Modulation of tumor microenvironment by targeting histone acetylation in bladder cancer.

Alterations in the epigenetic machinery in both tumor and immune cells contribute to bladder cancer (BC) development, constituting a promising target as an alternative therapeutic option. Here, we have explored the effects of a novel histone deacetylase (HDAC) inhibitor CM-1758, alone or in combination with immune checkpoint inhibitors (ICI) in BC. We determined the antitumor effects of CM-1758 in various BC cell lines together with the induction of broad transcriptional changes, with focus on the epigenetic regulation of PD-L1. Using an immunocompetent syngeneic mouse model of metastatic BC, we studied the effects of CM-1758 alone or in combination with anti-PD-L1 not only on tumor cells, but also in the tumor microenvironment. In vitro, we found that CM-1758 has cytotoxic and cytostatic effects either by inducing apoptosis or cell cycle arrest in BC cells at low micromolar levels. PD-L1 is epigenetically regulated by histone acetylation marks and is induced after treatment with CM-1758. We also observed that treatment with CM-1758 led to an important delay in tumor growth and a higher CD8 + T cell tumor infiltration. Moreover, anti-PD-L1 alone or in combination with CM-1758 reprogramed macrophage differentiation towards a M1-like polarization state and increased of pro-inflammatory cytokines systemically, yielding potential further antitumor effects. Our results suggest the possibility of combining HDAC inhibitors with immunotherapies for the management of advanced metastatic BC.

Explainable artificial intelligence for precision medicine in acute myeloid leukemia.

Artificial intelligence (AI) can unveil novel personalized treatments based on drug screening and whole-exome sequencing experiments (WES). However, the concept of "black box" in AI limits the potential of this approach to be translated into the clinical practice. In contrast, explainable AI (XAI) focuses on making AI results understandable to humans. Here, we present a novel XAI method -called multi-dimensional module optimization (MOM)- that associates drug screening with genetic events, while guaranteeing that predictions are interpretable and robust. We applied MOM to an acute myeloid leukemia (AML) cohort of 319 ex-vivo tumor samples with 122 screened drugs and WES. MOM returned a therapeutic strategy based on the FLT3, CBFß-MYH11, and NRAS status, which predicted AML patient response to Quizartinib, Trametinib, Selumetinib, and Crizotinib. We successfully validated the results in three different large-scale screening experiments. We believe that XAI will help healthcare providers and drug regulators better understand AI medical decisions.

Identifying Lethal Dependencies with HUGE Predictive Power.

Recent functional genomic screens­such as CRISPR-Cas9 or RNAi screening­have fostered a new wave of targeted treatments based on the concept of synthetic lethality. These approaches identified LEthal Dependencies (LEDs) by estimating the effect of genetic events on cell viability. The multiple-hypothesis problem is related to a large number of gene knockouts limiting the statistical power of these studies. Here, we show that predictions of LEDs from functional screens can be dramatically improved by incorporating the "HUb effect in Genetic Essentiality" (HUGE) of gene alterations. We analyze three recent genome-wide loss-of-function screens­Project Score, CERES score and DEMETER score­identifying LEDs with 75 times larger statistical power than using state-of-the-art methods. Using acute myeloid leukemia, breast cancer, lung adenocarcinoma and colon adenocarcinoma as disease models, we validate that our predictions are enriched in a recent harmonized knowledge base of clinical interpretations of somatic genomic variants in cancer (AUROC > 0.87). Our approach is effective even in tumors with large genetic heterogeneity such as acute myeloid leukemia, where we identified LEDs not recalled by previous pipelines, including FLT3-mutant genotypes sensitive to FLT3 inhibitors. Interestingly, in-vitro validations confirm lethal dependencies of either NRAS or PTPN11 depending on the NRAS mutational status. HUGE will hopefully help discover novel genetic dependencies amenable for precision-targeted therapies in cancer. All the graphs showing lethal dependencies for the 19 tumor types analyzed can be visualized in an interactive tool.

Inhibiting Histone and DNA Methylation Improves Cancer Vaccination in an Experimental Model of Melanoma.

