disease aggressiveness. Integrative analysis of chromatin has uncovered chromatin signatures, as well as regulatory regions specifically active in each CLL subtype or in Richter transformed samples. Unique transcription factor (TF) binding motifs are overrepresented on those regions, suggesting that altered TF networks operate from disease initiation to progression as nongenetic factors mediating the oncogenic transcriptional profiles. Multiomics analysis has identified that response to treatment is modulated by an epigenetic imprint, and that treatments affect chromatin through the activity of particular set of TFs. Additionally, the epigenome is an axis of therapeutic vulnerability in CLL, as it can be targeted by inhibitors of histone modifying enzymes, that have shown promising preclinical results. Altogether, this review aims at summarizing the major findings derived from published literature to distill how altered epigenomic mechanisms contribute to CLL origin, evolution, clinical behavior, and response to treatment.

C-terminal binding protein 2 is a novel tumor suppressor targeting the MYC-IRF4 axis in multiple myeloma

ABSTRACT

Multiple myeloma (MM) cells are addicted to MYC and its direct transactivation targets IRF4 for proliferation and survival. MYC and IRF4 are still considered "undruggable," as most small-molecule inhibitors suffer from low potency, suboptimal pharmacokinetic properties, and undesirable off-target effects. Indirect inhibition of MYC/IRF4 emerges as a therapeutic vulnerability in MM. Here, we uncovered an unappreciated tumor-suppressive role of C-terminal binding protein 2 (CTBP2) in MM via strong inhibition of the MYC-IRF4 axis. In contrast to epithelial cancers, CTBP2 is frequently downregulated in MM, in association with shortened survival, hyperproliferative features, and adverse clinical outcomes. Restoration of CTBP2 exhibited potent antitumor effects against MM in vitro and in vivo, with marked repression of the MYC-IRF4 network genes. Mechanistically, CTBP2 impeded the transcription of MYC and IRF4 by histone H3 lysine 27 deacetylation (H3K27ac) and indirectly via activation of the MYC repressor IFIT3. In addition, activation of the interferon gene signature by CTBP2 suggested its concomitant immunomodulatory role in MM. Epigenetic studies have revealed the contribution of polycomb-mediated silencing and DNA methylation to CTBP2 inactivation in MM. Notably, inhibitors of Enhance of zeste homolog 2, histone deacetylase, and DNA methyltransferase, currently under evaluation in clinical trials, were effective in restoring CTBP2 expression in MM. Our findings indicated that the loss of CTBP2 plays an essential role in myelomagenesis and deciphers an additional mechanistic link to MYC-IRF4 dysregulation in MM. We envision that the identification of novel critical regulators will facilitate the development of selective and effective approaches for treating this MYC/IRF4-addicted malignancy.

Epigenomic Characterization of Lymphoid Neoplasms

Lymphoid neoplasms represent a heterogeneous group of disease entities and subtypes with markedly different molecular and clinical features. Beyond genetic alterations, lymphoid tumors also show widespread epigenomic changes. These severely affect the levels and distribution of DNA methylation, histone modifications, chromatin accessibility, and three-dimensional genome interactions. DNA methylation stands out as a tracer of cell identity and memory, as B cell neoplasms show epigenetic imprints of their cellular origin and proliferative history, which can be quantified by an epigenetic mitotic clock. Chromatin-associated marks are informative to uncover altered regulatory regions and transcription factor networks contributing to the development of distinct lymphoid tumors. Tumor-intrinsic epigenetic and genetic aberrations cooperate and interact with microenvironmental cells to shape the transcriptome at different phases of lymphoma evolution, and intraclonal heterogeneity can now be characterized by single-cell profiling. Finally, epigenetics offers multiple clinical applications, including powerful diagnostic and prognostic biomarkers as well as therapeutic targets.

Machine learning and multi-omics data in chronic lymphocytic leukemia: the future of precision medicine?

Chronic lymphocytic leukemia is a complex and heterogeneous hematological malignancy. The advance of high-throughput multi-omics technologies has significantly influenced chronic lymphocytic leukemia research and paved the way for precision medicine approaches. In this review, we explore the role of machine learning in the analysis of multi-omics data in this hematological malignancy. We discuss recent literature on different machine learning models applied to single omic studies in chronic lymphocytic leukemia, with a special focus on the potential contributions to precision medicine. Finally, we highlight the recently published machine learning applications in multi-omics data in this area of research as well as their potential and limitations.

