Introduction

Multiple myeloma (MM) is a B-cell malignancy characterized by the clonal proliferation of malignant plasma cells within the bone marrow. While it primarily resides in the bone marrow, its progression can lead to systemic effects impacting various areas of the body.1

The pathogenesis of MM is driven by a series of genetic alterations that contribute to the initiation and progression of the disease, from Monoclonal Gammopathy of Unknown Significance (MGUS), then to Smoldering Multiple Myeloma (SMM), and ultimately to symptomatic myeloma, with each stage marked by an increasing mutation load.2 These abnormal plasma cells produce monoclonal proteins (M-protein), which are abnormal antibodies or parts of antibodies. These proteins are typically composed of heavy chains (types include IgG, IgA, IgD, IgE, or IgM) and light chains (kappa or lambda), which can be detected in the blood or urine and are used as markers for diagnosing and monitoring the disease. The presence of these monoclonal proteins can lead to complications such as kidney damage or bone lesions, highlighting the importance of early detection and tailored treatment strategies to manage the disease effectively. Additionally, MM patients may experience hypercalcemia, anemia, and bone pain. An aggressive form of MM, known as extramedullary disease (EMD), occurs approximately in 20% of cases. EMD is characterized by the spread of myeloma cells beyond the bone marrow to other organs, such as the lungs, liver, and soft tissues, significantly complicating treatment and management.3

MM is typically categorized into stages 1, 2, and 3, with the stage at diagnosis significantly influencing treatment decisions and prognosis. Historically, the Durie-Salmon staging system classified MM based on tumor cell mass and clinical parameters like hemoglobin, calcium levels, and urine light chain M-component.2 The International Staging System (ISS) improved on this by using serum beta-2 microglobulin (Sb2M) and serum albumin levels to classify MM into three stages.3 The Revised International Staging System (R-ISS) refined this approach further by incorporating genetic risks and lactate dehydrogenase (LDH) levels.4 The second revision of the ISS (R2-ISS) introduced a points-based, four-tier risk stratification system that considers risk factors such as gain(1q), del(17p), and high-risk translocations.5 This system assigns patients to low, low-intermediate, intermediate-high, and high-risk categories, providing a more nuanced assessment that helps tailor treatment strategies and predict patient outcomes more effectively.

The pathogenesis of MM is driven by a series of genetic events that contribute to the initiation and progression of the disease. The hierarchical layers of drivers in MM, from primary genetic alterations to the complex interactions with the tumor microenvironment (TME), are illustrated in Figure 1.

Figure 1 Hierarchical layers of drivers in multiple myeloma. The broadest levels at the top illustrate primary genetic alterations, which include initial chromosomal translocations and hyperdiploidy. As the layers narrow down, secondary genetic alterations, epigenetic alterations, and non-coding RNA dysregulation are shown, reflecting the increasing complexity of interactions. The narrowest levels at the bottom depict co-dependencies and regulatory networks, culminating in the tumor microenvironment (TME), highlighting the intricate network of factors contributing to myeloma pathogenesis and progression.

Driver genes may harbor critical mutations or be disrupted and dysregulated by structural variations or epigenetic aberrations. Driver mutations actively contribute to tumorigenesis and confer a selective advantage to cancer cells. These mutations can exhibit varying degrees of impact, categorized as strong, latent, or weak, and occur at different frequencies within the MM patient population. In contrast, passenger mutations are functionally neutral or even detrimental to cancer cells.6

Remarkably, about 80% of driver mutations in cancer are somatic, originating directly within the cancer cells, while 10% are inherited through the germline, and the remaining 10% occur in both somatic and germline contexts.7 Although some studies suggest that, on average, around five driver mutational genes are associated with each MM tumor, a recent study found that about 16% of cases in a large cohort of relapsed/refractory (RRMM) patients exhibited no known driver genes, underscoring the genomic complexity and heterogeneity inherent to MM.8

MM is highly heterogeneous, and whole-genome characterization studies have been pivotal in identifying and classifying recurrent genetic abnormalities.9 Computational approaches have been employed to categorize potential drivers of MM, with several studies providing comprehensive insights into its genomic landscape, identifying and classifying key drivers that contribute to MM pathogenesis and progression.8,10–12

Recent advances have shed light on the complexity of the clonal architecture of MM, revealing that primary genetic events occur early in the disease course and set the stage for further genetic alterations. High-throughput sequencing technologies have deepened our understanding of clonal evolution in MM, uncovering subclonal heterogeneity and the dynamic nature of the disease.9–12 This has significant implications for prognosis and treatment, as certain primary events are associated with different clinical outcomes and responses to therapy. The identification of these events can lead to the development of targeted therapies aimed at specific pathways altered by the primary drivers, offering a more personalized approach to MM treatment.

Understanding the roles of drivers can guide the development of precision therapies and enhance our comprehension of the mechanisms behind drug resistance, tumor development, and the identification of cancer biomarkers. Identifying driver aberrations is crucial for preventing disease progression, as even a small number of driver events can initiate disease development.13 Therefore, pinpointing and validating these mutations is essential to refine risk stratification and improve MM management. While substantial progress has been made in identifying genetic and molecular drivers of MM, the field continues to grapple with distinguishing true drivers from passenger alterations and understanding their precise roles in disease progression. Current tools and datasets often fall short in providing a comprehensive view of MM heterogeneity, leaving important questions unanswered.

This review provides a detailed exploration of the genetic and molecular drivers of MM, presenting both established and emerging factors, including epigenetic modifications, non-coding RNAs, and mutational signatures. We emphasize critical areas where understanding remains incomplete and discuss their implications for developing targeted and precision therapies. We examine how current insights into MM drivers are shaping the development of targeted therapies and precision medicine approaches, bridging the gap between their identification and translational applications. Additionally, we discuss how advanced computational analyses, combined with clinical perspectives, provide a unique view of the oncogenic dependencies that drive MM progression and the therapeutic opportunities that could shape its treatment.

