Множественная миелома: сказка о дерегулированных факторах транскрипции.

INTRODUCTION

Multiple myeloma (MM), the second most common hematological neoplasia, is characterized by the proliferation of clonal plasma cells (PC) and is frequently preceded by two asymptomatic premalignant conditions: monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). Malignant PCs accumulate in the bone marrow (BM) and secrete high levels of monoclonal immunoglobulins, producing organ injury and adverse clinical outcomes.
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Despite significant advances in treatment, driven by proteasome inhibitors (PIs), immunomodulatory drugs (IMiDs), monoclonal antibodies, and cellular therapies, MM remains incurable, not only due to its genetic, epigenetic, and transcriptional heterogeneity but also because the mechanisms underlying disease progression are still not fully understood. This highlights an urgent need to identify novel therapeutic targets and develop innovative treatment strategies capable of addressing the challenge of incomplete responses and frequent relapses across a broad patient population.

Transcriptional dysregulation is a hallmark of oncogenesis, as aberrant activity of key TFs can rewire gene expression programs that promote uncontrolled proliferation, survival, and therapeutic resistance. In MM, this principle is particularly evident. Among the emerging research avenues in MM, TFs have gained increasing attention due to their central roles in orchestrating gene expression networks that sustain myeloma cell survival and contribute to drug resistance. Beyond well‐established master regulators such as IRF4 and MYC,
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an expanding spectrum of TFs has been implicated in essential biological processes in MM, underscoring their relevance as potential therapeutic targets. Although TFs were long considered “undruggable,” recent advances in therapeutic modalities have reshaped this view and provided new opportunities for TF‐directed interventions in MM. Accordingly, in this review, we highlight the roles of pivotal TFs in myelomagenesis and MM pathobiology, and discuss emerging strategies and future perspectives for their therapeutic targeting.

Transcription factors and the regulation of gene expression

Gene transcription is a tightly regulated process coordinated by large multiprotein complexes, including nucleosome remodelers and histone or DNA‐modifying enzymes, which ultimately also need TFs acting as coactivators or corepressors. TFs are adaptor proteins with a DNA‐binding domain (DBD) that identifies and binds to specific DNA sequences known as transcription factor binding sites (TFBSs). These sites are predominantly localized in gene‐regulatory elements, like promoters and enhancers, ensuring the assembly of the transcriptional machinery at specific loci.
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Additionally, there is a subset of DNA‐regulatory elements composed of tightly clustered multiple enhancers termed super‐enhancers (SE), which contain higher levels of transcriptional coactivators and TFBS than single enhancers, exacerbating the activation of transcription of the associated genes. These SEs enriched in TFs are commonly found near genes with cell type‐specific functions, such as the immunoglobulin (Ig) heavy‐chain ( IGH) locus in PC.
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However, beyond their physiological roles, SEs have attracted considerable interest in cancer research, as genetic and epigenetic alterations can reprogram these regulatory elements to aberrantly activate oncogenes, including MYC .
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Most of the TFs bind to already accessible chromatin regions, where they can facilitate or avoid the binding of additional regulatory proteins, classifying TFs as transcriptional activators or repressors, respectively. Through these interactions, TFs recruit other chromatin‐modifying enzymes that ultimately promote or repress gene transcription. Moreover, TF activity is dynamically regulated by multiple signaling pathways that influence TF transcription, translation, and posttranslational modifications (PTMs), thereby modulating their abundance, localization, or functional state. Notably, PTMs regulate TF activation or inactivation without altering DNA‐binding specificity.
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For example, signaling through JAK tyrosine kinases activates STAT TFs via phosphorylation, leading to their nuclear translocation and transcriptional activation of target genes.
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In contrast, phosphorylation of FOXO TFs by the PI3K–AKT pathway results in their nuclear exclusion and functional inactivation.
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Although most TFs bind preferentially to accessible chromatin, a distinct subset, known as pioneer transcription factors, can recognize their cognate DNA motifs within condensed heterochromatin and initiate chromatin opening.
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Recent studies have shown that pioneer TF binding is influenced by the epigenomic landscape, including histone modifications, and that these factors recruit chromatin remodelers to promote nucleosome depletion and facilitate the subsequent binding of nonpioneer TFs. Hence, pioneer TFs play critical roles in physiological processes such as embryonic development and cell differentiation, and are also key drivers of transcriptional reprogramming during tumorigenesis.
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Beyond their individual binding activity, TFs frequently act cooperatively, forming dynamic regulatory complexes that enhance DNA‐binding specificity and transcriptional precision. Such cooperativity allows multiple TFs to bind adjacent motifs within promoters, enhancers, or SEs, stabilizing each other's occupancy and amplifying gene expression. Combinatorial TF binding is a hallmark of cell type‐specific transcriptional programs and contributes to the formation of SE architecture by recruiting high densities of coactivators such as Mediator and BRD4. These coordinated interactions ensure robust activation of lineage‐defining genes and facilitate the recruitment of chromatin remodelers that maintain accessible regulatory landscapes. Such cooperative networks are particularly relevant, for example, in B‐cell differentiation, where the interplay among lineage‐specific TFs orchestrates the transition from progenitors to antibody‐secreting PCs.
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Transcription factors in B‐cell development

The relevance of TFs to MM pathogenesis can be attributed, in part, to their essential roles in B‐cell differentiation into PCs, a tightly regulated process governed by lineage‐specific TF networks. Their precise temporal expression prevents hematopoietic disorders during rapid proliferation and DNA repair, while ensuring functional B‐cell maturation.
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Throughout B‐cell differentiation, coordinated and sequential TF activity directs lineage commitment, Ig gene rearrangement, and terminal differentiation into antibody‐secreting PCs.