Integrative epigenomics in chronic lymphocytic leukaemia: Biological insights and clinical applications

Chronic lymphocytic leukaemia (CLL) is not only characterised by driver genetic alterations but by extensive epigenetic changes. Over the last decade, epigenomic studies have described the DNA methylome, chromatin accessibility, histone modifications and the three-dimensional (3D) genome architecture of CLL. Beyond its regulatory role, the DNA methylome contains imprints of the cellular origin and proliferative history of CLL cells. These two aspects are strong independent prognostic factors. Integrative analyses of chromatin marks have uncovered novel regulatory elements and altered transcription factor networks as non-genetic means mediating gene deregulation in CLL. Additionally, CLL cells display a disease-specific pattern of 3D genome interactions. From the technological perspective, we are currently witnessing a transition from bulk omics to single-cell analyses. This review aims at summarising the major findings from the epigenomics field as well as providing a prospect of the present and future of single-cell analyses in CLL.

Influence of Unequal Amplification of Methylated and Non-Methylated Template on Performance of Pyrosequencing

Pyrosequencing is one of the technologies widely used for quantitative methylation assessment. The protocol of pyrosequencing experiment consists of PCR amplification of a locus of interest and subsequent sequencing via synthesis of the amplified PCR product. As the PCR in this protocol utilizes one primer set for the amplification of a template originating from both methylated and non-methylated versions of the analysed locus, the unequal amplification of one of the templates may affect the methylation level assessment by pyrosequencing. We have investigated whether the unequal amplification of one of the templates challenges the quantitative properties of the pyrosequencing technology. Our results show that the sensitivity and dynamic range of pyrosequencing can be significantly affected by unequal amplification of the methylated and non-methylated version of the locus of interest in an assay specific manner. Thus, the assessment of the effect of unequal template amplification on the performances of the specific pyrosequencing assay is necessary before using the assay either in research or especially in diagnostic settings.

Towards precision medicine in lymphoid malignancies

Careful histopathologic examination remains the cornerstone in the diagnosis of the clinically and biologically heterogeneous group of lymphoid malignancies. However, recent advances in genomic and epigenomic characterization using high-throughput technologies have significantly improved our understanding of these tumors. Although no single genomic alteration is completely specific for a lymphoma entity, some alterations are highly recurrent in certain entities and thus can provide complementary diagnostic information when integrated in the hematopathological diagnostic workup. Moreover, other alterations may provide important information regarding the clinical course, that is, prognostic or risk-stratifying markers, or response to treatment, that is, predictive markers, which may allow tailoring of the patient's treatment based on (epi)genetic characteristics. In this review, we will focus on clinically relevant diagnostic, prognostic, and predictive biomarkers identified in more common types of B-cell malignancies, and discuss how diagnostic assays designed for comprehensive molecular profiling may pave the way for the implementation of precision diagnostics/medicine approaches. We will also discuss future directions in this rapidly evolving field, including the application of single-cell sequencing and other omics technologies, to decipher clonal dynamics and evolution in lymphoid malignancies.

IGHV-associated methylation signatures more accurately predict clinical outcomes of chronic lymphocytic leukemia patients than IGHV mutation load

Currently, no molecular biomarker indices are used in standard care to make treatment decisions at diagnosis of chronic lymphocytic leukemia (CLL). We used Infinium MethylationEPIC array data from diagnostic blood samples of 114 CLL patients and developed a procedure to stratify patients based on methylation signatures associated with mutation load of the IGHV gene. This procedure allowed us to predict the time to treatment with a hazard ratio (HR) of 8.34 (95% confidence interval [CI]: 4.54-15.30), as opposed to a HR of 4.35 (95% CI: 2.60-7.28) using IGHV mutation status. Detailed evaluation of 17 cases for which the two classification procedures gave discrepant results showed that these cases were incorrectly classified using IGHV status. Moreover, methylation-based classification stratified patients with different overall survival (HR=1.82; 95% CI: 1.07-3.09), which was not possible using IGHV status. Furthermore, we assessed the performance of the developed classification procedure using published HumanMethylation450 array data for 159 patients for whom information on time to treatment, overall survival and relapse was available. Despite 450K array methylation data not containing all the biomarkers used in our classification procedure, methylation signatures again stratified patients with significantly better accuracy than did IGHV mutation load regarding all available clinical outcomes. Thus, stratification using IGHV-associated methylation signatures may provide better prognostic power than IGHV mutation status.