Immunotherapy has improved the treatment of malignant skin cancer of the melanoma type, yet overall clinical response rates remain low. Combination therapies could be key to meet this cogent medical need. Because epigenetic hallmarks represent promising combination therapy targets, we studied the immunogenic potential of a dual inhibitor of histone methyltransferase G9a and DNA methyltransferases (DNMTs) in the preclinical B16-OVA melanoma model. Making use of tumor transcriptomic and functional analyses, methylation-targeted epigenetic reprogramming was shown to induce tumor cell cycle arrest and apoptosis in vitro coinciding with transient tumor growth delay and an IFN-I response in immune-competent mice. In consideration of a potential impact on immune cells, the drug was shown not to interfere with dendritic cell maturation or T-cell activation in vitro. Notably, the drug promoted dendritic cell and, to a lesser extent, T-cell infiltration in vivo, yet failed to sensitize tumor cells to programmed cell death-1 inhibition. Instead, it increased therapeutic efficacy of TCR-redirected T cell and dendritic cell vaccination, jointly increasing overall survival of B16-OVA tumor-bearing mice. The reported data confirm the prospect of methylation-targeted epigenetic reprogramming in melanoma and sustain dual G9a and DNMT inhibition as a strategy to tip the cancer-immune set-point towards responsiveness to active and adoptive vaccination against melanoma.

BOSO: A novel feature selection algorithm for linear regression with high-dimensional data.

With the frenetic growth of high-dimensional datasets in different biomedical domains, there is an urgent need to develop predictive methods able to deal with this complexity. Feature selection is a relevant strategy in machine learning to address this challenge. We introduce a novel feature selection algorithm for linear regression called BOSO (Bilevel Optimization Selector Operator). We conducted a benchmark of BOSO with key algorithms in the literature, finding a superior accuracy for feature selection in high-dimensional datasets. Proof-of-concept of BOSO for predicting drug sensitivity in cancer is presented. A detailed analysis is carried out for methotrexate, a well-studied drug targeting cancer metabolism.

A network-based approach to integrate nutrient microenvironment in the prediction of synthetic lethality in cancer metabolism.

Synthetic Lethality (SL) is currently defined as a type of genetic interaction in which the loss of function of either of two genes individually has limited effect in cell viability but inactivation of both genes simultaneously leads to cell death. Given the profound genomic aberrations acquired by tumor cells, which can be systematically identified with -omics data, SL is a promising concept in cancer research. In particular, SL has received much attention in the area of cancer metabolism, due to the fact that relevant functional alterations concentrate on key metabolic pathways that promote cellular proliferation. With the extensive prior knowledge about human metabolic networks, a number of computational methods have been developed to predict SL in cancer metabolism, including the genetic Minimal Cut Sets (gMCSs) approach. A major challenge in the application of SL approaches to cancer metabolism is to systematically integrate tumor microenvironment, given that genetic interactions and nutritional availability are interconnected to support proliferation. Here, we propose a more general definition of SL for cancer metabolism that combines genetic and environmental interactions, namely loss of gene functions and absence of nutrients in the environment. We extend our gMCSs approach to determine this new family of metabolic synthetic lethal interactions. A computational and experimental proof-of-concept is presented for predicting the lethality of dihydrofolate reductase (DHFR) inhibition in different environments. Finally, our approach is applied to identify extracellular nutrient dependences of tumor cells, elucidating cholesterol and myo-inositol depletion as potential vulnerabilities in different malignancies.

Design and Synthesis of Novel Epigenetic Inhibitors Targeting Histone Deacetylases, DNA Methyltransferase 1, and Lysine Methyltransferase G9a with In Vivo Efficacy in Multiple Myeloma.

Concomitant inhibition of key epigenetic pathways involved in silencing tumor suppressor genes has been recognized as a promising strategy for cancer therapy. Herein, we report a first-in-class series of quinoline-based analogues that simultaneously inhibit histone deacetylases (from a low nanomolar range) and DNA methyltransferase-1 (from a mid-nanomolar range, IC50 < 200 nM). Additionally, lysine methyltransferase G9a inhibitory activity is achieved (from a low nanomolar range) by introduction of a key lysine mimic group at the 7-position of the quinoline ring. The corresponding epigenetic functional cellular responses are observed: histone-3 acetylation, DNA hypomethylation, and decreased histone-3 methylation at lysine-9. These chemical probes, multitarget epigenetic inhibitors, were validated against the multiple myeloma cell line MM1.S, demonstrating promising in vitro activity of 12a (CM-444) with GI50 of 32 nM, an adequate therapeutic window (>1 log unit), and a suitable pharmacokinetic profile. In vivo, 12a achieved significant antitumor efficacy in a xenograft mouse model of human multiple myeloma.