During hematopoiesis, hematopoietic stem cells (HSCs) generate common myeloid progenitors and common lymphoid progenitors (CLPs), the latter differentiating into B‐lineage cells within the BM. Pro‐B cells initiate IGH rearrangement and expand clonally into pre‐B cells, which subsequently complete light‐chain recombination to form mature naïve B‐cells (NBCs). NBCs then migrate to lymph nodes, where germinal center reactions involve somatic hypermutation and class switch recombination, ultimately yielding antibody‐producing PCs or memory B‐cells.
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Interestingly, in this hematopoietic differentiation, lineage fate decisions are tightly regulated by TFs, including PU.1, CEBPA, and IKZF1, in early hematopoiesis. High levels of PU.1 and CEBPA promote myeloid gene expression, whereas reduced PU.1 activity favors B‐cell differentiation. IKZF1 is persistently expressed, regulating lymphoid gene programs and V(D)J recombination in Ig genes. In parallel, E2A is required to maintain the HSC pool and activates key lymphoid genes, including IL7R , EBF1 , and PAX5 .
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IL‐7 produced by BM mesenchymal progenitors induces JAK/STAT signaling, promoting CLP survival and inducing EBF1 expression. EBF1 represses non‐B lineage genes and activates PAX5, the master regulator of B‐cell identity, which controls Ig gene recombination and the expression of B‐cell–specific genes such as CD19 and IRF4 .
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IRF4 regulates lymphocyte proliferation and, together with IRF8 and FOXO1, orchestrates Ig light‐chain recombination and PC differentiation by repressing BCL6, thus enabling activation of the BLIMP1–XBP1 axis required for antibody secretion.
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Additionally, reduced MYC expression contributes to the establishment and maintenance of quiescence of long‐lived PCs
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(Figure  1 ).

Role of TFs in B lymphopoiesis and plasma cell differentiation . Hematopoietic stem cells (HSC) divide into two progenitors: the common myeloid progenitor (CMP) and the common lymphoid progenitor (CLP). Then, part of the CLPs stays in the bone marrow (BM) and can differentiate into B‐cells, resulting in Pro‐B cells, which undergo the immunoglobulin (Ig) heavy‐chain (IGH) rearrangement. Upon Ig light‐chain rearrangement, Pre‐B cells give rise to naïve B‐cells (NBCs) that can egress from the BM to the lymph nodes to be activated in the germinal center (GC). Within the GC, centroblasts (CBs) proliferate and are subjected to Ig somatic hypermutation (SHM) and then, nondividing centrocytes (CCs) undergo Ig class switch recombination (CSR). Finally, CC will give rise to memory B‐cells (MBCs) or plasma cells (PCs). Finally, aberrant changes in these TFs can drive the transformation of PCs into malignant multiple myeloma PCs. This process is tightly regulated by stage‐specific TF expression, shown in blue, red, or black. Colors indicate the relative expression changes across B‐cell differentiation stages for each protein individually and are not comparable between different proteins.

Collectively, TFs are crucial for proper B‐cell differentiation and acquisition of PC identity. However, their deregulation can disrupt tightly controlled maturation programs, leading to pathological states such as MM. Exploration of these deregulation mechanisms is essential to understand the role of TFs in MM disease and progression.

Deregulation mechanisms of transcription factors in MM

The expression and activity of TFs in MM can be deregulated through different genetic and epigenetic mechanisms. Genetic alterations constitute a major source of TF deregulation. The most recurrent cytogenetic abnormalities in MM, also observed in MGUS and SMM, are chromosomal translocations, particularly those involving the IGH locus, whose SE drives high transcriptional output. Translocations juxtaposing IGH or other regulatory regions with partner genes lead to their pathological upregulation, as illustrated by several TFs listed in Table  1 .
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Additional structural abnormalities, including chromosomal segment amplifications and deletions, further modulate TF dosage, paralleling focal copy‐number changes or hotspot mutations that alter chromatin regions controlling disease‐driver TFs, summarized in Table  1 ,
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(Figure  2A ).

Table 1 Examples of TFs deregulated by distinct mechanisms in MM. Regulation mechanism Affected TF Relevance in MM References Genetic alterations Chromosome translocations MAF and MAFB t(14;16) and t(14;20), involving the IGH locus, are present in 5% and 1% of MM patients and produce the overexpression of MAF and MAFB . [ 3 , 35 , 36 , 37 , 38 ] MYC
MYC rearrangements involving IGH , IGL, and IGK loci, leading to overexpression, are found in 50% of MM patients. [ 1 , 39 , 40 ] IRF4 t(6;14) is present in 1‐3% of MM patients and juxtaposes the IGH locus to IRF4 , leading to its overexpression. In these cases, IRF4 would not only be an essential lineage‐specific TF but also an oncogenic driver of MM. [ 41 , 42 ] Chromosome amplifications and deletions BCL9 and PBX1 Gain of the long arm of chromosome 1 is found in 35%–40% of MM patients, driving the overexpression of approximately 679 genes, including TFs BCL9 and PBX1 . [ 1 , 39 , 43 ] RB1/E2F1 del(13q), monosomy of chromosome 13, or biallelic inactivation of the RB1 gene, located in this chromosome region, are present in 45%–50% of MM patients and lead to the downregulation of 68 genes, including RB1 , a transcriptional corepressor that binds to the E2F1 TF, modulating its function. [ 1 , 39 , 44 ] p53 del(17p), biallelic inactivation or mutations in the TP53 gene drive the downregulation or total loss of p53 TF. [ 39 ] Focal copy number alterations MYC Gain of 8q24.21, where MYC is located, is present in 14% of MM patients. [ 1 , 40 ] Point mutations IRF4 IRF4 activation is driven by the K123R mutation. [ 41 ] Epigenetic alterations Altered expression KLF2, PRDM1, IRF4, and MYC KDM3A/B and KDM6A histone demethylases, and EHMT2 (G9a), EHMT1 (GLP), and DOTL1 histone methyltransferases regulate histone marks, resulting in the overexpression of KLF2 , PRDM1 , IRF4 , and MYC . [ 45 , 46 , 47 , 48 ] IRF2 The chromatin region of IRF2 in MM cells presented increased accessibility and activation compared to healthy PCs, thereby increasing the average expression of IRF2 in this disease. [ 49 ] IRF4 and MYC SE activation in MM boosts the expression of IRF4 and MYC . [ 40 , 50 ] Altered activity FLI1 FLI1 binds to de novo active chromatin regions within an essential SMILO lncRNA, regulating its expression. [ 51 ] IRF2 IRF2 binds to several newly activated chromatin regions associated with genes involved in relevant signaling pathways like cell survival and migration. [ 49 ] BCL11A, BATF, EBF1, and PAX5 Their TF‐binding sites overlap with DNA hypermethylated regions in MM. [ 52 ] Other regulation layers Fusion transcripts FOSB Its expression or activity may be altered. [ 53 , 54 ] Alternative promoters ARID5B Its expression or activity may be altered. [ 55 ] Noncoding RNA miR‐125b‐5p It downregulates IRF4 expression in MM, in turn affecting the expression of its downstream effectors like BLIMP1 and MYC . [ 56 ] lnc‐17‐92 Its binding to MYC is necessary to form the MYC–WDR82 transcriptional complex and promote ACACA gene expression. [ 57 ] H19 This lncRNA is essential for the activation of the NF‐κB signaling pathway and its downstream transcriptional program. [ 58 ]
Note : Summary of TFs altered through genetic, epigenetic, or additional regulatory mechanisms in MM, leading to aberrant expression or activity with functional relevance in disease pathogenesis. Abbreviations: del, deletion; t, translocation. John Wiley & Sons, Ltd.