The Genomic Landscape of MM

The genetic makeup and evolutionary history of a tumor constitute its clonal landscape, where drivers contribute to tumorigenesis, clonal expansion, heterogeneity, and response to therapy. Clonal mutations, occurring in the initiating cell of a clonal sweep, are theoretically present in every cell of a tumor, whereas subclonal mutations arise in descendant cell populations.14 This distinction between primary (clonal) and secondary (subclonal) events is crucial for understanding MM development and tumorigenesis. The genomic alterations that drive MM pathogenesis are non-linear – they are heterogeneous and appear in branched patterns, which adds to disease complexity and can potentially favor the emergence of drug-resistant subclones.6,7,15 Plasma cells clones can accumulate genomic alterations, gain proliferative advantages, and establish multiple subclonal populations within the bone marrow, further compounding the genetic landscape with primary and secondary translocations among other genomic changes. The interplay between primary clonal developments and the broader genomic landscape highlights how early genetic alterations drive tumor initiation and shape the evolutionary trajectory of MM.

Table 1 Summary of Main Cytogenetic Alterations in Multiple Myeloma

Table 1 summarizes the main cytogenetic alterations in MM, including key translocations, hyperdiploidy, and the most common amplifications and deletions. Figure 2 presents a circos plot illustrating a more comprehensive view of recurrent genetic alterations in MM, encompassing these main cytogenetic changes as well as additional copy number alterations (CNAs) and single nucleotide variants (SNVs). Together, these figures underscore the genomic complexity and heterogeneity characteristic of the disease.

Figure 2 Circos plot summarizing the most recurrent genetic alterations observed in multiple myeloma. This circos plot includes translocations, copy number alterations (CNAs), and single nucleotide variants (SNVs). The outer ring represents the chromosomes, with different colors indicating various types of genetic alterations. Translocations are depicted as lines connecting different chromosomal regions, CNAs are shown as segments along the chromosomes, and SNVs are marked at their respective genomic locations. This visual representation highlights the complexity and heterogeneity of the genomic landscape in multiple myeloma, providing insights into key genetic events that drive the disease.

Primary IgH Translocations

Primary clonal events in MM are mainly characterized by immunoglobulin (Ig) translocations and hyperdiploidy. Ig translocations involve the rearrangement of immunoglobulin genes, located on chromosome 14, that encode antibodies and can affect both heavy and light chains.8,9 The heavy chain translocations (IgH) are usually classified as primary clonal events, while light chain translocations are secondary. The IgH translocations typically involve seven main recurrent partner loci: CCND1, CCND2, CCND3, MAF, MAFA, MAFB, and NSD2.

The most prevalent is the t(11;14)(q13;q32) translocation involving CCND1, which is found in approximately 16–24% of MM cases.10–12 Tumors harboring this translocation are characterized by overexpression of cyclin D1, elevated levels of the anti-apoptotic protein BCL-2, and frequent CD20 expression, which are not typically seen in t(11;14)-negative MM.12 A recent meta-analysis of 13 studies involving 961 patients, suggests that high CCND1 expression correlates with poorer overall survival (OS) in patients receiving chemotherapy.27 However, those treated with bortezomib tended to have a longer OS. Other studies show that the prognosis of patients with t(11;14) differ subject to co-occurring alterations and respond slowly to proteasome inhibitors.28 CCND1 is implicated in MM progression by promoting cell survival and proliferation, partly through its interactions with cell adhesion molecules. Other cyclin D genes, such as CCND2 and CCND3, are also implicated in MM pathogenesis, although translocations involving these genes occur less frequently.21,29 Post-transcriptional mechanisms, alongside Ig translocations, may also upregulate CCND2, contributing to the pathogenesis of the disease.19

The translocations t(4;14)(p16.3;q32) and t(14;16)(q32;q23) are found in approximately 15% and 5% of MM cases, respectively. The t(4;14) translocation leads to overexpression of NSD2 (Nuclear Receptor Binding SET Domain Protein 2, also known as MMSET) and FGFR3 (Fibroblast Growth Factor Receptor 3).30,31 In the revised International Staging System (rISS), this translocation is classified as a high-risk lesion.4 This is due to its association with a more aggressive disease course and shorter OS. However, our recent Patient Similarity Network (MM-PSN) model based on multi-omics data from NDMM patients, revealed that co-occurrence of t(4;14) and gain of chromosome 1q (gain(1q)) identified patients at significantly higher risk of relapse and shorter survival as compared to t(4;14) as a single lesion.32

NSD2 encodes a histone methyltransferase that alters chromatin structure and primarily regulates gene expression through histone methylation, specifically at histone H3 lysine 36 (H3K36).33 Methylation by NSD2 influences several cellular processes, including gene transcription, proliferation, and cell cycle progression. A recent study on patients affected by t(4;14) identified three distinct breakpoint categories within the NSD2 gene, finding that the location of the translocation breakpoints significantly affected patient outcomes.34 Concurrently, FGFR3 overexpression, caused by the same t(4;14) translocation, drives cell growth and division, which can contribute to the aggressive nature of certain MM cases.31,35 However, patients who do not express FGFR3 exhibit poor prognosis, indicating a more critical role of NSD2 in the progression of the disease.34 NSD2 also interacts with various proteins and manages downstream signaling pathways involved in cell death, cell cycle, DNA repair, and integrin-mediated signaling. The use of proteasome inhibitors, such as bortezomib, has been shown to improve outcomes in patients with this translocation.36