Evaluation of a Prognostic Epigenetic Classification System in Chronic Lymphocytic Leukemia Patients

Background:

Methylation at 5 CpG sites was previously shown to classify chronic lymphocytic leukemia (CLL) into 3 prognostic subgroups. Here, we aimed to validate the marker set in an additional cohort and to evaluate its clinical utility for CLL patient stratification.

Methods:

We evaluated this epigenetic marker set in 79 German patients using bisulfite treatment followed by pyrosequencing and classification using a support vector machine-learning tool.

Results:

The n-CLL, i-CLL, and m-CLL classification was detected in 28 (35%), 10 (13%), and 41 (51%) patients, respectively. Epigenetic grouping was associated with IGHV mutational status ( P = 2 × 10−12), isolated del13q ( P = 9 × 10−6), del17p ( P = .015), complex karyotype ( P = .005), VH-usage, and clinical outcome as time to first treatment ( P = 1.4 × 10−12) and overall survival ( P = .003). Multivariate Cox regression analysis identified n-CLL as a factor for earlier treatment hazard ratio (HR), 6.3 (95% confidence interval [CI] 2.4-16.4; P = .0002) compared to IGHV mutational status (HR 4.6, 95% CI 1.9-11.3, P = .0008). In addition, when comparing the prognostic value of the epigenetic classification system with the IGHV classification, epigenetic grouping performed better compared to IGHV mutational status using Kaplan-Meier estimation and allowed the identification of a third, intermediate (i-CLL) group. Thus, our study confirmed the prognostic value of the epigenetic marker set for patient stratification in routine clinical diagnostics.

Altered DNA Methylation Profiles in SF3B1 Mutated CLL Patients

Mutations in splicing factor genes have a severe impact on the survival of cancer patients. Splicing factor 3b subunit 1 (SF3B1) is one of the most frequently mutated genes in chronic lymphocytic leukemia (CLL); patients carrying these mutations have a poor prognosis. Since the splicing machinery and the epigenome are closely interconnected, we investigated whether these alterations may affect the epigenomes of CLL patients. While an overall hypomethylation during CLL carcinogenesis has been observed, the interplay between the epigenetic stage of the originating B cells and SF3B1 mutations, and the subsequent effect of the mutations on methylation alterations in CLL, have not been investigated. We profiled the genome-wide DNA methylation patterns of 27 CLL patients with and without SF3B1 mutations and identified local decreases in methylation levels in SF3B1^mut CLL patients at 67 genomic regions, mostly in proximity to telomeric regions. These differentially methylated regions (DMRs) were enriched in gene bodies of cancer-related signaling genes, e.g., NOTCH1, HTRA3, and BCL9L. In our study, SF3B1 mutations exclusively emerged in two out of three epigenetic stages of the originating B cells. However, not all the DMRs could be associated with the methylation programming of B cells during development, suggesting that mutations in SF3B1 cause additional epigenetic aberrations during carcinogenesis.

Chromatin network markers of leukemia

MOTIVATION

The structure of chromatin impacts gene expression. Its alteration has been shown to coincide with the occurrence of cancer. A key challenge is in understanding the role of chromatin structure (CS) in cellular processes and its implications in diseases.

RESULTS

We propose a comparative pipeline to analyze CSs and apply it to study chronic lymphocytic leukemia (CLL). We model the chromatin of the affected and control cells as networks and analyze the network topology by state-of-the-art methods. Our results show that CSs are a rich source of new biological and functional information about DNA elements and cells that can complement protein-protein and co-expression data. Importantly, we show the existence of structural markers of cancer-related DNA elements in the chromatin. Surprisingly, CLL driver genes are characterized by specific local wiring patterns not only in the CS network of CLL cells, but also of healthy cells. This allows us to successfully predict new CLL-related DNA elements. Importantly, this shows that we can identify cancer-related DNA elements in other cancer types by investigating the CS network of the healthy cell of origin, a key new insight paving the road to new therapeutic strategies. This gives us an opportunity to exploit chromosome conformation data in healthy cells to predict new drivers.