Examples of TFs deregulated by distinct mechanisms in MM.

Note : Summary of TFs altered through genetic, epigenetic, or additional regulatory mechanisms in MM, leading to aberrant expression or activity with functional relevance in disease pathogenesis.

Abbreviations: del, deletion; t, translocation.

Mechanisms regulating the expression and function of TFs in MM . (A) Cytogenetic alterations modifying TF expression: schematic representation of physiological gene expression (healthy, top) and aberrant gene expression (disease, bottom) resulting from chromosome amplifications, translocations, mutations, or deletions. (B) Epigenetic alterations converting closed chromatin regions (healthy, top) into open regions (disease, bottom), leading to the emergence of new TF‐binding sites (TFBS) and/or increased TF expression. (C) DNA methylation can alter the activity of TFs. For instance, DNA hypomethylation allows the binding of TFs to their TFBS, resulting in normal gene expression (healthy, top), whereas DNA hypermethylated regions in TFBS impede the binding of TFs, affecting gene expression (disease, bottom). (D) Fusion transcripts and alternative promoter usage generating novel TF isoforms with altered functions or promoting TF overexpression, together with an example of one of the functions of noncoding RNAs: an aberrant lncRNA plays a role as a scaffold for two TFs, driving its interaction and promoting their downstream transcriptional programs (healthy, top; disease, bottom).

Epigenetic deregulation also plays a central role in modifying the expression and activity of TFs in MM. Aberrant activity of chromatin‐modifying enzymes reshapes chromatin accessibility, altering the expression of TFs and their binding landscapes. In line with findings in other cancers, MM shows extensive enhancer remodeling, including the emergence of SEs that amplify transcription of essential TFs for myeloma biology. These changes can both disrupt the normal expression of TFs and permit their binding to previously inaccessible loci. Recent studies have shown that certain TFs bind de novo active chromatin regions, marked by acetylation in MM, but absent in healthy PC, which are associated with genes involved in MM‐relevant signaling pathways (Figure  2B ). Similarly, alterations in DNA hypermethylation in MM can hinder the DNA‐binding ability of TFs (Figure  2C ). Representative TFs affected by these epigenetic mechanisms are listed in Table  1 .
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Beyond these established genetic and epigenetic drivers, emerging evidence points to additional layers of TF regulation in MM. Notably, several TFs have been reported as partners in fusion transcripts or as regulated by alternative promoters, potentially altering their expression or functional output, and revealing underexplored regulatory mechanisms requiring further study (Figure  2D ). Finally, the noncoding RNA landscape has also been put forward, as different microRNAs (miRNAs) and long noncoding RNAs (lncRNAs) are able to modify the activity of TFs (Figure  2E and Table  1 ,
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Collectively, these findings underscore the disease‐specific relevance of the deregulation of TFs in MM, highlighting diverse mechanisms that extend far beyond their canonical regulatory roles.

The relevance of transcription factors in MM

Understanding how TFs shape myeloma biology provides essential insights into disease mechanisms and reveals potential therapeutic vulnerabilities. TFs in MM include both classical oncogenic drivers and lineage‐specific regulators. While oncogenic TFs such as MYC or MAF are frequently deregulated and drive tumor progression, lineage‐specific TFs including IRF4, PRDM1, and XBP1 constitute essential survival dependencies, representing disease‐specific therapeutic vulnerabilities. In the following sections, we summarize the most relevant TFs and TF families functionally implicated in this plasma cell dyscrasia.

MYC, IRF family, IKZF1/3, and KLF2

In MM, a limited set of TFs ‐MYC, IRF4, IKZF1/3, and KLF2‐ constitutes a core regulatory circuitry that maintains the malignant PC phenotype and sustains cell survival. These TFs engage in reciprocal regulatory loops that reinforce each other's expression and activity, establishing a state of transcriptional dependency often referred to as myeloma addiction. Disruption of this circuit causes MM cell death, underscoring their functional interdependence.

MYC is a well‐established oncogenic TF that regulates approximately 15% of human genes and is frequently overexpressed in MM. It orchestrates diverse tumorigenic programs, including cell growth, DNA replication, metabolism and modulation of the immune microenvironment, leading to a strong MYC dependency of MM cells.
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Furthermore, MYC has long been implicated in MM development and progression from premalignant states like MGUS.
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Interestingly, MYC expression is regulated by the TF IRF4, and both have been described as essential proteins for MM cell survival.
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The dependency of MM cells on IRF4 extends beyond MYC regulation, as IRF4 controls additional target genes involved in metabolism, cell cycle progression, and apoptosis, including the pro‐apoptotic proteins BMF and BIM.
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IRF4 is indispensable for lymphocyte activation and PC differentiation, and its inhibition leads to MM cell death independently of the molecular subtype.
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In turn, certain TFs have been identified as IRF4 modulators, underscoring that both IRF4 and its regulators represent essential nodes for MM cell survival. This is exemplified by IKZF1 and IKZF3, key TFs in lymphopoiesis that control the transcription of both IRF4 and MYC , and their inhibition results in MM cell death.
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Strikingly, IMiD‐mediated downregulation of IKZF1/3 and IRF4 has been associated with increased expression of membrane factors recognized by NK cells, suggesting a potential role for these transcription factors in immune evasion mechanisms.
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Likewise, the TF KLF2 contributes to PC homeostasis and, although its role in MM remains incompletely defined, participates in a positive autoregulatory loop with IRF4. KLF2 promotes IRF4 transcription and is reciprocally regulated by IRF4. Notably, KLF2 knockdown induces apoptosis in MM cells and disrupts cell homing to the BM.
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Moreover, KLF2 has also been implicated in the EGFL7–ITGB3 signaling pathway, which mediates crosstalk between MM cells and the BM microenvironment, promoting drug resistance by enhancing integrin‐dependent adhesion.
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Some studies suggested that, beyond IRF4, additional members of the IRF family members may play important roles in MM, given its binding to active chromatin‐regulatory regions.
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For instance, IRF5 knockdown induces MM cell death, albeit its function is not yet characterized, as it cannot be found in the nucleus under basal conditions, suggesting that it plays an essential role other than the regulation of transcription.
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Interestingly, a genome‐wide CRISPR/Cas9 library screening performed across 19 MM cell lines subsequently identified IRF2 as a novel MM dependency.
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A recent study further elucidated the role of IRF2 in MM biology, demonstrating that its inhibition induced necroptosis‐mediated cell death and reduced MM cell migratory capacity. Besides, IRF2 target genes were already dysregulated in MGUS and SMM premalignant states, suggesting a potential role for IRF2 in disease progression. This study also highlighted that IRF1 was found in cooperation with IRF2 in several chromatin regions, although its inhibition did not affect MM cell fitness.
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Together, these findings expand the concept of the IRF–IKZF–KLF–MYC axis as the transcriptional backbone of myeloma, integrating lineage identity programs with oncogenic signaling and epigenetic plasticity (Figure  3 ).

