Abbreviations
bone marrow mesenchymal stromal cells
cis ‐regulatory element
Elotuzumab in combination with pomalidomide, bortezomib and dexamethasone
gene regulatory network
histone deacetylase
histone deacetylase inhibitors
human myeloma cell line
immunoglobulin heavy chain
immunomodulatory drug
monoclonal gammopathy of undetermined significance
multiple myeloma
plasma cell
plasmacytoid dendritic cells
proteasome inhibitor
smouldering myeloma
transcription factor
tumour microenvironment
INTRODUCTION
Multiple myeloma (MM) is the second most common haematological malignancy and is characterised by the clonal expansion of abnormal plasma cells (PCs) in the bone marrow. Technological advancement over the past three decades has greatly expanded the arsenal of available anti‐myeloma therapies, from alkylating chemotherapy, corticosteroids and autologous stem cell transplantation to immunomodulatory drugs (IMiDs) and proteasome inhibitors (PIs), and more recently monoclonal antibodies, bi‐specific T cell engagers and CAR‐T cells. 1 , 2 Collectively, these treatments combined with better supportive care have progressively increased the duration and quality of life of people who have been diagnosed with myeloma. Notwithstanding the improved outlook, management of high‐risk disease still remains a major challenge, and most MM patients undergo several rounds of relapse, eventually exhausting all available therapeutic options. 1 Thus, there is an unmet need for increased knowledge of myeloma biology and new agents that complement existing treatments.
The natural history of myeloma follows a well‐defined multi‐step process, beginning with the asymptomatic precursor state monoclonal gammopathy of undetermined significance (MGUS) and progressing to ever more proliferative and clinically aggressive states: smouldering myeloma (SMM), MM, and in some cases extramedullary disease or plasma cell leukaemia. 3 , 4 The genetic evolution of myeloma cells that drives this progression has been extensively characterised by large‐scale genome sequencing studies. 5 , 6 , 7 , 8 , 9 Briefly, amplification of certain odd‐numbered chromosomes (referred to as hyperdiploidy), or chromosomal translocations that bring myeloma oncogenes (most commonly CCND1 , CCND3 , MAF , MAFB or NSD2 ) under the control of the immunoglobulin heavy chain ( IGH ) enhancer occur in a mutually exclusive manner and initiate the outgrowth of a PC clone. Subsequent translocations, copy number alterations and point mutations dysregulate various pathways important for PC proliferation and genomic integrity (Tp53, MAPK, NFκB among others), producing a compendium of sub‐clones with increasing fitness and capacity to evade immune control. The genetic changes in MM have been reviewed extensively elsewhere 3 , 4 and we do not discuss them in detail here. Instead, we focus on epigenetic alterations which work side by side with changes that alter the DNA sequence to shape the phenotype and fate of MM cells. In the first section, we outline how chromatin remodelling contributes to myelomagenesis and therapy resistance by modifying gene expression networks. In the second section, we discuss the possibility of deploying epigenetic drugs in MM, a strategy that is not currently utilised and which has the capacity to synergize with existing modalities to overcome drug resistance.
EPIGENETIC DYSREGULATION DURING MM EVOLUTION
Epigenetic regulation encompasses an array of processes that occur throughout the hierarchy of genomic organisation, from covalent modifications of histones and DNA to the spatial organisation of chromatin, that collectively influence DNA accessibility and gene expression. Like the DNA sequence of a cell, the epigenetic state is heritable and transmitted from mother cells to daughter cells during cell division, enabling epigenetically encoded advantageous traits to be selected through Darwinian evolution. It is now apparent that a large proportion of the phenotypic heterogeneity that is observed in cancer is attributable to epigenetic rather than genetic variation. 10 , 11 Importantly, however, and in contrast to the genome, the epigenome is malleable and can be altered in response to specific stimuli. This property, commonly referred to as plasticity, facilitates cell state transitions and rapid adaptation to changing environmental conditions. 12 , 13 , 14
At the molecular level, the epigenome is controlled by so‐called ‘writer’, ‘reader’ and ‘eraser’ proteins, which function in concert with sequence‐specific transcription factors (TFs) to lay down, interpret and remove the epigenetic state of defined regions of the genome. Epigenetic dysregulation in malignant cells can occur via mutations of key epigenetic regulators, resulting in aberrant self‐renewal and a block of differentiation as commonly seen in tumours. 15 , 16 Additionally, many other pathways can drive an altered epigenetic state including growth factor signalling and nutrient availability, which play a critical role in regulating the expression and activity of epigenetic proteins. 17 As such, the epigenome cannot be inferred from DNA sequencing alone and requires a separate analysis of the chromatin state, with its remarkable complexity dictating not only what a cell is capable of doing at present but what it or its progeny may be able to do in the future. In the following sections, we describe how the various layers of epigenetic information are altered in MM and their contribution to disease progression and pathology (Figure 1 ).