AVAILABILITY AND IMPLEMENTATION

Our predicted CLL genes and RNAs are provided as a free resource to the community at https://life.bsc.es/iconbi/chromatin/index.html.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Genomic and Epigenomic Alterations in Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia is a common disease in Western countries and has heterogeneous clinical behavior. The relevance of the genetic basis of the disease has come to the forefront recently, with genome-wide studies that have provided a comprehensive view of structural variants, somatic mutations, and different layers of epigenetic changes. The mutational landscape is characterized by relatively common copy number alterations, a few mutated genes occurring in 10-15% of cases, and a large number of genes mutated in a small number of cases. The epigenomic profile has revealed a marked reprogramming of regulatory regions in tumor cells compared with normal B cells. All of these alterations are differentially distributed in clinical and biological subsets of the disease, indicating that they may underlie the heterogeneous evolution of the disease. These global studies are revealing the molecular complexity of chronic lymphocytic leukemia and provide new perspectives that have helped to understand its pathogenic mechanisms and improve the clinical management of patients.

Machine learning and clinical epigenetics: a review of challenges for diagnosis and classification

BACKGROUND

Machine learning is a sub-field of artificial intelligence, which utilises large data sets to make predictions for future events. Although most algorithms used in machine learning were developed as far back as the 1950s, the advent of big data in combination with dramatically increased computing power has spurred renewed interest in this technology over the last two decades.

MAIN BODY

Within the medical field, machine learning is promising in the development of assistive clinical tools for detection of e.g. cancers and prediction of disease. Recent advances in deep learning technologies, a sub-discipline of machine learning that requires less user input but more data and processing power, has provided even greater promise in assisting physicians to achieve accurate diagnoses. Within the fields of genetics and its sub-field epigenetics, both prime examples of complex data, machine learning methods are on the rise, as the field of personalised medicine is aiming for treatment of the individual based on their genetic and epigenetic profiles.

CONCLUSION

We now have an ever-growing number of reported epigenetic alterations in disease, and this offers a chance to increase sensitivity and specificity of future diagnostics and therapies. Currently, there are limited studies using machine learning applied to epigenetics. They pertain to a wide variety of disease states and have used mostly supervised machine learning methods.

Advances in Epigenetics and Epigenomics in Chronic Lymphocytic Leukemia

Purpose of Review

The development and progression of chronic lymphocytic leukemia (CLL), a highly heterogenous B cell malignancy, are influenced by both genetic and environmental factors. Environmental factors, including pharmacological interventions, can affect the epigenetic landscape of CLL and thereby determine the CLL phenotype, clonal evolution, and clinical outcome. In this review, we critically present the latest advances in the field of CLL epigenomics/epigenetics in order to provide a systematic overview of to-date achievements and highlight the potential of epigenomics approaches in light of novel treatment therapies.

Recent Findings

Recent technological advances have enabled broad and precise mapping of the CLL epigenome. The identification of CLL-specific DNA methylation patterns has allowed for accurate CLL subtype definition, a better understanding of clonal origin and evolution, and the discovery of reliable biomarkers. More recently, studies have started to unravel the prognostic, predictive, and therapeutic potential of mapping chromatin dynamics and histone modifications in CLL. Finally, analysis of non-coding RNA expression has indicated their contribution to disease pathogenesis and helped to define prognostic subsets in CLL.

Summary

Overall, the potential of CLL epigenomics for predicting treatment response and resistance is mounting, especially with the advent of novel targeted CLL therapies.

Clinical significance of DNA methylation in chronic lymphocytic leukemia patients: results from 3 UK clinical trials

Chronic lymphocytic leukemia patients with mutated immunoglobulin heavy-chain genes (IGHV-M), particularly those lacking poor-risk genomic lesions, often respond well to chemoimmunotherapy (CIT). DNA methylation profiling can subdivide early-stage patients into naive B-cell-like CLL (n-CLL), memory B-cell-like CLL (m-CLL), and intermediate CLL (i-CLL), with differing times to first treatment and overall survival. However, whether DNA methylation can identify patients destined to respond favorably to CIT has not been ascertained. We classified treatment-naive patients (n = 605) from 3 UK chemo and CIT clinical trials into the 3 epigenetic subgroups, using pyrosequencing and microarray analysis, and performed expansive survival analysis. The n-CLL, i-CLL, and m-CLL signatures were found in 80% (n = 245/305), 17% (53/305), and 2% (7/305) of IGHV-unmutated (IGHV-U) cases, respectively, and in 9%, (19/216), 50% (108/216), and 41% (89/216) of IGHV-M cases, respectively. Multivariate Cox proportional analysis identified m-CLL as an independent prognostic factor for overall survival (hazard ratio [HR], 0.46; 95% confidence interval [CI], 0.24-0.87; P = .018) in CLL4, and for progression-free survival (HR, 0.25; 95% CI, 0.10-0.57; P = .002) in ARCTIC and ADMIRE patients. The analysis of epigenetic subgroups in patients entered into 3 first-line UK CLL trials identifies m-CLL as an independent marker of prolonged survival and may aid in the identification of patients destined to demonstrate prolonged survival after CIT.