Most relevant TFs and their main roles in MM . Representative figure of the most important families of TFs for the pathobiology of MM, including some examples of specific TFs and their roles, such as promoting cell proliferation and survival, sustaining plasma cell (PC) functions, maintaining the homeostasis of endoplasmic reticulum (ER) stress, drug resistances, and interaction with bone marrow (BM) stromal cells.

AP‐1 complex (MAF, ATF, FOS, and JUN)

The activator protein‐1 (AP‐1) complex represents a versatile and context‐dependent regulatory hub composed of members of the MAF, ATF, JUN, and FOS TF families. AP‐1 proteins act downstream of multiple signaling cascades, including MAPK, ERK, and JNK pathways, thereby translating extracellular and microenvironmental stimuli into transcriptional programs that promote myeloma cell survival, proliferation, and drug resistance. Accumulating evidence supports a central role for AP‐1 signaling in the pathobiology of MM. For instance, MAF is a TF aberrantly expressed in MM and activates the transcription of genes involved in cell cycle progression, invasion, and metastasis of cancer cells.
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The inhibition of MAF induces MM cell death,
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which could be partly attributed to its role in the transcriptional activation of CCND2 , the protein that drives the transition into the S phase of the cell cycle. In addition, MAF regulates integrin β7 expression, thereby facilitating interactions between MM cells and BM stromal cells, contributing to the malignant phenotype of the tumor microenvironment.
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In MM, MAF has also been implicated in cell invasion and metastasis through transactivation of ARK5 , a downstream effector of AKT signaling, previously related to these malignant pathways.
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Besides, MAF has been described as pioneer TF in MM, given its ability to open transcriptionally inactive chromatin, inducing the expression of genes once again related to cell proliferation and migration.
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Clinically, MAF overexpression in MM patients harboring the t(14;16) translocation has been associated with resistance to PIs such as Bortezomib. This resistance is partly explained by PI‐mediated disruption of GSK3β‐dependent degradation of MAF and MAFB, contributing to MM cell growth and PI resistances.
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In addition to classical AP‐1 components, other MAF family members that do not participate directly in the AP‐1 complex, including MAFK and MAFG, have recently been proposed as essential for MM cell survival, although their role is as yet uncharacterized.
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Conversely, the AP‐1 family member JUN is expressed at low levels in malignant PCs, and its upregulation has been associated with MM cell death. Some studies have demonstrated that JUN directly modulates the expression of EGR‐1 , leading to downregulation of survivin and induction of caspase‐dependent apoptosis.
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In addition, JUN enhances TP53 expression, triggering apoptosis in MM cells.
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Otherwise, other JUN family members have been related to MM cell proliferation, as is the case of JUND
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and JUNB. The overexpression of the latter in MM cells has been linked to interactions with the tumor microenvironment and contributes to resistance to glucocorticoids and bortezomib. JUNB also directly regulates the expression of angiogenic factors such as VEGF and IGF1 . Its silencing disrupts apoptosis, cell cycle progression, and NF‐κB and MAPK signaling, and is associated with increased sensitivity to selected therapies and reduced angiogenesis.
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This highlights the distinct and context‐dependent roles of AP‐1 components in MM biology.

Other studies revealed that the members of the FOS family, within the AP‐1 complex, participated in the myeloma bone disease via the NCX1/JNK/FOS/NFATc1 pathway, which promotes RANKL expression in MM cells to induce osteoclast differentiation.
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FOS and FOSB have been recently identified as essential genes for MM survival.
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Notably, FOS has also been shown to co‐occupy certain regulatory regions together with IKZF1 and IKZF3, regulating key genes essential for MM survival, such as IRF4 and SLAMF7 . Consequently, elevated FOS expression has been associated with resistance to IKZF1/3‐targeting agents, such as lenalidomide.
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Under specific conditions, ATF4 can form heterodimers with FOS and JUN proteins, integrating into AP‐1–like transcriptional complexes. This TF binds to chromatin‐active regions and SE associated with MM dependency genes, and its silencing affects MM cell growth.
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Among the basic leucine zipper ATF‐like factors, BATF, together with BATF2 and BATF3, has been implicated in resistance to IMiDs and EP300 inhibitors. When complexed with JUNB as part of the AP‐1 complex, BATF interacts with IRF4 and sustains MYC and IRF4 expression during treatment, promoting MM cell survival.
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Collectively, the AP‐1 network functions as a dynamic and stress‐responsive transcriptional module that interfaces with key myeloma regulators such as IRF4, MYC, and IKZF proteins, thereby reinforcing pathways that support cell survival, adaptation, and drug resistance. Through its flexible dimer composition and inducible activity, AP‐1 confers transcriptional plasticity to MM cells, enabling them to adapt to fluctuating cellular stress and therapeutic pressure (Figure  3 ).