The t(14;16) translocation affects the MAF (musculoaponeurotic fibrosarcoma) oncogene, which encodes a transcription factor crucial for various cellular processes.37 While MAF translocations occur only in 5–10% of cases, c-MAF is overexpressed in 50% of myelomas, enhancing tumor survival.38 The t(14;16) translocation generally indicates stable disease in MGUS patients, but in MM patients, it is associated with a higher risk and poorer overall survival.39 However, like for co-occurrence of gain(1q) and t(4;14), our network analysis found that most patients with t(14;16) also had concurrent gain(1q), which is known to confer poor prognosis, and thus, the prognostic impact of the MAF translocation may be confounded by this.32

MAF translocations also contribute to resistance against proteasome inhibitors like bortezomib, often resulting in a poor response in MM patients,24 with the mechanisms behind the resistance not fully understood. Immunomodulatory drugs have been particularly effective at treating t(14;16 MM).40

The t(14; 20) and t(8;14) translocations, involving MAFB and MAFA respectively, occur less frequently, in about 1–2% of cases.41 Like MAF, MAFB and MAFA are also transcription factors and their overexpression due to translocations can drive oncogenic processes, although their exact roles and impacts on prognosis in MM are less well-studied and need further investigation.

Hyperdiploidy

Hyperdiploidy (HD) in MM is characterized by the trisomy of odd-numbered chromosomes - specifically chromosomes 3, 5, 7, 9, 11, 15, 19, and 21.6,42 Tumors are classified as either HD or non-HD based on the number of chromosome sets in a cell, with diagnosis typically achieved through flow cytometry, fluorescence in situ hybridization (FISH), or whole genome sequencing.43 This chromosomal anomaly leads to an increased dosage of genes on these chromosomes, which may affect gene expression and contribute to the disease’s development and progression.44 Interestingly, while HD and non-HD MM differ in gene expression on trisomy chromosomes, a higher proportion of dosage-sensitive genes is found on non-trisomy chromosomes.

The identification of HD often includes the gain of chromosome 11 and increased expression of CCND1. Notably, a subset of patients with the t(11;14) translocation, which involves CCND1, also exhibit this chromosomal gain. This combination can further amplify CCND1 expression, potentially intensifying the aggressiveness of the disease. Such cases may represent a distinct clinical subset of MM with unique characteristics and prognostic outcomes.32 HD is the most common primary genetic event in MM, affecting 56% of tumors, underscoring its significance in understanding the primary or clonal events in early-stage disease and its progression.45 Moreover, the presence of HD is typically associated with improved patient survival rates compared to non-HD cases,46 especially in patients with trisomies of chromosomes 3 and 5. However, this trend does not apply universally. Trisomy of chromosome 21, or co-occurrence of high-risk cytogenetic features such as gain of 1q are exceptions that are linked to poorer survival outcomes.13,47,48

Other Ploidy Changes

Beyond the identification of HD, the broader ploidy status of MM cells is a critical factor in disease characterization.49 Non-hyperdiploid MM, which includes hypodiploid (fewer than the normal diploid number of chromosomes), pseudodiploid (approximately the normal diploid number), and near-tetraploid (close to twice the normal diploid number but not exceeding 75 chromosomes), plays a significant role in the pathogenesis of the disease.

Specifically, hypodiploid MM has been linked to a higher risk of disease progression and shorter overall survival compared to hyperdiploid MM, which tends to have a more favorable prognosis.50,51 Pseudodiploid MM, which harbors a normal chromosome count but with structural abnormalities, also tends to have an adverse prognosis due to the presence of high-risk cytogenetic abnormalities such as t(4;14), t(14;16), and del(17p).52 Near-tetraploid MM is less common, and its implications are less clear, but it may be associated with an intermediate profile between hyperdiploid and other non-hyperdiploid subtypes.53,54

Overall, the non-hyperdiploid group, particularly with certain cytogenetic abnormalities, is often associated with a more aggressive disease course and resistance to certain therapies, underscoring the importance of ploidy and cytogenetic analysis in understanding primary clonal events and informing treatment planning for MM patients. In addition to primary clonal events, subclonal events, including mutations and MYC rearrangements, further contribute to MM heterogeneity.

Secondary or Subclonal Events

Secondary or subclonal events in MM, which are acquired during tumor progression from the initiating pool of cells, include light chain translocations, copy-number alterations (CNA), non-Ig translocations, somatic mutations in driver genes and other biologically relevant genes, structural variation (SV) events, and alternative splicing events. Co-occurrences of oncogenic markers, as well as influences from the immune system and cellular metabolism pathways like the unfolded protein response (UPR), also contribute to MM progression.11,55

Secondary IgH Translocations

Secondary IgH translocations frequently involve the dysregulation of the MYC oncogene. This dysregulation is mediated by the Eα1 and Eα2 enhancers, which are potent regulatory elements within the IgH locus.56 The progression of MM is driven by several pivotal signaling pathways, notably those involving MYC as well as RAS, and NF-κB. These pathways often exhibit functional redundancy and are typically co-activated, ensuring that at least one is active in the vast majority (95%) of NDMM cases.

MYC, a proto-oncogene, plays a critical role in regulating various cellular processes, including growth, proliferation, apoptosis, differentiation, and transformation.28 In MM, chromosomal rearrangements or CNAs involving MYC are considered secondary events that can contribute to a more aggressive disease phenotype.21,29 While chromosomal rearrangements typically lead to increased monoallelic MYC expression, tumors without rearrangements often show high biallelic MYC expression already in the MGUS stage.57 Translocations involving MYC can disrupt the regulation of other essential driver genes and perturb the expression of downstream genes pivotal to B-cell biology, such as FGF16, ADAMTS1, FBXL7, HRK, PDGFD, and PRKD1. These changes are instrumental in driving the progression of MM.