Targeting aberrant DNA methylation in mesenchymal stromal cells as a treatment for myeloma bone disease.

Multiple myeloma (MM) progression and myeloma-associated bone disease (MBD) are highly dependent on bone marrow mesenchymal stromal cells (MSCs). MM-MSCs exhibit abnormal transcriptomes, suggesting the involvement of epigenetic mechanisms governing their tumor-promoting functions and prolonged osteoblast suppression. Here, we identify widespread DNA methylation alterations of bone marrow-isolated MSCs from distinct MM stages, particularly in Homeobox genes involved in osteogenic differentiation that associate with their aberrant expression. Moreover, these DNA methylation changes are recapitulated in vitro by exposing MSCs from healthy individuals to MM cells. Pharmacological targeting of DNMTs and G9a with dual inhibitor CM-272 reverts the expression of hypermethylated osteogenic regulators and promotes osteoblast differentiation of myeloma MSCs. Most importantly, CM-272 treatment prevents tumor-associated bone loss and reduces tumor burden in a murine myeloma model. Our results demonstrate that epigenetic aberrancies mediate the impairment of bone formation in MM, and its targeting by CM-272 is able to reverse MBD.

Chromatin activation as a unifying principle underlying pathogenic mechanisms in multiple myeloma.

Multiple myeloma (MM) is a plasma cell neoplasm associated with a broad variety of genetic lesions. In spite of this genetic heterogeneity, MMs share a characteristic malignant phenotype whose underlying molecular basis remains poorly characterized. In the present study, we examined plasma cells from MM using a multi-epigenomics approach and demonstrated that, when compared to normal B cells, malignant plasma cells showed an extensive activation of regulatory elements, in part affecting coregulated adjacent genes. Among target genes up-regulated by this process, we found members of the NOTCH, NF-kB, MTOR signaling, and TP53 signaling pathways. Other activated genes included sets involved in osteoblast differentiation and response to oxidative stress, all of which have been shown to be associated with the MM phenotype and clinical behavior. We functionally characterized MM-specific active distant enhancers controlling the expression of thioredoxin (TXN), a major regulator of cellular redox status and, in addition, identified PRDM5 as a novel essential gene for MM. Collectively, our data indicate that aberrant chromatin activation is a unifying feature underlying the malignant plasma cell phenotype.

Immunogenomic identification and characterization of granulocytic myeloid-derived suppressor cells in multiple myeloma.

Granulocytic myeloid-derived suppressor cells (G-MDSCs) promote tumor growth and immunosuppression in multiple myeloma (MM). However, their phenotype is not well established for accurate monitoring or clinical translation. We aimed to provide the phenotypic profile of G-MDSCs based on their prognostic significance in MM, immunosuppressive potential, and molecular program. The preestablished phenotype of G-MDSCs was evaluated in bone marrow samples from controls and MM patients using multidimensional flow cytometry; surprisingly, we found that CD11b+CD14-CD15+CD33+HLADR- cells overlapped with common eosinophils and neutrophils, which were not expanded in MM patients. Therefore, we relied on automated clustering to unbiasedly identify all granulocytic subsets in the tumor microenvironment: basophils, eosinophils, and immature, intermediate, and mature neutrophils. In a series of 267 newly diagnosed MM patients (GEM2012MENOS65 trial), only the frequency of mature neutrophils at diagnosis was significantly associated with patient outcome, and a high mature neutrophil/T-cell ratio resulted in inferior progression-free survival (P < .001). Upon fluorescence-activated cell sorting of each neutrophil subset, T-cell proliferation decreased in the presence of mature neutrophils (0.5-fold; P = .016), and the cytotoxic potential of T cells engaged by a BCMA×CD3-bispecific antibody increased notably with the depletion of mature neutrophils (fourfold; P = .0007). Most interestingly, RNA sequencing of the 3 subsets revealed that G-MDSC-related genes were specifically upregulated in mature neutrophils from MM patients vs controls because of differential chromatin accessibility. Taken together, our results establish a correlation between the clinical significance, immunosuppressive potential, and transcriptional network of well-defined neutrophil subsets, providing for the first time a set of optimal markers (CD11b/CD13/CD16) for accurate monitoring of G-MDSCs in MM.