PRDM1 and XBP1

PRDM1 (also known as BLIMP1) is a transcriptional repressor that silences B‐cell–specific gene programs during terminal differentiation, thereby maintaining PC features.
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In MM, PRDM1 is crucial for the survival of long‐lived PCs in the BM, and its knockdown leads to the reduction of the pro‐survival factor MCL1 and the upregulation of BIM, ultimately inducing MM cell death.
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Similarly, XBP1 is a key TF that governs the unfolded protein response to relieve the endoplasmic reticulum (ER) stress generated by the high demand for Ig protein production in PCs. Accordingly, XBP1 overexpression is critical for MM cells to regulate ER homeostasis and support cell survival, and this TF has therefore been widely proposed as a promising therapeutic target.
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MEF2, FOX, PBX, ETS, and RUNX families

Several studies have shown that binding sites for specific TF families are enriched within active promoters, enhancers, and SEs in MM, highlighting their potential regulatory relevance. Some of these TFs have already been demonstrated to play critical roles in MM biology, including the previously discussed MYC, IKZF, AP‐1, and IRF families, as well as additional TF families such as MEF2, FOX, ETS, and RUNX.
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MEF2A is upregulated in MM patients and has been related to several pathways underlying myeloma development, including cell proliferation, apoptosis, cell cycle, and cell migration. Notably, this TF also regulates the expression of VEGF , modulating the pro‐angiogenic activity of malignant PCs within the tumor microenvironment.
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Other MEF2 family members, such as MEF2C and MEF2D, have been identified as downstream effectors of the MAPK–ERK5 signaling cascade, which regulates MM cell proliferation.
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Although their precise roles in MM remain incompletely characterized, a recent CRISPR‐based TF library screening demonstrated that MEF2D is essential for MM cell viability, highlighting this factor as a potential novel therapeutic target.
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The FOX family comprises a large group of TFs that have long been implicated in MM pathobiology. FOXK2 regulates the expression of glycolytic enzymes, thereby promoting energy uptake and cell proliferation in MM.
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Besides, FOXK2, together with its family partner FOXK1, has been shown to be critical for MM survival.
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FOXO4 is also upregulated in MM,
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while FOXP1 and FOXP2 are aberrantly expressed in MGUS and MM compared to healthy PCs,
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suggesting a potentially important, yet uncharacterized, role for these TFs in MM pathogenesis. In addition, FOXM1 interacts with the Rb–E2F axis to promote cell cycle progression, and its upregulation has been associated with tumor progression and relapsed MM patients.
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Strikingly, FOXM1 expression, and consequently E2F activity, can be regulated by the PBX1 TF, which is upregulated in MM cases harboring gain(1q) alterations, and may explain the increased proliferation rate in these cells.
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The ETS family comprises several TF members, among which FLI1 and ETV4 are the most extensively studied in MM. FLI1 has been shown to co‐bind with IRF4 at several active chromatin‐regulatory elements of MM such as enhancers and SE, suggesting its important role in regulating central pathways for malignant PC biology. Accordingly, FLI1 knockdown triggered MM cell death, which may be explained by ChIP‐seq data revealing FLI1 occupancy at key regulatory loci, including IRF4 and PRDM1, master regulators of MM pathology.
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Interestingly, reverse‐ChIP data from a recent study identified that FLI1 is upregulated in MM and binds to de novo active chromatin regions associated with an essential lncRNA for MM cell survival, SMILO , and its inhibition reduced the expression of this lncRNA.
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In parallel, the ETS family member ETV4 has been implicated in resistance to IMiDs in MM. Following IMiD‐induced depletion of IKZF1, ETV4 occupies IKZF1‐binding sites, functionally compensating for its loss and sustaining myeloma cell survival.
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Finally, several members of the RUNX TF family have been described implicated in MM pathobiology. RUNX1 and RUNX3 contribute to IMiD resistance in MM through their direct interaction with IKZF1 and IKZF3. The formation of RUNX–IKZF complexes protects IKZF1/3 from IMiD‐induced degradation, whereas RUNX inhibition restores the sensitivity of MM cells to therapy.
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In parallel, RUNX2 promotes MM cell survival by activating the Akt/β‐catenin/survivin signaling axis and inducing the expression of metastasis‐associated genes. Moreover, RUNX2 contributes to myeloma‐associated bone disease by enhancing osteoclast differentiation and bone lesion formation in the BM.
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Accordingly, targeting RUNX2 in vivo results in reduced tumor burden and fosters a more antitumoral BM niche
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(Figure  3 ).

p53 and GFI1

The involvement of the tumor suppressor TP53 gene in multiple cancer types has been extensively documented. p53 functions as a transcriptional regulator whose loss impairs the expression of DNA repair genes, thereby influencing DNA damage‐mediated cell cycle arrest and apoptosis.
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However, the role of p53 in tumor progression is not limited to this mechanism. Mutations in TP53 have been associated with gain‐of‐function activities in multiple cancers
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and are increasingly being suggested in MM. TP53 mutations have been associated not only with a more proliferative phenotype in malignant PC but also with increased treatment resistance. Recent evidence, however, suggests that these alterations may confer sensitivity to specific therapies, although the transcriptional reprogramming driven by TP53 mutations remains incompletely understood.
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Additionally, it is known that p53 loss can also induce the expression of oncogenic genes such as GFI1 . Notably, GFI1 acts as a transcriptional repressor that promotes myeloma cell survival by silencing pro‐apoptotic genes. Accordingly, GFI1 inhibition restores the expression of these genes, induces MM cell death, and enhances sensitivity to bortezomib‐induced apoptosis. Moreover, GFI1 overexpression in MM cells has been associated with increased osteoclast‐mediated bone lesions in murine models.
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Altogether, the p53–GFI1 axis exemplifies how transcriptional deregulation connects genomic instability with MM pathogenesis and bone disease (Figure  3 ).

Collectively, all these TFs establish a multilayered regulatory landscape in MM, integrating genomic alterations, epigenetic remodeling, and signals from the tumor microenvironment. Elucidating how these TF networks interact, cooperate, and compensate for one another is crucial for identifying synthetic vulnerabilities and improving therapeutic strategies. The functional roles of the TFs discussed in this section are summarized in Table  2 .