Mutations in epigenetic regulators
The most commonly mutated epigenetic gene in MM is NSD2 (aka MMSET ), which becomes fused to the IGH locus as a result of the t (4;14) chromosomal translocation found as the initiating clonal lesion in ~15% of newly diagnosed MM patients. 9 The NSD2 gene has several transcriptional isoforms and encodes a multi‐domain histone methyltransferase that deposits the chromatin mark H3K36me2. Elevated expression of NSD2 in t (4;14) MM cells has been linked with increased deposition of H3K36me2 and its redistribution from predominantly promoter regions to widespread localisation across the genome. 18 , 19 At least in some contexts, the increase in H3K36 methylation caused by NSD2 overexpression is so profound that it depletes the universal methyl donor S‐adenosylmethionine (used by all histone and DNA methyltransferases), altering one‐carbon metabolism and driving a dependence on the metabolic enzyme AK2. 20 Increased H3K36me2 also reduces recruitment of EZH2 (the enzymatic component of the PRC2 complex) and a consequent decrease in the repressive mark H3K27me3, collectively promoting increased chromatin accessibility and expression of transcriptional programs required for MM proliferation. 18 , 19 Interestingly, recent analysis of a large cohort of newly diagnosed t (4;14) MM patients revealed variable disease correlated with different chromosomal breakpoints within the NSD2 gene. 21 This observation suggests greater complexity of t (4;14) translocations beyond an increase of H3K36me2, potentially linked with differential effects of individual breakpoints on specific NSD2 isoforms. 21
Aside from t (4;14) translocations, mutations in enzymes that regulate DNA methylation (e.g., DNMT3A , TET2 , IDH1‐2 ), histone acetylation (e.g., EP300 , CREBBP ), histone methylation (e.g., SETD2 , KMT2A‐C , KDM6A ) and nucleosome remodelling (e.g., ARID1A , SMARCA4 , CHD2 ) have been reported in MM. 5 , 8 , 22 , 23 While mutations in any given epigenetic regulator are infrequent, collectively, mutations in epigenetic modifiers occur in 25%–50% of MM patients, tending to arise more often in relapsed/refractory disease. 7 , 8 , 22 , 23 For most of these mutations, additional work in model systems is required to understand their contribution to disease progression and therapy response.
Altered enhancer landscape and 3‐D genome organisation
Cell type‐specific gene expression is controlled by extensive gene regulatory networks (GRNs) that encompass interactions between cis ‐regulatory DNA elements (CREs), TFs and their target genes. GRNs are typically highly interconnected and encompass multiple TFs acting synergistically to amplify and reinforce the GRN while repressing alternative transcriptional circuits. 24 Enhancers and super‐enhancers (large clusters of nearby enhancers) are distal CREs that promote the expression of GRNs and thereby define cellular identity and control cell fate. 25 Dysregulation of enhancer activity is a prominent and universal feature of MM cells and occurs through both genetic and non‐genetic mechanisms.