While the prevailing view supports the occurrence of MYC alterations in the later stages of MM, some evidence suggests that they may also appear in early stages. MYC translocations, which are present in approximately 25%-42% of NDMM cases, are associated with poorer prognosis. These genetic events have been linked to increased mortality and the development of resistance to therapeutic drugs.30,31

Immunoglobulin Light Chain Translocations

Secondary Ig translocations in MM can significantly impact disease prognosis and treatment response. Approximately 10% of MM patients exhibit translocations involving the immunoglobulin lambda (IgL) locus, which are associated with a poor prognosis.32,33 Notably, IgL-MYC translocations, characterized by focal amplifications of enhancers at both the IgL and MYC loci, are linked to a particularly adverse prognosis.58 These translocations also confer resistance to immunomodulatory drugs (IMiDs), which target the lymphocyte-specific transcription factor Ikaros (IKZF1), known to bind robustly to the IgL enhancer. This resistance highlights the prognostic importance of IgL-MYC translocations, independent of other genetic abnormalities.35 Despite their significance, IgL translocations do not define a specific gene expression signature, are not associated with any mutations, and occur across all gene subtypes of MM. However, their co-occurrence with HD disease and their status as an independent marker of poor prognosis suggests that some patients diagnosed with HD myeloma may be misclassified due to the presence of an IgL translocation. Patients with HD myeloma and IgL translocations may experience outcomes that are heavily influenced by the broader genomic instability rather than by the translocation itself. Moreover, emerging evidence highlights the heterogeneity within the IgL-MYC translocation subtype, with some patients responding to alternative therapies targeting downstream MYC pathways.36 This suggests a potential therapeutic avenue for overcoming IMiD resistance in these patients. In addition, recent advances in proteasome inhibitors and bispecific T-cell engagers (BiTEs) have demonstrated efficacy in high-risk MM, including cases with MYC involvement.36

Translocations involving the immunoglobulin kappa (IgK) locus are less common than those involving the immunoglobulin lambda (IgL) locus, occurring in approximately 4.5% of cases. Similar to IgL translocations, IgK translocations can also target the MYC gene, leading to the juxtaposition of IgK enhancers to the MYC locus. However, unlike IgL-MYC translocations, those involving IgK do not necessarily result in decreased survival.35

Copy Number Alterations

Beyond immunoglobulin translocations, which are critical early drivers of MM, additional genomic alterations arise during disease progression. Among these, copy number alterations (CNAs) represent pivotal secondary events that contribute to tumor evolution by amplifying or deleting segments of the genome, thereby impacting gene expression and cellular function. These abnormalities can manifest as gains, including duplications and amplifications, or losses, such as deletions and loss of heterozygosity (LOH).8 CNAs are commonly observed in chromosomes 1, 8, 13, 14, and 17, and to a lesser extent in chromosomes 3, 5, 7, 9, 15, 16, 22, and X. While the prognostic relevance of these alterations has been defined and confirmed by multiple studies, the mechanistic underpinning of their presence has not yet been fully characterized, although some of these lesions have been dissected to a greater degree than others.

The most recurrent CNAs include losses of chromosome 13q (del(13q)), observed in 45% of patients, and gains of chromosome 1q, which are seen in about 40% of patients, with high-level gains or amplifications (amp(1q)) in 6.8% of cases.37–39 The prognostic implication of del(13q) in MM is somewhat variable and may depend on the presence of other cytogenetic abnormalities.24 It is often considered associated with a worse prognosis, particularly when it occurs alongside other high-risk abnormalities. The aberration primarily encompasses the entire chromosome 13 without a clearly identified specific driver gene. Although RB1 and DIS3 have been posited as candidate loci, only biallelic deletion of RB1 is linked with MM progression, while DIS3, a commonly essential gene, does not exhibit complete inactivation.41–43 The deletion of the microRNA Mir15a/Mir16-1 locus on chromosome 13, however, has been found to contribute to disease progression in MM mouse models, a phenomenon also noticed in MM patients.44,45 Further explorations and implications of these findings will be discussed in the miRNA section of this review.

The gain of 1q (gain(1q)) is particularly concerning as it is linked with worse progression-free survival (PFS) and is often observed to increase at the time of relapse.23,46,59 This aberration has long been considered a high-risk factor and was recently incorporated into the second revision of the International Staging System (R2-ISS).5 Our recent Patient Similarity Network (MM-PSN) model, based on multi-omics data from NDMM patients, identified six disease subtypes enriched for gain(1q) and revealed that co-occurrence of gain(1q) with other recurrent lesions confers a shorter median time to relapse and death, particularly when co-occurring with the t(4;14) translocation.48 A minor clone of gain(1q) might represent an earlier stage in the pathogenesis of the abnormality and is prone to evolve into a dominant clone at relapse.26 The co-occurrence of gain(1q) with other cytogenetic abnormalities besides t(4;14), such as del(1p) or del(17p), also identifies subsets of patients with particularly poor prognoses, and its co-occurrence with del(13q) is considered a driver event in MM progression, defining a distinct subgroup of patients with overexpression of CCND2 and unfavorable clinical outcomes.47 Our PSN study also showed differential expression of 1q genes across the subtypes enriched with gain(1q), suggesting that different sets of 1q genes may be active in the different subgroups of MM patients. The large size of the genomic region affected has posed a significant challenge in the identification of the drivers of 1q-MM. Most studies so far have focused on genes located in 1q21, a critical focal area of amplification, including MCL1, CKS1B, ADAR1, and ILF2, which have been proposed and validated as drivers of aggressive disease in 1q-MM.60–63 Their pathogenic roles range from ADAR1’s promotion of malignant transformation through RNA editing, ILF2’s facilitation of genomic instability tolerance, MCL1’s critical involvement in cell survival and resistance to apoptosis, and CKS1B’s contribution to cell cycle progression and proliferation. Another recent study has also demonstrated a driver role for a gene outside of 1q21, PBX1, which is located in 1q42, and has been implicated in directly regulating critical oncogenic pathways and a FOXM1-dependent transcriptional program, leading to adverse prognosis and high-risk disease in patients.64