Table 2 Key TFs in MM. TF name Activity Role in MM biology References MYC Up
Regulates cell growth, DNA replication, metabolism, and modulation of the immune microenvironment.
It is related to MM development and progression from MGUS and SMM premalignant states.
It is essential for MM cell viability.
[ 10 , 40 , 59 , 60 , 61 , 62 , 63 ] IRF4 Up
Regulates the expression of MYC and genes involved in metabolism, cell cycle, and cell death.
It is essential for MM cell viability.
[ 9 , 10 , 41 , 64 ] IKZF1 and IKZF3 Up Control the transcription of IRF4 and MYC , thereby being essential for the viability of MM. [ 65 , 66 ] KLF2 Up
Regulates PC homeostasis and presents a positive autoregulatory loop with IRF4.
Its knockdown induces apoptosis.
Involved in drug resistances via the crosstalk between MM cells and the BM microenvironment.
[ 68 , 69 ] IRF5 Expressed Its knockdown leads to MM cell death. [ 49 ] IRF2 Up
MM dependency.
Its inhibition triggers necroptosis cell death and reduces cell migration.
Its target genes are dysregulated in MGUS, SMM, and MM cells.
[ 49 , 71 ] MAF Up in t(14;16)
Part of the AP‐1 complex.
Controls genes involved in cell cycle, invasion, and metastasis of cancer cells.
Its silencing leads to MM cell death.
Participates in the interaction between MM cells and BM stromal cells, promoting malignant tumor microenvironment.
Opens transcriptionally inactive chromatin in genes related to cell proliferation and migration.
Its expression correlates with resistance to PIs.
[ 35 , 49 , 72 , 73 , 74 , 75 , 76 ] MAFK and MAFG Expressed Described as dependencies of MM. [ 49 ] JUN Down
Part of the AP‐1 complex.
Its upregulation is linked to MM cell death.
Regulates caspase‐dependent apoptosis.
Enhances TP53 expression, triggering apoptosis in MM cells.
[ 77 , 78 ] JUND and JUNB Expressed
Part of the AP‐1 complex.
Related to MM cell proliferation.
JUNB inhibition leads to the dysregulation of apoptosis, cell cycle, NF‐κB, and MAPK signaling pathways, along with enhanced sensitivity to specific therapies and reduced angiogenesis.
[ 49 , 79 , 80 ] FOS Expressed
Part of the AP‐1 complex.
Involved in MM bone disease through osteoclast differentiation.
Co‐operates with IKZF1/3 to regulate essential genes for MM like IRF4 and SLAMF7 .
Its expression is linked to lenalidomide resistances.
[ 6 , 49 , 81 ] FOSB Expressed Part of the AP‐1 complex, and its knockdown leads to MM cell death. [ 49 ] ATF4 Expressed
Part of the AP‐1‐like complex.
Regulates the expression of MM dependency genes.
Its silencing affects MM cell growth.
[ 49 , 82 ] BATF, BATF2 and BATF3 Expressed
Implicated in resistance to IMiDs and EP300 inhibitors.
BATF along with JUNB, forming the AP‐1 complex, sustains MYC and IRF4 expression, promoting MM cell survival.
[ 83 ] PRDM1 Up
Crucial for long‐lived PC in the BM.
Its knockdown reduces MCL1 , causing cell death.
[ 78 , 85 ] XBP1 Up Maintains ER homeostasis, supporting MM cell survival. [ 84 , 86 ] MEF2A Up
Controls cell proliferation, apoptosis, cell cycle, and migration in MM.
Regulates pro‐angiogenic factors like VEGF.
[ 87 ] MEF2C and MEF2D Expressed
Regulates MM cell proliferation via the MAPK cascade.
MEF2D is essential for MM cell viability.
[ 49 , 88 ] FOXK2 and FOXK1 Up
FOXK2 governs the expression of glycolytic enzymes, promoting energy uptake and cell proliferation in MM.
Both TFs are essential for MM cell viability.
[ 49 , 89 ] FOXO4, FOXP1, and FOXP2 Up
Aberrantly expressed in MM.
FOXP1 and FOXP2 dysregulated from the MGUS state, suggesting a role in disease progression.
[ 70 , 90 , 91 ] FOXM1 Up
Interacts with the Rb‐E2F axis, promoting cell cycle in MM.
Its expression is correlated with tumor progression and relapsed MM patients.
[ 92 , 93 ] PBX1 Up in gain(1q) Transactivates FOXM1 and E2F TFs, resulting in higher proliferation rates of MM cells. [ 43 ] FLI1 Up
Co‐binds with IRF4 at enhancers and SE in MM, including IRF4 and PRDM1 regions.
Regulates de novo active chromatin regions associated with SMILO , an essential lncRNA for MM.
FLI1 knockdown triggered MM cell death.
[ 50 , 51 ] ETV4 Up Implicated in resistance to IMiDs in MM through binding to IKZF1‐associated chromatin regions upon treatment. [ 94 ] RUNX1 and RUNX3 Up Contribute to IMiD resistance in MM through direct interaction with IKZF1 and IKZF3, preventing their degradation upon treatment. [ 95 ] RUNX2 Up
Drives MM cell survival through Akt/β‐catenin/survivin signaling and metastatic gene expression.
Promotes osteoclast differentiation and bone lesions in the BM.
Its targeting in vivo leads to a decreased tumor growth and an antitumoral microenvironment.
[ 96 , 97 , 98 ] p53 Down Its loss not only impairs DNA repair, affecting cell cycle arrest and apoptosis, but also induces the expression of oncogenic genes such as GFI1 . [ 1 ] GFI Up
Its inhibition increases the expression of proapoptotic genes, triggering cell death and sensitizing cells to bortezomib‐induced apoptosis.
Its expression is correlated with an increased bone lesion by osteoclast.
[ 101 ]
Note : Summary of the role of TFs in the biology of MM. The expression (activity) of TFs in MM is indicated relative to normal PCs. TFs are labeled as expressed when no specific evidence of upregulation or downregulation has been reported. Abbreviations: down, downregulated; ER, endoplasmic reticulum; IMiDs, immunomodulatory drugs; PI, proteasome inhibitor; up, upregulated. John Wiley & Sons, Ltd.

Key TFs in MM.

Regulates cell growth, DNA replication, metabolism, and modulation of the immune microenvironment.

It is related to MM development and progression from MGUS and SMM premalignant states.

It is essential for MM cell viability.

Regulates the expression of MYC and genes involved in metabolism, cell cycle, and cell death.

It is essential for MM cell viability.

Regulates PC homeostasis and presents a positive autoregulatory loop with IRF4.

Its knockdown induces apoptosis.

Involved in drug resistances via the crosstalk between MM cells and the BM microenvironment.