As mentioned earlier, canonical myeloma initiating translocations as well as secondary re‐arrangements bring various oncogenes ( CCND1 , CCND1 , NSD2 , MAF , MYC , etc) under the control of PC‐specific super‐enhancers such as those associated with the IGH and PRDM1 loci. More generally, comparison of MM cells with non‐malignant B cells and PCs has revealed that MM cells are characterised by widespread increased chromatin accessibility at distal CREs that are independent of specific genetic events. 26 , 27 Studies using ATAC‐seq and ChIP‐seq for H3K27ac (a mark of active chromatin) found that de novo MM cells fail to activate many developmentally regulated enhancers and subsequent gene expression programs along the memory‐B to PC trajectory, whilst simultaneously de‐repressing heterochromatin resulting in an extensive increase in DNA accessibility. 26 , 27 , 28 , 29 Interestingly, a significant increase in accessibility within enhancer regions, but not transcription start sites, is highly correlated with the upregulation of gene expression in MM, particularly for genes that regulate signalling pathways, proliferation, survival and interactions with the bone marrow microenvironment. 27 , 28 , 29 , 30 These observations underscore the critical importance of enhancer hyperactivity, and by extension the epigenetic proteins that regulate enhancers, in MM biology.
As MM cells arise from PCs, they remain dependent on lineage‐specific TFs such as IRF4, PRDM1 and XBP1. 31 Despite similar expression levels of these TFs between malignant and healthy PCs, MM has a higher prevalence of accessible PC‐specific TF motifs, owing in part to the vast increase in accessible enhancer regions. 27 , 28 , 29 Moreover, studies have reported increased complexity in the TF regulatory networks in MM versus PCs, driven by the widespread opening of chromatin. 27 , 29 Collectively, these studies identify TF activity underpinned by an accessible chromatin state rather than TF expression as the major driver of differential gene expression between MM and PCs.
Whilst MM cells exhibit gross changes to DNA accessibility when compared with normal PCs, distinct chromatin landscapes have been associated with specific genetic contexts. 29 , 30 , 32 In general, chromatin accessibility provided better stratification of genetic subtypes than the transcriptional profiles alone, suggesting that variations in the chromatin architecture converge on the same pathogenic pathways in MM. 29 Alvarez‐Benayas and colleagues reported that models combining both chromatin accessibility and gene expression data were able to clearly distinguish t (14;16) and t (11;14) MMs, and less so t (4;14) and hyperdiploid subtypes, likely a result of small sample sizes and inherent genetic heterogeneity within the hyperdiploid subtype. 29 Despite these limitations, these genetic subtypes displayed distinct TF regulatory networks, suggesting that TF rewiring underpins MM subtypes. 29
In addition to the acquisition of genetic drivers that confer drug resistance, rewiring of enhancer and TF regulatory networks provides transcriptional plasticity to MM cells, which can also facilitate therapy resistance. 26 , 33 , 34 , 35 For example, ETV4 and BATF occupancy at IKZF1‐bound enhancers promotes IMiD resistance by compensating for IMiD‐mediated IKZF1 depletion and sustaining the expression of IRF4 and MYC in MM cells. 33 , 34 Similarly, Frede et al. reported that enhancer rewiring promotes the expression of genes required for MM cells to persist under Elotuzumab in combination with pomalidomide, bortezomib and dexamethasone (Elo‐PVD) treatment. 26 Whilst Elo‐PVD reduced the total number of genes expressed in short‐term in vitro assays and in patients after 5 cycles, indicative of a decrease in transcriptional diversity and developmental potential, 36 surprisingly, this was not accompanied by a decrease in chromatin accessibility. 26 Instead, Elo‐PVD treatment increased the activity of key lineage TFs, such as IRF4, and increased the average number of enhancers associated per gene, particularly at genes involved in signalling, inflammation and response to stimuli. 26 Moreover, longitudinal single‐cell multiomics studies of MM cells from patients before therapy and at the time of relapse have described instances of drug resistance arising from converging adaptation, whereby the majority of therapy‐induced changes in chromatin accessibility, TF activity and gene expression were conserved between genetically distinct subclones. 35 Collectively, these data demonstrate that epigenetic and transcriptional plasticity within MM cells can promote the expression of pathways associated with drug resistance.