HDAC Inhibitors in Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a hematological malignancy characterized by uncontrolled proliferation, differentiation arrest, and accumulation of immature myeloid progenitors. Although clinical advances in AML have been made, especially in young patients, long-term disease-free survival remains poor, making this disease an unmet therapeutic challenge. Epigenetic alterations and mutations in epigenetic regulators contribute to the pathogenesis of AML, supporting the rationale for the use of epigenetic drugs in patients with AML. While hypomethylating agents have already been approved in AML, the use of other epigenetic inhibitors, such as histone deacetylases (HDAC) inhibitors (HDACi), is under clinical development. HDACi such as Panobinostat, Vorinostat, and Tricostatin A have been shown to promote cell death, autophagy, apoptosis, or growth arrest in preclinical AML models, yet these inhibitors do not seem to be effective as monotherapies, but rather in combination with other drugs. In this review, we discuss the rationale for the use of different HDACi in patients with AML, the results of preclinical studies, and the results obtained in clinical trials. Although so far the results with HDACi in clinical trials in AML have been modest, there are some encouraging data from treatment with the HDACi Pracinostat in combination with DNA demethylating agents.

Inhibition of a G9a/DNMT network triggers immune-mediated bladder cancer regression.

Bladder cancer is lethal in its advanced, muscle-invasive phase with very limited therapeutic advances1,2. Recent molecular characterization has defined new (epi)genetic drivers and potential targets for bladder cancer3,4. The immune checkpoint inhibitors have shown remarkable efficacy but only in a limited fraction of bladder cancer patients5-8. Here, we show that high G9a (EHMT2) expression is associated with poor clinical outcome in bladder cancer and that targeting G9a/DNMT methyltransferase activity with a novel inhibitor (CM-272) induces apoptosis and immunogenic cell death. Using an immunocompetent quadruple-knockout (PtenloxP/loxP; Trp53loxP/loxP; Rb1loxP/loxP; Rbl1-/-) transgenic mouse model of aggressive metastatic, muscle-invasive bladder cancer, we demonstrate that CM-272 + cisplatin treatment results in statistically significant regression of established tumors and metastases. The antitumor effect is significantly improved when CM-272 is combined with anti-programmed cell death ligand 1, even in the absence of cisplatin. These effects are associated with an endogenous antitumor immune response and immunogenic cell death with the conversion of a cold immune tumor into a hot tumor. Finally, increased G9a expression was associated with resistance to programmed cell death protein 1 inhibition in a cohort of patients with bladder cancer. In summary, these findings support new and promising opportunities for the treatment of bladder cancer using a combination of epigenetic inhibitors and immune checkpoint blockade.

Dual Targeting of Histone Methyltransferase G9a and DNA-Methyltransferase 1 for the Treatment of Experimental Hepatocellular Carcinoma.

Epigenetic modifications such as DNA and histone methylation functionally cooperate in fostering tumor growth, including that of hepatocellular carcinoma (HCC). Pharmacological targeting of these mechanisms may open new therapeutic avenues. We aimed to determine the therapeutic efficacy and potential mechanism of action of our dual G9a histone-methyltransferase and DNA-methyltransferase 1 (DNMT1) inhibitor in human HCC cells and their crosstalk with fibrogenic cells. The expression of G9a and DNMT1, along with that of their molecular adaptor ubiquitin-like with PHD and RING finger domains-1 (UHRF1), was measured in human HCCs (n = 268), peritumoral tissues (n = 154), and HCC cell lines (n = 32). We evaluated the effect of individual and combined inhibition of G9a and DNMT1 on HCC cell growth by pharmacological and genetic approaches. The activity of our lead compound, CM-272, was examined in HCC cells under normoxia and hypoxia, human hepatic stellate cells and LX2 cells, and xenograft tumors formed by HCC or combined HCC+LX2 cells. We found a significant and correlative overexpression of G9a, DNMT1, and UHRF1 in HCCs in association with poor prognosis. Independent G9a and DNMT1 pharmacological targeting synergistically inhibited HCC cell growth. CM-272 potently reduced HCC and LX2 cells proliferation and quelled tumor growth, particularly in HCC+LX2 xenografts. Mechanistically, CM-272 inhibited the metabolic adaptation of HCC cells to hypoxia and induced a differentiated phenotype in HCC and fibrogenic cells. The expression of the metabolic tumor suppressor gene fructose-1,6-bisphosphatase (FBP1), epigenetically repressed in HCC, was restored by CM-272. Conclusion: Combined targeting of G9a/DNMT1 with compounds such as CM-272 is a promising strategy for HCC treatment. Our findings also underscore the potential of differentiation therapy in HCC.