Developmental subtypes assessed by DNA methylation-iPLEX forecast the natural history of chronic lymphocytic leukemia

Alterations in global DNA methylation patterns are a major hallmark of cancer and represent attractive biomarkers for personalized risk stratification. Chronic lymphocytic leukemia (CLL) risk stratification studies typically focus on time to first treatment (TTFT), time to progression (TTP) after treatment, and overall survival (OS). Whereas TTFT risk stratification remains similar over time, TTP and OS have changed dramatically with the introduction of targeted therapies, such as the Bruton tyrosine kinase inhibitor ibrutinib. We have shown that genome-wide DNA methylation patterns in CLL are strongly associated with phenotypic differentiation and patient outcomes. Here, we developed a novel assay, termed methylation-iPLEX (Me-iPLEX), for high-throughput quantification of targeted panels of single cytosine guanine dinucleotides from multiple independent loci. Me-iPLEX was used to classify CLL samples into 1 of 3 known epigenetic subtypes (epitypes). We examined the impact of epitype in 1286 CLL patients from 4 independent cohorts representing a comprehensive view of CLL disease course and therapies. We found that epitype significantly predicted TTFT and OS among newly diagnosed CLL patients. Additionally, epitype predicted TTP and OS with 2 common CLL therapies: chemoimmunotherapy and ibrutinib. Epitype retained significance after stratifying by biologically related biomarkers, immunoglobulin heavy chain mutational status, and ZAP70 expression, as well as other common prognostic markers. Furthermore, among several biological traits enriched between epitypes, we found highly biased immunogenetic features, including IGLV3-21 usage in the poorly characterized intermediate-programmed CLL epitype. In summary, Me-iPLEX is an elegant method to assess epigenetic signatures, including robust classification of CLL epitypes that independently stratify patient risk at diagnosis and time of treatment.

Chronic lymphocytic leukemia and mantle cell lymphoma: crossroads of genetic and microenvironment interactions

Chronic lymphocytic leukemia (CLL) and mantle cell lymphoma (MCL) are 2 well-defined entities that diverge in their basic pathogenic mechanisms and clinical evolution but they share epidemiological characteristics, cells of origin, molecular alterations, and clinical features that differ from other lymphoid neoplasms. CLL and MCL are classically considered indolent and aggressive neoplasms, respectively. However, the clinical evolution of both tumors is very heterogeneous, with subsets of patients having stable disease for a long time whereas others require immediate intervention. Both CLL and MCL include 2 major molecular subtypes that seem to derive from antigen-experienced CD5⁺ B cells that retain a naive or memory-like epigenetic signature and carry a variable load of immunoglobulin heavy-chain variable region somatic mutations from truly unmutated to highly mutated, respectively. These 2 subtypes of tumors differ in their molecular pathways, genomic alterations, and clinical behavior, being more aggressive in naive-like than memory-like-derived tumors in both CLL and MCL. The pathogenesis of the 2 entities integrates the relevant influence of B-cell receptor signaling, tumor cell microenvironment interactions, genomic alterations, and epigenome modifications that configure the evolution of the tumors and offer new possibilities for therapeutic intervention. This review will focus on the similarities and differences of these 2 tumors based on recent studies that are enhancing the understanding of their pathogenesis and creating solid bases for new management strategies.

Epigenetic deregulation in chronic lymphocytic leukemia: Clinical and biological impact