A larger scale of genomic organisation that provides additional layers of transcriptional regulation includes chromosome territories (interphase chromosomes that occupy discrete regions), which in turn consist of A/B compartments of active (A) and inactive (B) gene expression. Chromosome pairs that are commonly translocated in MM exhibit high spatial proximity and overlapping boundaries in B lymphocytes and MM cells, which presumably contribute to the prevalence of myeloma initiating chromosomal re‐arrangements. 37 , 38 In concordance with an open chromatin state being a common feature in MM that facilitates the expression of pathogenic transcriptional networks, the volume occupied by chromosomal territories is larger in MGUS and MM cells compared with B lymphocytes. 37 Moreover, a large proportion of compartment B‐to‐A switching, whilst minimal A‐to‐B, with concordant gene expression activation, was reported in human MM cell lines (HMCLs) when compared with a lymphoblastoid B‐cell line. 39 Although compartment switching has yet to be verified in primary patient samples, this data supports the notion of broad chromatin opening and transcriptional activation in MM.
Post‐translational modifications of histones
Post‐translational modifications of histone tails regulate gene expression by recruiting machinery that promotes chromatin remodelling and transcriptional activation or repression to specific regions of the genome. Major alterations to the levels or distribution of a particular mark can be evidence of dysfunction of the epigenetic writers or erasers that control it and may provide a therapeutic opportunity. Aside from the t (4;14) MM subtype characterised by hyperactivation of NSD2 and increased H3K36me2 deposition (see above), little is known about the histone mark landscape in MM and how it contributes to disease progression. Recent efforts by Ordonez and colleagues began to address this lack of understanding by integrating ChIP‐seq of six histone marks with chromatin accessibility, DNA methylation and gene expression data from PCs isolated from MM patients. 28 Compared with healthy cells throughout B cell development, MM cells predominantly exhibit gains of active histone marks and relatively few changes to repressive histone marks. 28 Most de novo H3K27ac occurred within enhancer regions and was associated with the transcriptional activation of canonical pathogenic pathways as well as key genes involved in detoxification processes, which are required for MM cells to survive under inherently high oxidative stress conditions. 28 Whilst a small sample size prevents further stratification by genetic subtype and justifies validation in larger cohorts, the authors identified an MM epigenetic signature that is distinct from normal cells across the B cell differentiation hierarchy. Further studies are also required to understand how the abundance, distribution and intratumor heterogeneity of histone modifications contribute to disease transformation, progression from MGUS to MM, and clinical outcomes.
Unlike DNA methylation, which is a relatively stable epigenetic mark, 40 histone modifications are often highly dynamic and facilitate rapid responses to stimuli. 41 As such, differences in the histone mark landscape have been associated with altered transcriptional states that underpin drug resistance across several cancer contexts. 42 In MM, changes in H3K27me3 downstream of the altered expression of EZH2 or its antagonist KDM6A may drive resistance to anti‐CD38 monoclonal antibodies. 43 , 44 HMCLs can adapt to continual exposure to Daratumumab in vitro by suppressing CD38 expression via H3K27me3 deposition at the promoter of CD38, suggesting a role for PRC2 regulation of CD38 expression in MM. 43 Indeed, high EZH2 expression is associated with decreased CD38 expression in MM patients and shorter event‐free survival following anti‐CD38 monoclonal antibodies. 44 Liu and colleagues also reported that loss of KDM6A in HMCLs conferred resistance to Daratumumab via increased H3K27me3 and concomitant downregulation of CD38. 43 Concordantly, decreased KDM6A and CD38 expression was observed in a subset of MM patients that relapsed or were refractory to Daratumumab, relative to newly diagnosed MM. 43 These studies demonstrate that the histone landscape may play an important role in drug response in MM and thus warrant further investigation.