Deletion of the short arm of chromosome 17 (del(17p)), specifically at the TP53 locus, 17p13.1, is recognized as a significant adverse cytogenetic marker in MM.65 Del(17p) is among the most detrimental prognostic factors in MM, and it contributes to the classification of stage 3 disease as per the revised International Staging System (R-ISS).4 In MM, TP53 abnormalities have a frequency distribution of approximately 8% for deletion, around 6% for mutation, and about 4% for biallelic inactivation. The acquisition of a second detrimental alteration to TP53, often called a “second hit”, is suggested to be a significant step towards increased drug resistance and the risk of MM spreading outside the bone marrow.66 Biallelic inactivation of TP53, which typically results from either a homozygous deletion or a combination of deletion on one allele and mutation on the other, leads to the complete loss of p53 protein function. Given that TP53 is a crucial tumor suppressor, its impairment, coupled with genetic changes that heighten cell proliferation, likely paves the way for the rapid outgrowth of MM subclones resistant to treatment. This scenario significantly worsens clinical outcomes and elevates the risk of a second relapse.67

Deletion of the short arm of chromosome 1 (del(1p)) is another strong predictor of poor outcome in MM patients, particularly those undergoing autotransplant.25,68 Among patients with NDMM, approximately 11% harbor a focal deletion of 1p32, which is considered the second worst abnormality in MM after del(17p) in terms of prognostic significance.69,70 Biallelic deletion of 1p32, which involves both copies of a particular region on chromosome 1p, defines an ultra-high-risk group of MM with a median OS of only 25 months.69 Even monoallelic del(1p32) is a strong prognostic factor, with a median OS of 60 months. Del(1p32) is often found in conjunction with other high-risk cytogenetic abnormalities such as del(17p), t(4;14), or gain(1q). When associated with these abnormalities, the OS of patients with del(1p32) significantly decreases. Chromosome 1p/q abnormalities are also highly associated with chromosome 13/13q deletions.68 While the specific driver or relevant genes in 1p have not been validated, studies have shown deletions of FAM46C at 1p12 and CDKN2C at 1p32.3 as being associated with poor outcomes.71 In particular, FAM46C functions as a tumor suppressor and is an active non-canonical poly(A) polymerase that enhances mRNA stability, particularly for genes expressed in B-lymphocytes.72 Loss of FAM46C function due to mutations or deletions has been shown to promote cell survival and proliferation, while its reintroduction in MM cell lines induced cell death.73

The deletion of chromosome 16q (del(16q)) is a CNA observed in approximately 19.5% of NDMM patients and its presence is associated with worse OS.74 Moreover, the adverse impact on survival is further heightened when del(16q) co-occurs with other poor-risk cytogenetic factors such as t(4;14) and del(17p). LOH on 16q has been identified in three regions: the entirety of 16q, a region focused around 16q12 where the CYLD gene resides, and a region centered on 16q23, the location of the WW domain-containing oxidoreductase gene (WWOX). WWOX, a tumor suppressor gene involved in apoptosis, shows significantly reduced expression in cases with 16q LOH or t(14;16) translocations.74 The importance of WWOX is underscored by its role as the translocation breakpoint in t(14;16) cases, a recognized high-risk feature in MM. The CYLD gene, located at 16q12, is a negative regulator of the NF-kappaB pathway, a critical pathway in MM pathogenesis.75 Cases exhibiting low CYLD expression have been employed to define a “low-CYLD signature”, indicative of a poor prognosis. Both genes, WWOX and CYLD, and their corresponding pathways offer vital insights into how 16q LOH may confer a poor prognosis in MM patients. Disruption of these genes’ functions through deletion can trigger uncontrolled cell growth and resistance to apoptosis, thus intensifying the disease’s aggressiveness.

For other recurrent CNAs, the prevalence, driver role, and prognostic impact can vary, and in many instances, remain unclear. In our MM-PSN model, the gain of chromosome 15q emerged as a common alteration in HD patients and was significantly enriched in a subgroup of patients with concurrent t(4;14) and gain(1q).48 Multivariate cox-regression analysis revealed that gain(15q) confers a protective effect, with its presence resulting in significantly longer PFS and OS. However, the specific mechanism resulting from this alteration has not been described yet, and further investigations are needed to decipher its potential protective effect. The MM-PSN analysis also spotlighted a small subgroup of NDMM patients marked by multiple deletions, including del(16p). While no known driver potential has been ascribed to this lesion beyond its recurring nature, this region encompasses TNFRSF17, the gene encoding BCMA, a significant target of immunotherapies like CAR T cells and bispecific antibodies. Patients with del(16p) are at an elevated risk of biallelic loss of BCMA, which has been demonstrated to trigger resistance to anti-BCMA CAR T and bispecific therapies in MM.76

Structural Variants

Beyond CNAs, which primarily involve changes in copy numbers, structural variants (SVs) encompass a broader range of chromosomal rearrangements that disrupt gene function and regulatory networks. These SVs introduce additional layers of complexity to the genomic architecture of MM. While our primary focus so far has been on translocations, it’s important to understand that SVs encompass a broader spectrum. This includes various genomic alterations, such as deletions, duplications, inversions, and complex rearrangements, each playing a critical role in the pathogenesis and progression of MM.

A recent comprehensive analysis of SVs in a large patient cohort identified 68 SV hotspots involving 17 new candidate driver genes and potential therapeutic targets such as BCMA (TNFRSF17), SLAMF7, and MCL1.77 Notably, catastrophic complex rearrangements such as chromothripsis were present in 24% of patients and were independently associated with poor clinical outcomes.