MM dependency.

Its inhibition triggers necroptosis cell death and reduces cell migration.

Its target genes are dysregulated in MGUS, SMM, and MM cells.

Part of the AP‐1 complex.

Controls genes involved in cell cycle, invasion, and metastasis of cancer cells.

Its silencing leads to MM cell death.

Participates in the interaction between MM cells and BM stromal cells, promoting malignant tumor microenvironment.

Opens transcriptionally inactive chromatin in genes related to cell proliferation and migration.

Its expression correlates with resistance to PIs.

Part of the AP‐1 complex.

Its upregulation is linked to MM cell death.

Regulates caspase‐dependent apoptosis.

Enhances TP53 expression, triggering apoptosis in MM cells.

Part of the AP‐1 complex.

Related to MM cell proliferation.

JUNB inhibition leads to the dysregulation of apoptosis, cell cycle, NF‐κB, and MAPK signaling pathways, along with enhanced sensitivity to specific therapies and reduced angiogenesis.

Part of the AP‐1 complex.

Involved in MM bone disease through osteoclast differentiation.

Co‐operates with IKZF1/3 to regulate essential genes for MM like IRF4 and SLAMF7 .

Its expression is linked to lenalidomide resistances.

Part of the AP‐1‐like complex.

Regulates the expression of MM dependency genes.

Its silencing affects MM cell growth.

Implicated in resistance to IMiDs and EP300 inhibitors.

BATF along with JUNB, forming the AP‐1 complex, sustains MYC and IRF4 expression, promoting MM cell survival.

Crucial for long‐lived PC in the BM.

Its knockdown reduces MCL1 , causing cell death.

Controls cell proliferation, apoptosis, cell cycle, and migration in MM.

Regulates pro‐angiogenic factors like VEGF.

Regulates MM cell proliferation via the MAPK cascade.

MEF2D is essential for MM cell viability.

FOXK2 governs the expression of glycolytic enzymes, promoting energy uptake and cell proliferation in MM.

Both TFs are essential for MM cell viability.

Aberrantly expressed in MM.

FOXP1 and FOXP2 dysregulated from the MGUS state, suggesting a role in disease progression.

Interacts with the Rb‐E2F axis, promoting cell cycle in MM.

Its expression is correlated with tumor progression and relapsed MM patients.

Co‐binds with IRF4 at enhancers and SE in MM, including IRF4 and PRDM1 regions.

Regulates de novo active chromatin regions associated with SMILO , an essential lncRNA for MM.

FLI1 knockdown triggered MM cell death.

Drives MM cell survival through Akt/β‐catenin/survivin signaling and metastatic gene expression.

Promotes osteoclast differentiation and bone lesions in the BM.

Its targeting in vivo leads to a decreased tumor growth and an antitumoral microenvironment.

Its inhibition increases the expression of proapoptotic genes, triggering cell death and sensitizing cells to bortezomib‐induced apoptosis.

Its expression is correlated with an increased bone lesion by osteoclast.

Note : Summary of the role of TFs in the biology of MM. The expression (activity) of TFs in MM is indicated relative to normal PCs. TFs are labeled as expressed when no specific evidence of upregulation or downregulation has been reported.

Abbreviations: down, downregulated; ER, endoplasmic reticulum; IMiDs, immunomodulatory drugs; PI, proteasome inhibitor; up, upregulated.

Transcription factors as prognostic biomarkers in MM

Beyond their relevant biological functions in MM, multiple TFs have emerged as potential prognostic biomarkers for patients. Altered expression levels or genetic alterations affecting these TFs frequently correlate with distinct clinical outcomes and may refine current risk‐stratification systems. In some cases, the expression of TFs is increased in high‐risk MM patients compared with standard‐risk cases, although their specific value as biomarkers has not yet been fully established. In other cases, aberrant expression of TFs has been directly correlated with unfavorable progression‐free survival or overall survival. Importantly, prognostic models that integrate the expression of TFs with recurrent genetic alterations outperform approaches based on cytogenetic data alone, underscoring the added value of TF‐based biomarkers in capturing disease heterogeneity and informing clinical decision‐making.
1
,
3
,
39
,
40
,
43
,
49
,
51
,
67
,
77
,
85
,
86
,
87
,
89
,
90
,
91
The prognostic relevance of the TFs discussed in this section is summarized in Table  3 .

Table 3 TFs as prognostic biomarkers for MM patients. TF name Regulation Prognostic impact References MYC High Translocations involving MYC are related to adverse prognosis, while gain of the MYC segment is associated with a neutral prognosis. [ 1 , 40 ] PRDM1 High Mutations have been associated with a good prognosis. [ 1 ] MAF High via t(14;16) Associated with a poor prognosis. [ 1 , 3 , 72 ] XBP1 High High levels of its active form predict lower OS in MM patients. [ 86 ] IRF4 High Translocations involving IRF4 are associated with advanced disease state and a poor prognosis, while IRF4 mutations are related to a good prognosis. [ 1 , 84 ] IRF2 High
Associated with worse PFS and OS.

IRF2 expression and genetic alterations stratified patients into 5 PFS and 4 OS risk groups.
[ 49 ] FLI1 High
Linked to unfavorable PFS and OS.

FLI1 expression with genetic alterations stratifies patients into 6 PFS and 5 OS risk groups.
[ 51 ] BCL9 High via gain(1q) Related to an unfavorable prognosis. [ 1 ] MAFB High via t(14;20) Adverse prognosis in MM, long‐term disease if it is found in the MGUS or SMM stages. [ 1 , 3 , 72 ] p53 Down or mutated Chromosome alterations and mutations of TP53 are always associated with an adverse prognosis. [ 39 ] PBX1 High via gain(1q) Linked to HR disease, worse OS, higher proliferation rates of MM PC, and progressive/relapsed disease. [ 43 ] The expression signature regulated by PBX1 is linked to an unfavorable prognosis in MM. FOXM1 High
More expressed in HR compared to standard‐risk patients. Patients with MF and PR molecular subtypes, which present worse outcomes and clinical courses, have higher expression of FOXM1 than other subgroups.
High expression linked to a subset of relapsed patients.
[ 92 , 93 ] ETV4 High It is higher in three MM subtypes –CD‐1/CD‐2, MS, and PR– which are associated with poor outcomes. Associated with poor outcomes and resistance to IMiDs treatment. [ 94 ] RUNX2 High Increased expression in patients with HR disease, although its role as a biomarker is yet to be determined. [ 96 , 97 , 98 ]
Note : Summary of the implication of TFs and their expression in the prognosis of MM patients. Abbreviations: CAN, copy number alteration; CD‐1/CD‐2: t(11;14) and CCND1‐3 molecular subtype; HR, high‐risk patient; IMiDs, immunomodulatory drugs; MF, MAF/MAFB, molecular subtype; MS, t(4;14)‐MMSET molecular subtype; OS, overall survival; PC, plasma cell; PFS, progression‐free survival; PR, proliferation molecular subtype. John Wiley & Sons, Ltd.