DNA hypomethylation
Regions with increased active histone marks and chromatin opening have also been associated with loss of DNA methylation and gene expression increase in MM compared with normal B cells. 28 Indeed, pervasive hypomethylation is a common feature in MM, 45 , 46 , 47 , 48 , 49 , 50 which occurs irrespective of genomic location and the presence of repressive histone marks or heterochromatin 28 and is associated with genomic instability and poor prognosis. 45 , 47 Distinct DNA methylation patterns are associated with disease progression; vast DNA hypomethylation is established in MGUS and newly diagnosed MM, with focal hypermethylation at promoters of tumour suppressor genes, resulting in their suppression, occurring in advanced disease. 45 , 46 , 48 , 51 Moreover, enhancers of key B cell‐specific genes, which become progressively demethylated during B cell differentiation, were hypermethylated in MM and early progenitor B cells, suggesting that DNA methylation patterns may facilitate the retention of a more stem‐like state in MM development. 51 Similarly, MM cells stochastically gain methylation at bivalent promoters of developmental genes, 50 which may reflect age‐related spontaneous methylation changes that have been linked to the activation of a stem‐like state and cancer progression. 52 Interestingly, whilst the gain in CREs in MM is demarcated by increased chromatin accessibility, active histone marks, DNA demethylation and gene up‐regulation, the opposite trend was seen for CREs that are lost in MM, with the exception of DNA methylation. 28 At these loci, DNA methylation was largely similar between normal B and MM cells, 28 suggesting that MM cells retain epigenetic memory of past cellular states, akin to the retention of demethylated regions throughout normal B cell differentiation despite transcriptional inactivation. 53 , 54
Notwithstanding the general trends in DNA methylation, a large degree of heterogeneity exists in the methylation patterning of MM, which increases during disease development and is substantially higher than other lymphoid malignancies. 45 , 49 , 50 , 51 Whilst there is some evidence to suggest that interpatient heterogeneity in the DNA methylome can be explained by particular cytogenetic subtypes in MM, 45 , 49 overall, the pathogenic relevance of disrupted DNA methylation and the association with specific cytogenetics in MM remain unknown. Early studies with larger cohorts examined DNA methylation in MM utilising low‐resolution methods such as PCR of Alu or LINE‐1 sequences or methylation arrays that could detect ~27k CpG loci proximal to TSSs, 45 , 49 neither of which are poised to capture the extent of perturbations to the DNA methylome. Conversely, studies utilising sequencing methods with higher resolution and coverage often have small sample sizes within cytogenetic classes, making it difficult to conclude the associations between the DNA methylome and genetic subtype of MM. 28 , 50 , 51
DNA methylation of specific elements has also been implicated in drug resistance in MM. 48 For example, hypermethylation of the enhancer, and not the promoter, of the CRBN locus was associated with reduced CRBN expression and IMiD resistance. 55 , 56 , 57 Promoter hypermethylation and concomitant gene down‐regulation of DCC have been associated with poor survival in patients treated with VAD chemotherapy, IMiDs or alkylating agents, 58 but increased sensitivity to proteasome inhibitors. 59 Gene inactivation of RASD1 by DNA methylation promoted dexamethasone resistance to HMCLs. 60 Despite these associations, the DNA methylation landscape in relapsed/refractory MM cells remains largely uncharacterised. Further studies are required to identify patterns in DNA methylation that emerge following various treatment schemes, how these methylation changes arise and how they facilitate drug resistance.
Analogous to genetic instability enabling the stochastic acquisition of oncogenic mutations that drive tumour evolution and promote drug resistance, epigenetic instability results in stochastic heritable changes to the epigenome which can alter the transcriptional landscape and impact clonal fitness to promote malignant transformation or enable adaptation to therapeutic pressures. 61 , 62 Derrien et al. examined the epipolymorphisms of MM cells and found extensive intratumor heterogeneity arising from stochastic methylation changes; notably, gains within bivalent promoters of developmental genes and loss within partially methylated domains (PMDs). 50 High epigenetic heterogeneity at diagnosis, as measured by the degree in epiallele composition change between MM and PCs, was associated with a decoupling between promoter methylation and gene expression levels, transcriptional variability (or ‘noise’) and adverse outcomes that were independent of high‐risk genetic lesions. Some patients exhibited further changes in epiallele composition at relapse, suggesting a strong clonal outgrowth following treatment, although the authors did not investigate whether this was a consequence of the selection of a pre‐existing genetic event, acquisition of novel genetic driver mutations or by epigenetic plasticity and accompanying transcriptional changes. Similar findings have been reported in the context of CLL, whereby tracking the epipolymorphisms revealed high intratumour epigenetic heterogeneity, which in some instances was associated with specific genetic driver lesions, whilst in others occurred in the absence of genetic subclonal mutations. 63 , 64 Moreover, several studies have shown the importance of transcriptional noise in adapting to drug pressures, 65 , 66 which is predominantly driven by enhancer‐regulated genes and enables cells to rapidly respond to stimuli. 67 Given the importance of enhancer regulation of transcriptional networks in MM, these studies suggest that the intratumor epigenetic heterogeneity of enhancers may underpin the elevated transcriptional noise of genetically identical subclones in MM and facilitate the rapid response and clonal outgrowth in response to drug treatment, warranting further studies.