Chromothripsis is a catastrophic event leading to the shattering and random reorganization of chromosomes, resulting in copy number abnormalities. This process contributes to genomic instability, thereby accelerating tumorigenesis.78,79 Chromothripsis can cause hundreds of rearrangements within a few cell divisions, deregulating multiple drivers and generally leading to an extremely poor prognosis in NDMM.80 This event is associated with high-risk APOBEC (apolipoprotein B editing complex) mutational activity, potentially due to double-stranded breaks, TP53 inactivation, as well as NSD2 and MAF translocations due to structural alterations, telomere dysfunction, and chromosomal instability. Studies have identified 13 recurrent hotspots involving driver genes such as CDKN2C, MYC, FAM46C, and MAP3L14 where chromothripsis can occur. Notably, oscillations in copy number during these events can activate oncogenes (50%) and inactivate tumor suppressor genes (40%), creating a “double hit” scenario that rapidly propels tumorigenesis.80 Moreover, 47% of chromothripsis events deregulate at least one MM driver gene, and these events are 1.5 times more likely to occur in polyploid tumors than in diploid ones.

Templated insertions, the second most frequent complex event, involve a similar linking of translocations but are associated with gains in copy number. These events were found to be primarily involved in super-enhancer hijacking and activation of oncogenes like CCND1 and MYC. Interestingly, a recent study revealed that a significant proportion (31%) of patients had two or more putative driver events caused by a single structural event, underscoring the complexity of the genomic landscape in MM and its acquisition through key events during tumor evolution.77

The study also highlighted chromoplexy, a distinct complex event characterized by interconnected structural variant breakpoints across more than two chromosomes associated with copy number loss. Found in approximately 11% of NDMM cases, chromoplexy impacts tumor biology and evolution by concurrently causing deletion of key tumor suppressor genes on each involved chromosome. Despite its complexity, chromoplexy has been associated with a neutral prognosis.81

Role of Somatic SNVs (Single Nucleotide Variations) in Myeloma Pathogenesis

While SVs and CNAs are major forces driving the pathogenesis and progression of MM, Single Nucleotide Variants (SNVs) and Insertions/Deletions (INDELs) also contribute substantially to its genomic complexity. SNVs involve alterations of a single base pair within the DNA sequence, which, when occurring within coding regions, can induce changes in protein structure and function, potentially impacting cellular processes.

SNVs are possibly the most studied aberration in cancer. A comprehensive analysis, encompassing over 3000 tumor samples from twenty-seven cancer types, indicated that MM exhibits an average mutation rate of approximately 1 mutation per megabase (Mb), positioning it in the intermediate range of the mutation frequency spectrum.82 In our study of 450 NDMM patients, missense mutations were the most prevalent, constituting 17% of the mutations, while nonsense, splice site, and start codon mutations collectively accounted for less than 3% of the 4,013 potentially pathogenic mutations identified across 3,163 genes.83 The mutational burden varied widely, with an average of 72.77 mutations per patient. Interestingly, patients with a greater number of subclones exhibited a significantly higher mutational burden. NRAS mutations were notably impactful, influencing gene co-expression patterns, and patients with the t(14;16) MAF translocations exhibited a notably higher mutational burden, possibly due to increase APOBEC activity. While higher mutational burden is typically correlated with poor prognosis, some studies suggest that it may improve response to immunotherapy due to presence of higher load of neoantigens.84

The Integrative Onco Genomics (IntOGen) browser hosts pan-cancer mutational driver data, including from MM studies.85 IntOGen is a framework that automatically extracts comprehensive knowledge based on mutational data from sequenced tumor samples to identify cancer genes and determine their putative mechanism of action across tumor types. It predicts driver genes by using seven different methods that assess mutation count bias, mutation clustering, protein structure and domain, and functional impact for cancer driver gene identification, and then combines the output of these methods to produce a compendium of driver genes. IntOGen lists 55 driver genes in MM, including KRAS, NRAS, TP53, BRAF, and FAM46C. These findings were derived from an analysis of 1,122 mm patients across three cohorts. However, while some of these genes are known bona fide drivers of MM, others have never been experimentally validated, therefore they remain putative drivers.

Several studies have focused on identifying and characterizing recurrent SNVs in tumor suppressors and proto-oncogenes. Significant driver point mutations in key signaling pathways, including MAPK and NF-κB, were identified.86–88 These studies have mostly relied on computational analyses employing frequency-based and functional methodologies to categorize mutated genes as drivers, many of which are recognized as significant contributors in various cancer types, indicating a shared oncogenic framework across malignancies. Table 2 lists candidate SNV drivers identified in four different studies, along with information on whether they have been experimentally validated.

Table 2 Candidate and Validated SNVs in Multiple Myeloma

Below, we present some functionally validated cancer drivers found to be recurrently mutated through SNVs in MM.

BRAF, KRAS, and NRAS are part of the RAS/MAPK pathway, which is critical in regulating cell division, differentiation, and secretion. Mutations in these genes lead to the activation of downstream signaling that promotes myeloma cell proliferation and survival.114 BRAF mutations, present in about 4–5% of MM cases, often correlate with a more aggressive disease course and poorer prognosis.93,115,116 The V600E mutation, the most common, has been targeted successfully by specific inhibitors.117 KRAS and NRAS mutations, occurring in about 20–25% of patients, are typically activating and have been linked to poor responses to standard treatments.118,119 Although the prevalence of these mutations suggests potential for therapeutic targeting, results obtained in case studies indicate short-lived responses in patients treated with MAPK inhibitors, including MEK and BRAF inhibitors.120–122

CYLD is a tumor suppressor gene that functions as a negative regulator of the NF-κB and Wnt/β-catenin signaling signaling pathways, known to play a critical role in MM pathogenesis. Loss of function of CYLD, due to either mutation or deletion, can lead to dysregulated NF-κB and Wnt activity, promoting cell survival and proliferation.75 Studies have shown that CYLD mutations are associated with advanced stages of MM and may contribute to therapeutic resistance.75,123

DIS3 is an RNA exosome component implicated in RNA processing and degradation. Mutations in DIS3 disrupt its normal function, leading to the accumulation of defective RNA molecules. This disruption can contribute to MM by altering gene expression profiles that favor myeloma cell growth.43,96 Approximately 10% of MM patients harbor DIS3 mutations, which have been associated with a poor prognosis.124 Understanding the role of DIS3 in RNA metabolism could provide new avenues for targeted therapy.