Discovery of Reversible DNA Methyltransferase and Lysine Methyltransferase G9a Inhibitors with Antitumoral in Vivo Efficacy.

Using knowledge- and structure-based approaches, we designed and synthesized reversible chemical probes that simultaneously inhibit the activity of two epigenetic targets, histone 3 lysine 9 methyltransferase (G9a) and DNA methyltransferases (DNMT), at nanomolar ranges. Enzymatic competition assays confirmed our design strategy: substrate competitive inhibitors. Next, an initial exploration around our hit 11 was pursued to identify an adequate tool compound for in vivo testing. In vitro treatment of different hematological neoplasia cell lines led to the identification of molecules with clear antiproliferative efficacies (GI50 values in the nanomolar range). On the basis of epigenetic functional cellular responses (levels of lysine 9 methylation and 5-methylcytosine), an acceptable therapeutic window (around 1 log unit) and a suitable pharmacokinetic profile, 12 was selected for in vivo proof-of-concept ( Nat. Commun. 2017 , 8 , 15424 ). Herein, 12 achieved a significant in vivo efficacy: 70% overall tumor growth inhibition of a human acute myeloid leukemia (AML) xenograft in a mouse model.

Detailed Exploration around 4-Aminoquinolines Chemical Space to Navigate the Lysine Methyltransferase G9a and DNA Methyltransferase Biological Spaces.

Epigenetic regulators that exhibit aberrant enzymatic activities or expression profiles are potential therapeutic targets for cancers. Specifically, enzymes responsible for methylation at histone-3 lysine-9 (like G9a) and aberrant DNA hypermethylation (DNMTs) have been implicated in a number of cancers. Recently, molecules bearing a 4-aminoquinoline scaffold were reported as dual inhibitors of these targets and showed a significant in vivo efficacy in animal models of hematological malignancies. Here, we report a detailed exploration around three growing vectors born by this chemotype. Exploring this chemical space led to the identification of features to navigate G9a and DNMT1 biological spaces: not only their corresponding exclusive areas, selective compounds, but also common spaces. Thus, we identified from selective G9a and first-in-class DNMT1 inhibitors, >1 log unit between their IC50 values, with IC50 < 25 nM (e.g., 43 and 26, respectively) to equipotent inhibitors with IC50 < 50 nM for both targets (e.g., 13). Their ADME/Tox profiling and antiproliferative efficacies, versus some cancer cell lines, are also reported.

Reversible dual inhibitor against G9a and DNMT1 improves human iPSC derivation enhancing MET and facilitating transcription factor engagement to the genome.

The combination of defined factors with small molecules targeting epigenetic factors is a strategy that has been shown to enhance optimal derivation of iPSCs and could be used for disease modelling, high throughput screenings and/or regenerative medicine applications. In this study, we showed that a new first-in-class reversible dual G9a/DNMT1 inhibitor compound (CM272) improves the efficiency of human cell reprogramming and iPSC generation from primary cells of healthy donors and patient samples, using both integrative and non-integrative methods. Moreover, CM272 facilitates the generation of human iPSC with only two factors allowing the removal of the most potent oncogenic factor cMYC. Furthermore, we demonstrated that mechanistically, treatment with CM272 induces heterochromatin relaxation, facilitates the engagement of OCT4 and SOX2 transcription factors to OSKM refractory binding regions that are required for iPSC establishment, and enhances mesenchymal to epithelial transition during the early phase of cell reprogramming. Thus, the use of this new G9a/DNMT reversible dual inhibitor compound may represent an interesting alternative for improving cell reprogramming and human iPSC derivation for many different applications while providing interesting insights into reprogramming mechanisms.

In-silico gene essentiality analysis of polyamine biosynthesis reveals APRT as a potential target in cancer.