Tumour microenvironment as a driver of epigenetic dysregulation in MM
An additional layer of complexity with MM is the spatial heterogeneity and interaction with the tumour microenvironment (TME), with recent studies finding an interplay between the epigenetic landscape of MM and interactions with the TME. 68 , 69 At the simplest level, mutations in epigenetic modifiers in PCs, such as the histone demethylase LSD1, can predispose the progression to MGUS and MM by promoting the expression of pathways associated with pathogenic MM–TME interactions. 70 Inflammatory signalling by MM cells can also trigger long‐term suppression of osteoblast differentiation through epigenetic remodelling and transcriptional repression of key osteoblast transcription factors in bone marrow mesenchymal stromal cells (BMSCs). 71 Similarly, MM cells can alter the DNA methylome and support the suppression of Homeobox and osteogenic genes in BMSCs. 72 Conversely, the TME can influence the epigenome of MM cells. Utilising changes in chromatin architecture and gene expression data from HMCLs co‐cultured with BMSCs in vitro, Binder et al. identified a set of stromal interacting genes whose expression was a prognostic factor in newly diagnosed MM that was independent of mutational status and transcriptome‐based classifiers. 68 They reported that BMSCs promoted a significant increase in chromatin accessibility in MM cells, particularly within enhancer regions, which correlated with transcriptional up‐regulation of signalling, extracellular matrix organisation and cell migration pathways. 68 Moreover, the sustained expression of stromal‐induced genes in extramedullary and circulating PCs was associated with accelerated disease dissemination. 68 Recently, single‐cell RNA and ATAC sequencing of bone marrow focal lesions in newly diagnosed MM patients have revealed epigenetic and transcriptional plasticity between genetically identical MM subclones that are spatially separated within the TME. 69 Although the consequence of these differences is not entirely understood, increased epigenetic plasticity has been associated with poorer clinical outcomes as cancer cells have increased potential to adapt to selective pressures.
Transcriptional plasticity within the TME can also facilitate therapeutic resistance. For example, plasmacytoid dendritic cells (pDCs) upregulated pro‐tumorigenic genes important for immunosuppression in MM patients that relapsed or were refractory to IMiDs, when compared with normal donors. 73 Conversely, scRNA‐seq ligand‐receptor interaction analysis of relapsed/refractory MM and the corresponding TME revealed that MM cells upregulated inflammatory cytokines and inhibitory receptors that target specific immune populations, 73 which likely contribute to the immunosuppressive environment and changes in cellular composition within the TME. 73 , 74 , 75 Direct adhesion between MM cells and BMSCs can stimulate phosphorylation and inactivation of EZH2, thus decreasing H3K27me3 and upregulating antiapoptotic genes in MM cells, and facilitating resistance to cytotoxic drugs. 76 Further, single‐cell sequencing studies integrating genomic, epigenomic and transcriptomic profiles of MM and the surrounding TME would provide a detailed characterisation of the interactions between MM and TME throughout disease progression and clonal evolution under therapeutic pressure.
TARGETING EPIGENETIC REGULATORS—A VIABLE STRATEGY IN MYELOMA?
A growing appreciation of the critical importance of epigenetic dysregulation to the biology of cancer cells has prompted extensive efforts to therapeutically target epigenetic proteins. Most epigenetic proteins possess highly structured domains and/or enzymatic activities that are amenable to disruption with small molecule drugs. Inhibitors of various classes of epigenetic proteins that produce meaningful clinical benefit have been developed, as exemplified by DNA hypomethylating agents and histone deacetylase, lysine methyltransferase and Menin inhibitors. 77 , 78 It is also possible to target upstream processes such as altered metabolism, which can be a major driver of the epigenetic state in some cancers. 79 , 80
Epigenetic inhibitors can induce both cell autonomous and non‐cell autonomous anti‐cancer effects. Many epigenetic therapies act as differentiation agents, blocking self‐renewal circuits and promoting terminal differentiation, leading to tumour exhaustion. 81 Moreover, epigenetic blockade can have a major impact on anti‐cancer immunity, including by inducing a state of viral mimicry in malignant cells and altering the development or activity of various immune subsets. 82 The latter is especially important in the myeloma context, given the extensive and growing utilisation of immuno‐oncology agents.