The FAM46C gene, considered a tumor suppressor, is frequently mutated in MM. Mutations in FAM46C, leading to a loss of function, are associated with shorter survival in patients, suggesting its potential as a prognostic marker.7,87,125 A recent study has demonstrated that FAM46C forms a complex with the ER-associated protein FNDC3A, which modulates secretion routes and increases lysosome exocytosis, highlighting its role into the cellular remodeling of trafficking machinery in response to ER stress.126

TP53 is a key tumor suppressor gene that plays a crucial role in cell cycle regulation, DNA repair, and apoptosis. In MM, TP53 deletions and mutations are relatively rare but are associated with a highly aggressive form of the disease and a poor prognosis.111,127 The loss of p53 function allows for the uncontrolled proliferation of myeloma cells, making it a critical target for therapeutic intervention.

FGFR3, a member of the fibroblast growth factor receptor family, is involved in cell growth, differentiation, and angiogenesis. In MM, mutations in FGFR3 are associated with its translocation along with NSD2 (t(4;14)).48 Activating mutations and the overexpression of FGFR3 due to the translocation contribute to MM pathogenesis.98 Inhibitors of FGFR3 have been explored as potential treatments for patients with this genetic alteration.128,129

TRAF3 is an adaptor protein that negatively regulates NF-κB and non-canonical NF-κB signaling. Mutations or deletions of TRAF3 in MM lead to the activation of NF-κB signaling, which is a key driver of cell survival and proliferation.112 The loss of TRAF3 function is implicated in MM pathogenesis and may serve as a therapeutic target. Studies have shown that targeting NF-κB signaling can be effective, especially when combined with proteasome inhibitors.130

Mutational Signatures

Mutational signatures are distinctive patterns of DNA mutations that arise from specific mutagenic processes or DNA repair defects. Each signature reflects the unique activities of mutagenic agents or endogenous enzymatic processes involved in genomic alterations.131 The analysis of these mutational patterns can provide insights into the underlying mechanisms of mutagenesis contributing to cancer development. In MM, different mutational signatures have been identified, carrying prognostic value and revealing the contribution of various mutagenic processes.88

The APOBEC enzymes, a family of cytidine deaminases, contribute significantly to the mutational burden in MM. APOBEC signatures are particularly enriched in cases with MAF translocations, such as t(14;16) and t(14;20).48,132 They are also more prevalent in MM cases with MYC rearrangements.132 The presence of APOBEC signatures is associated with a higher overall mutation load, genomic instability, and poor clinical outcomes. MYC translocations contribute to kataegis, a phenomenon characterized by clusters of localized hypermutations, further compounding genomic instability.

Aging-related mutational signatures, caused by the spontaneous deamination of 5-methylcytosine and other age-associated DNA alterations, are more commonly observed in hyperdiploid MM.48

A mutational signature attributable to defective DNA mismatch repair (MMR) is more prevalent in patients with the CCND1 translocation and gain of chromosome 11, but is underrepresented in patients with the MAF translocation.48 A signature associated with replication by polymerase eta is enriched in patients with the NSD2 translocation, while a signature related to polymerase epsilon exonuclease (POLE-Exo) domain mutations is enriched in patients with either the MAF or the NSD2 translocation associated with gain(1q).48

A recent study identified a new mutational signature, MM1, through non-negative matrix factorization. The study found no evidence of BRCA1/BRCA2-mediated homologous recombination deficiency (HD), challenging previous assumptions that a signature associated with BRCA1 and BRCA2 bi-allelic loss and HD in solid cancers was active in MM.133,134 False positives, such as the tobacco-smoking or the UV light signatures, were ruled out using rigorous validation strategies.

Cytotoxic agents introduce hundreds of unique mutations in surviving cancer cells. Chemotherapy-related signatures are only detectable if a single cancer cell undergoes clonal expansion post-therapy. Another study identified mutational signatures associated with specific chemotherapeutic agents, such as one linked to platinum-based chemotherapy, and a newly characterized SBS-MM1 signature.135 Chemotherapy-related signatures are responsible for approximately 25.7% of all nonsynonymous mutations at clinical relapse, particularly after high-dose melphalan therapy and autologous stem cell transplant.

These studies underscore the complexity of mutagenesis in MM, revealing the interplay between various mutational processes. In particular, APOBEC-related mutational signatures suggest a DNA repair deficiency even in other translocation groups like t(11;14) and t(4;14), highlighting a broader impact on MM pathogenesis. Conversely, chemotherapy-related signatures emphasize the significant influence of treatment on the mutational landscape of relapsed MM.

Gene Fusions in MM

Most studies in MM have focused on recurrent translocations involving the IgH locus and, to a lesser extent, the IgK and IgL loci. However, recent studies have broadened the scope to investigate the global landscape of gene fusions in MM beyond Ig translocations. One notable study revealed that MM patients exhibit an average of 5.5 expressed fusion genes, highlighting a significant presence of these genetic anomalies in the disease.136 A considerable portion of these fusion genes involve kappa and lambda light chains along with IgH genes, with kappa light chains participating in more fusions than IgH. This finding suggests that Ig fusions are influenced by the underlying biology of plasma cells and the disease process, reflecting the physiological preference for kappa light chain rearrangement during B-cell maturation. The study also identified novel fusion partners of Ig genes, including B2M, TXNDC5, FOSB, JUND, and JUN.