Constraint-based modeling for genome-scale metabolic networks has emerged in the last years as a promising approach to elucidate drug targets in cancer. Beyond the canonical biosynthetic routes to produce biomass, it is of key importance to focus on metabolic routes that sustain the proliferative capacity through the regulation of other biological means in order to improve in-silico gene essentiality analyses. Polyamines are polycations with central roles in cancer cell proliferation, through the regulation of transcription and translation among other things, but are typically neglected in in silico cancer metabolic models. In this study, we analysed essential genes for the biosynthesis of polyamines. Our analysis corroborates the importance of previously known regulators of the pathway, such as Adenosylmethionine Decarboxylase 1 (AMD1) and uncovers novel enzymes predicted to be relevant for polyamine homeostasis. We focused on Adenine Phosphoribosyltransferase (APRT) and demonstrated the detrimental consequence of APRT gene silencing on different leukaemia cell lines. Our results highlight the importance of revisiting the metabolic models used for in-silico gene essentiality analyses in order to maximize the potential for drug target identification in cancer.

An in-silico approach to predict and exploit synthetic lethality in cancer metabolism.

Synthetic lethality is a promising concept in cancer research, potentially opening new possibilities for the development of more effective and selective treatments. Here, we present a computational method to predict and exploit synthetic lethality in cancer metabolism. Our approach relies on the concept of genetic minimal cut sets and gene expression data, demonstrating a superior performance to previous approaches predicting metabolic vulnerabilities in cancer. Our genetic minimal cut set computational framework is applied to evaluate the lethality of ribonucleotide reductase catalytic subunit M1 (RRM1) inhibition in multiple myeloma. We present a computational and experimental study of the effect of RRM1 inhibition in four multiple myeloma cell lines. In addition, using publicly available genome-scale loss-of-function screens, a possible mechanism by which the inhibition of RRM1 is effective in cancer is established. Overall, our approach shows promising results and lays the foundation to build a novel family of algorithms to target metabolism in cancer.Exploiting synthetic lethality is a promising approach for cancer therapy. Here, the authors present an approach to identifying such interactions by finding genetic minimal cut sets (gMCSs) that block cancer proliferation, and apply it to study the lethality of RRM1 inhibition in multiple myeloma.

Discovery of first-in-class reversible dual small molecule inhibitors against G9a and DNMTs in hematological malignancies.

The indisputable role of epigenetics in cancer and the fact that epigenetic alterations can be reversed have favoured development of epigenetic drugs. In this study, we design and synthesize potent novel, selective and reversible chemical probes that simultaneously inhibit the G9a and DNMTs methyltransferase activity. In vitro treatment of haematological neoplasia (acute myeloid leukaemia-AML, acute lymphoblastic leukaemia-ALL and diffuse large B-cell lymphoma-DLBCL) with the lead compound CM-272, inhibits cell proliferation and promotes apoptosis, inducing interferon-stimulated genes and immunogenic cell death. CM-272 significantly prolongs survival of AML, ALL and DLBCL xenogeneic models. Our results represent the discovery of first-in-class dual inhibitors of G9a/DNMTs and establish this chemical series as a promising therapeutic tool for unmet needs in haematological tumours.

Whole-epigenome analysis in multiple myeloma reveals DNA hypermethylation of B cell-specific enhancers.

While analyzing the DNA methylome of multiple myeloma (MM), a plasma cell neoplasm, by whole-genome bisulfite sequencing and high-density arrays, we observed a highly heterogeneous pattern globally characterized by regional DNA hypermethylation embedded in extensive hypomethylation. In contrast to the widely reported DNA hypermethylation of promoter-associated CpG islands (CGIs) in cancer, hypermethylated sites in MM, as opposed to normal plasma cells, were located outside CpG islands and were unexpectedly associated with intronic enhancer regions defined in normal B cells and plasma cells. Both RNA-seq and in vitro reporter assays indicated that enhancer hypermethylation is globally associated with down-regulation of its host genes. ChIP-seq and DNase-seq further revealed that DNA hypermethylation in these regions is related to enhancer decommissioning. Hypermethylated enhancer regions overlapped with binding sites of B cell-specific transcription factors (TFs) and the degree of enhancer methylation inversely correlated with expression levels of these TFs in MM. Furthermore, hypermethylated regions in MM were methylated in stem cells and gradually became demethylated during normal B-cell differentiation, suggesting that MM cells either reacquire epigenetic features of undifferentiated cells or maintain an epigenetic signature of a putative myeloma stem cell progenitor. Overall, we have identified DNA hypermethylation of developmentally regulated enhancers as a new type of epigenetic modification associated with the pathogenesis of MM.