A prominent example of a class of epigenetic agents that has been tested in myeloma is histone deacetylase inhibitors (HDACi). Histone deacetylases (HDACs) are a family of proteins that catalyse the removal of acetyl moieties from histone and non‐histone substrates. There are 18 known HDACs in humans grouped into 4 classes. 83 HDACi cause pleiotropic molecular changes and potent anti‐proliferative and cytotoxic effects in a wide variety of cell types, including MM cells, as demonstrated by preclinical studies in the early 2000s. 84 Subsequent clinical development of several HDACi culminated with the approval of the pan‐HDACi panobinostat for relapsed and refractory myeloma in the United States and Europe in 2015. Notably, however, it has since been voluntarily withdrawn from FDA approval, with Secura Bio citing a lack of feasibility to complete post‐marketing clinical trials. Indeed, the clinical activity of various HDACi used either as single agents or in combination with other agents has been mostly disappointing. 85 , 86 , 87 , 88 A case in point is the phase 3 PANORAMA 1 trial that reported a very modest increase in overall survival by the addition of panobinostat to bortezomib and dexamethasone in relapsed or relapsed and refractory MM with one to three previous treatments. 89 Similarly, a retrospective analysis of approximately 100 heavily pretreated MM patients reported modest overall response rates when panobinostat was combined with various drugs beyond proteasome inhibitors, including IMiDs and daratumumab. 88
The experience of HDACi in myeloma, as well as those of EZH2 90 and BET bromodomain 91 inhibitors, highlights a major challenge for the effective deployment of epigenetic drugs, namely the identification of sensitive disease contexts and predictive response biomarkers. The most straightforward approach is to directly inhibit a mutant oncogene or its known downstream dependencies, which have found success in certain sub‐types of acute myeloid leukaemia, such as those with IDH mutations or KMT2A re‐arrangements. For myeloma, the recent discovery of NSD2 degraders provides a potential pathway to target t (4;14) re‐arranged MM cells. 92 Although targeting an initiating genetic event is attractive and potentially avoids the outgrowth of malignant clones that lack the molecular drug target, it remains to be seen whether NSD degradation can be safely achieved in vivo and the ease with which MM cells can overcome NSD blockade.
An alternative strategy is to tailor targeted therapies to the ‘cellular state’ rather than the genotype of a particular tumour. 93 This paradigm is attractive for myeloma (and lymphoid cancers more broadly) even if the treatment does not effectively discriminate between malignant plasma cells and their normal counterparts. Crucially, despite the fact that most epigenetic proteins are widely expressed in many different (normal and cancer) cells, their disruption often results in profound cellular phenotypes only in specific cell types. 94 In line with this notion, recent studies have applied genome‐wide screening technologies to identify myeloma‐selective genetic dependencies, which include many epigenetic proteins. 31
Among the most notable epigenetic dependencies in MM are the paralogous multi‐functional transcriptional co‐activators EP300 and CREBBP. EP300/CREBBP are acetyltransferases that acetylate thousands of residues on a wide array of histone and non‐histone protein substrates including lysine 27 of histone 3 (H3K27ac). 95 EP300/CREBBP catalytic inhibitors are highly active against MM cells, and trigger pronounced loss of histone acetylation at enhancers, leading to downregulation of cell identity, proliferation and survival gene expression programs. 96 EP300/CBP inhibitors synergise with IMiDs to downregulate MYC and IRF4, 34 and their activity can be further boosted by drugs that increase the activity of the PRC2 complex, which functionally antagonises EP300/CBP. 96