Deregulated transcriptional control caused by aberrant DNA methylation and/or histone modifications is a hallmark of cancer cells. In chronic lymphocytic leukemia (CLL), the most common adult leukemia, the epigenetic 'landscape' has added a new layer of complexity to our understanding of this clinically and biologically heterogeneous disease. Early studies identified aberrant DNA methylation, often based on single gene promoter analysis with both biological and clinical impact. Subsequent genome-wide profiling studies revealed differential DNA methylation between CLLs and controls and in prognostics subgroups of the disease. From these studies, it became apparent that DNA methylation in regions outside of promoters, such as enhancers, is important for the regulation of coding genes as well as for the regulation of non-coding RNAs. Although DNA methylation profiles are reportedly stable over time and in relation to therapy, a higher epigenetic heterogeneity or 'burden' is seen in more aggressive CLL subgroups, albeit as non-recurrent 'passenger' events. More recently, DNA methylation profiles in CLL analyzed in relation to differentiating normal B-cell populations revealed that the majority of the CLL epigenome reflects the epigenomes present in the cell of origin and that only a small fraction of the epigenetic alterations represents truly CLL-specific changes. Furthermore, CLL patients can be grouped into at least three clinically relevant epigenetic subgroups, potentially originating from different cells at various stages of differentiation and associated with distinct outcomes. In this review, we summarize the current understanding of the DNA methylome in CLL, the role of histone modifying enzymes, highlight insights derived from animal models and attempts made to target epigenetic regulators in CLL along with the future directions of this rapidly advancing field.

Charting the dynamic epigenome during B-cell development

The epigenetic landscape undergoes a widespread modulation during embryonic development and cell differentiation. Within the hematopoietic system, B cells are perhaps the cell lineage with a more dynamic DNA methylome during their maturation process, which involves approximately one third of all the CpG sites of the genome. Although each B-cell maturation step displays its own DNA methylation fingerprint, the DNA methylome is more extensively modified in particular maturation transitions. These changes are gradually accumulated in specific chromatin environments as cell differentiation progresses and reflect different features and functional states of B cells. Promoters and enhancers of B-cell transcription factors acquire activation-related epigenetic marks and are sequentially expressed in particular maturation windows. These transcription factors further reconfigure the epigenetic marks and activity state of their target sites to regulate the expression of genes related to B-cell functions. Together with this observation, extensive DNA methylation changes in areas outside gene regulatory elements such as hypomethylation of heterochromatic regions and hypermethylation of CpG-rich regions, also take place in mature B cells, which intriguingly have been described as hallmarks of cancer. This process starts in germinal center B cells, a highly proliferative cell type, and becomes particularly apparent in long-lived cells such as memory and plasma cells. Overall, the characterization of the DNA methylome during B-cell differentiation not only provides insights into the complex epigenetic network of regulatory elements that mediate the maturation process but also suggests that late B cells also passively accumulate epigenetic changes related to cell proliferation and longevity.

Chronic lymphocytic leukaemia

Chronic lymphocytic leukaemia (CLL) is a malignancy of CD5+ B cells that is characterized by the accumulation of small, mature-appearing lymphocytes in the blood, marrow and lymphoid tissues. Signalling via surface immunoglobulin, which constitutes the major part of the B cell receptor, and several genetic alterations play a part in CLL pathogenesis, in addition to interactions between CLL cells and other cell types, such as stromal cells, T cells and nurse-like cells in the lymph nodes. The clinical progression of CLL is heterogeneous and ranges from patients who require treatment soon after diagnosis to others who do not require therapy for many years, if at all. Several factors, including the immunoglobulin heavy-chain variable region gene (IGHV) mutational status, genomic changes, patient age and the presence of comorbidities, should be considered when defining the optimal management strategies, which include chemotherapy, chemoimmunotherapy and/or drugs targeting B cell receptor signalling or inhibitors of apoptosis, such as BCL-2. Research on the biology of CLL has profoundly enhanced our ability to identify patients who are at higher risk for disease progression and our capacity to treat patients with drugs that selectively target distinctive phenotypic or physiological features of CLL. How these and other advances have shaped our current understanding and treatment of patients with CLL is the subject of this Primer.

Decoding the DNA Methylome of Mantle Cell Lymphoma in the Light of the Entire B Cell Lineage

We analyzed the in silico purified DNA methylation signatures of 82 mantle cell lymphomas (MCL) in comparison with cell subpopulations spanning the entire B cell lineage. We identified two MCL subgroups, respectively carrying epigenetic imprints of germinal-center-inexperienced and germinal-center-experienced B cells, and we found that DNA methylation profiles during lymphomagenesis are largely influenced by the methylation dynamics in normal B cells. An integrative epigenomic approach revealed 10,504 differentially methylated regions in regulatory elements marked by H3K27ac in MCL primary cases, including a distant enhancer showing de novo looping to the MCL oncogene SOX11. Finally, we observed that the magnitude of DNA methylation changes per case is highly variable and serves as an independent prognostic factor for MCL outcome.