Patients with high hyperdiploidy, characterized by a significant increase in chromosome number, showed a distinct fusion profile involving genes like UBC and CCNG2, with many intra-chromosomal fusions and an average of four per patient. Chromosome 19, particularly TPM4, was frequently identified as a common fusion partner.

Another recent study reported fusions between Ig loci and MYC or its downstream neighbor PVT1, with MYC or PVT1 usually being the 5′ partner.137 These fusions have clinical implications; patients with PVT1-IGL fusions experienced worse survival, while those with MYC-IGL fusions showed better outcomes. Additionally, 51 fusions were significantly associated with overexpression of the partner genes, including nine cancer-related genes annotated as a driver, drug target, kinase, oncogene, or tumor suppressor, such as FGFR3, MAPKAPK2, MYC, NTRK1, PAX5, PIM3, RARA, TXNIP, and NSD2.

In the MM-PSN model, TPM4-SIK1 fusions were significantly enriched in hyperdiploid patients, particularly those without trisomies of chromosome 7.48 Different fusions were also enriched in patients with the t(11;14) translocation of CCND1, including CCND1-KLF2, FOSB-KLF6, and C21orf91-CHODL. Additionally, a significant prevalence of IGK-ITGB7 fusions was identified in patients with the t(14;16) translocation of MAF, concurrent with ITGB7 overexpression. This aligns with prior research indicating that integrin-β7 plays a critical role in MM by promoting cell adhesion, migration, and bone marrow homing, which are crucial for tumor progression and potentially influence therapeutic responses.138 Recent findings also highlight the significant upregulation of ITGB7 in the t(14;16) and t(14;20) subgroups across all stages of MGUS, SMM, and MM, emphasizing its potential role in disease progression.139 In one study, patients with highy expressed ITGB7 also exhibited poor response with combination therapy.138 Furthermore, ITGB7 expression is intricately regulated by a predetermined enhancer state in primary B-cells, transitioning to an active enhancer in the t(4;14) subgroup or a super-enhancer in the t(14;16) subgroup, indicative of complex regulation by chromatin-state alterations and DNA-methylation dynamics.139

Double and Triple Hits in MM Progression

MM progression is influenced not only by individual genetic abnormalities but also by their interactions and dependencies. Double and triple hits—co-occurrences of two or three cytogenetic abnormalities—are significantly associated with disease progression and survival outcomes.140,141 In NDMM, approximately 20% of patients exhibit such multi-hit scenarios, dramatically impacting prognostic expectations.140,142 For instance, patients with single genetic abnormalities have a predicted overall survival (OS) of about 32 months, while those with double hits face a drastically reduced OS of only 6 months.

Specific combinations of cytogenetic abnormalities are recurrently observed. Common oncogenic pairs include t(11;14) and CCND1 mutations, gain(1q) with t(4;14), co-occurrence of t(4;14) with TRAF3 deletions, and of FAM46C and CDKN2C deletions.11 Biallelic deletions of tumor suppressors combined with chr(1q) amplifications have been shown to deregulate cell cycle and proliferation pathways.143 Additionally, monoallelic del(17p)/TP53, an important prognostic marker, appears in 10% of NDMM cases but is more frequent in relapsed/refractory MM (RRMM), affecting 23–45% of cases, pointing towards increasing genomic instability with disease progression.66,144

The Role of Germline Mutations in MM Risk, Pathogenesis and Progression

It has long been suggested that MM might have an inherited genetic component, with several families showing multiple cases of MGUS and MM, indicating possible autosomal dominant Mendelian transmission. Systematic epidemiological family studies, particularly in Sweden, have confirmed that first-degree relatives of patients with MM have a 2–4 times higher risk of developing MM and MGUS.145–147 These relatives also show an increased risk of other lymphoid malignancies and certain solid tumors.148,149

Genome-wide association studies (GWAS) have played a pivotal role in identifying genetic risk factors for MM, pinpointing several independent loci associated with the disease.150,151 Among these, several loci and corresponding genes stand out due to their biological relevance and potential impact on MM development. For instance, the risk allele at 3p22.1 spans ULK4, a gene encoding a serine/threonine-protein kinase involved in autophagy regulation, which is crucial for cellular homeostasis and has been implicated in cancer.152 Another significant locus is 7p15.3, which includes CDCA7L and DNAH11, with CDCA7L being implicated in cell division and potentially in MYC-mediated transformation events, a known pathway in MM pathogenesis.152 Additionally, the locus at 2p23.3 involves DNMT3A, a gene that plays a role in DNA methylation, a key epigenetic modification affecting gene expression.153 These loci, among others identified through GWAS, highlight the genetic complexity of MM and underscore the importance of specific biological pathways in its etiology.

Sequencing studies of familial cases have identified a small number of rare, high-penetrance germline variants in candidate susceptibility genes, including CDKN2A, KDM1A, USP45, ARID1A, DIS3, and EP300.151 Notably, variants in the KDM1A gene, leading to a frameshift mutation, have been confirmed to confer susceptibility to MM, highlighting the role of histone modification in MM pathogenesis.154 Similarly, a germline splice donor site variant and a germline stop-loss variant within the DIS3 gene have been associated with familial MM, underscoring the importance of RNA processing in the disease and suggesting DIS3 as an “intermediate-risk” MM susceptibility gene.155 The CDKN2A gene, known for its tumor suppressor function, has also been implicated in MM through a duplication variant, suggesting a cross-cancer predisposition mechanism.