Notwithstanding their promising activity against model systems in vitro and in vivo, clinical development of catalytic (acetyltransferase) EP300/CREBP inhibitors has proved challenging. By contrast, targeting the bromodomain of EP300/CREBBP is emerging as a more viable strategy. 97 EP300 and CREBBP each contain a single bromodomain which acts as a reader for acetylated lysine residues on histones and other DNA‐associated proteins and is required for the recruitment of EP300/CREBBP to some but not all regions of the genome. 97 , 98 Molecules that are highly selective for the EP300/CREBBP bromodomains such as CCS1477 (inobrodib) 98 and GNE‐781 99 have been reported. Unlike EP300/CREBBP catalytic inhibitors which produce near‐global (albeit somewhat enriched at enhancers) hypoacetylation, bromodomain disruption drives highly focused displacement of EP300/CREBBP from IRF4 to E2A bound enhancers, disrupting oncogenic transcription in a more targeted manner. 97 Encouragingly, inobrodib treatment reportedly induced objective responses with minimal toxicity in four heavily pre‐treated MM patients, with further clinical assessment ongoing. 97
Beyond EP300/CREBBP, components of the chromatin remodelling SWI/SNF complex were recently identified as essential epigenetic regulators of IRF4 oncogenic transcription. 100 Inhibitors of the catalytic subunits of SWI/SNF, SMARCA2 and SMARCA4, are currently being tested in early clinical trials, including for blood cancers. 101 Although much work remains to be done to establish the safety and efficacy of this approach, it represents another promising avenue to counter resistance to IMiDs, which remain a cornerstone of frontline myeloma therapy.
CONCLUDING REMARKS
The relentless pace of MM evolution continues to challenge our capacity to provide effective treatment, with many patients exhausting all available options. Alongside the acquisition of sequential genetic events, the epigenetic landscape of MM cells becomes progressively dysregulated. Global chromatin activation, demarcated by increased chromatin accessibility, active histone marks and DNA hypomethylation, particularly within enhancer regions, is common and serves to promote highly interconnected GRNs that sustain MM cell survival and proliferation.
Despite recent efforts, we still lack a comprehensive understanding of the interplay between the layers of epigenetic regulation and their contribution to the regulation of gene networks that underpin MM disease initiation, progression and drug resistance. A major challenge in the field is the ability to isolate enough bone marrow‐residing PCs from healthy donors to use as a comparator for MM cells. As such, studies often utilize other B‐cell subsets as a reference population for MM, which likely do not accurately reflect the chromatin landscape of healthy or malignant PCs. For example, the 3D genome architecture of GM12878 B cells 102 has been used as a reference to predict TAD boundaries and chromatin states in MM cells. 26 , 27 , 28 , 29 , 50 Moreover, the absence of epigenetic information in normal bone marrow PCs prevents the distinction in epigenetic states between MM‐specific cells and those of origin. Given the epigenetic and transcriptional heterogeneity of MM, even within a cytogenetic subtype, additional studies with larger cohorts of patients are required to increase the resolution and delineate how the epigenetic state of MM cells contributes to their cellular state, interactions with TME and response to therapeutic pressures. This will provide the basis for further research for the identification of better biomarkers of response and new therapies for MM.
AUTHOR CONTRIBUTIONS
Subhasree Kumar: Writing – original draft; writing – review and editing. Lev M. Kats: Conceptualization; writing – original draft; writing – review and editing; supervision. Emily Gruber: Conceptualization; writing – original draft; writing – review and editing; supervision.
CONFLICT OF INTEREST STATEMENT
The authors declare no conflicts of interest.
ACKNOWLEDGEMENTS
This work is supported by the Barrie Dalgleish Centre for Myeloma and Related Blood Cancers. SK is supported by the Australian Postgraduate Award. LMK is supported by a Leukaemia and Lymphoma Society Scholar Award. Open access publishing facilitated by The University of Melbourne, as part of the Wiley ‐ The University of Melbourne agreement via the Council of Australian University Librarians.
Kumar S, Kats LM, Gruber E. Epigenetic reprogramming in multiple myeloma—Challenges and opportunities. Int J Cancer. 2026;158(2):423‐432. doi: 10.1002/ijc.35426
Lev M. Kats and Emily Gruber contributed equally to this study.
Contributor Information
Lev M. Kats, Email: lev.kats@petermac.org.
Emily Gruber, Email: emily.gruber@petermac.org.
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