TFs as prognostic biomarkers for MM patients.

Associated with worse PFS and OS.

IRF2 expression and genetic alterations stratified patients into 5 PFS and 4 OS risk groups.

Linked to unfavorable PFS and OS.

FLI1 expression with genetic alterations stratifies patients into 6 PFS and 5 OS risk groups.

More expressed in HR compared to standard‐risk patients. Patients with MF and PR molecular subtypes, which present worse outcomes and clinical courses, have higher expression of FOXM1 than other subgroups.

High expression linked to a subset of relapsed patients.

Note : Summary of the implication of TFs and their expression in the prognosis of MM patients.

Abbreviations: CAN, copy number alteration; CD‐1/CD‐2: t(11;14) and CCND1‐3 molecular subtype; HR, high‐risk patient; IMiDs, immunomodulatory drugs; MF, MAF/MAFB, molecular subtype; MS, t(4;14)‐MMSET molecular subtype; OS, overall survival; PC, plasma cell; PFS, progression‐free survival; PR, proliferation molecular subtype.

Altogether, these results further emphasize the central role of TFs in the pathogenesis and progression of MM. Expression patterns of TFs reflect the biological heterogeneity of the disease and may complement conventional cytogenetic markers in prognostic assessment. Incorporation of TF‐based biomarkers such as IRF2, FLI1, PBX1, FOXM1 , and ETV4 , could therefore improve patient stratification and guide precision‐based therapeutic strategies.

From classic to cutting‐edge: Targeting transcription factors in MM

As discussed in previous sections, TFs are frequently deregulated across multiple malignancies, including MM, underscoring their potential as therapeutic targets. However, their structural and functional characteristics have historically rendered them “undruggable.”
102
Consequently, strategies to target TFs have traditionally focused on different approaches to modulate their expression or activity.
103
,
104
,
105
Notwithstanding these limitations, recent advances in RNA‐based therapies or targeted protein degradation technologies have begun to reshape this paradigm, providing new opportunities for the direct targeting of TFs in cancer.
106
,
107
,
108

Widely used strategies for targeting TFs in MM can be broadly classified into three main categories: inhibition of essential protein dependencies required for the function of the TFs,
72
,
105
,
109
modulation of chromatin accessibility at TF‐regulatory loci,
51
,
110
,
111
and regulation of TF stability through controlled degradation.
65
,
104
,
112

Targeting essential cofactors or upstream signaling pathways necessary for TF function has been proven to be effective in modulating key MM‐associated TFs, including MAF, IRF4, and XBP1. For example, inhibition of MEK1/2 proteins disrupts AP‐1 dimerization, leading to reduced MAF expression in vitro.
72
Similarly, inhibition of SWI/SNF chromatin‐remodeling components SMARCA2/4 impairs IRF4 transcriptional activity through disruption of its interaction with ARID1A.
109
Another successful example is the inhibition of IRE1α, which blocks XBP1 mRNA splicing and reduces levels of the transcriptionally active XBP1 isoform in vivo
105
(Figure  4A ).

Therapeutic strategies for targeting TFs in MM . Schematic representation of pharmacological approaches to target TFs. (A) Small‐molecule inhibitors targeting functional TF dependencies, including upstream signaling, post‐transcriptional regulators, and cofactors. (B) Epigenetic modulators and BET inhibitors (BETi) that regulate TF chromatin accessibility and transcription. (C) IMiDs and E3 ligase modulators that harness proteasomal pathways to degrade oncogenic or stabilize tumor suppressor TFs. (D) Direct inhibition of TFs by small molecules to block TF dimerization or DNA‐binding activity. (E) RNA‐based therapies, such as CRISPR/Cas9 systems delivered via functionalized lipid nanoparticles (LNPs; top) or antisense oligonucleotides (ASOs; bottom), to selectively silence TF expression. MM, multiple myeloma; TF, transcription factors.

Epigenetic remodeling has also emerged as an effective approach to restrict TF expression or limit their access to regulatory chromatin regions.
51
,
103
,
110
,
111
,
113
,
114
,
115
Bromodomain and extra‐terminal protein inhibitors (BETi) suppress IRF4 , MYC , and FLI1 expression by displacing BRD proteins from enhancers and SE that are critical for their transcription
51
,
110
,
111
(Figure  4B ). Likewise, pharmacological inhibition of both bromodomain and the histone acetyltransferase activity of CBP/EP300 interferes with enhancer function. This results in the transcriptional downregulation of IRF4 and MYC , effectively attenuating the IRF4–MYC axis.
113
,
116
Additional strategies targeting MYC exploit G‐quadruplex DNA stabilization, achieving a potent repression of MYC expression. More broadly, epigenetic inhibitors targeting HDAC1, EZH2, and G9a further demonstrate the therapeutic potential of chromatin‐based interventions to suppress IRF4 expression and impair MM cell viability.
114
,
115

Lastly, manipulation of the ubiquitin–proteasome system provides another powerful route to counteract oncogenic TF programs.
65
,
104
,
112
The canonical example involves cereblon, whose substrate specificity is redirected by IMiDs to induce selective degradation of IKZF1 and IKZF3, two TFs essential for MM cell survival.
65
,
112
Conversely, inhibition of E3 ligases that negatively regulate tumor suppressor TFs can restore beneficial transcriptional programs. For instance, inhibition of MDM2 stabilizes p53 and reactivates its tumor‐suppressive activity in malignant PCs
104
(Figure  4C ).

While these strategies have provided valuable insights and proof‐of‐concept therapeutic avenues to target TFs, they frequently rely on modulation of upstream signaling pathways or broad epigenetic mechanisms, which may result in limited specificity and off‐target effects. In contrast, novel approaches, including small‐molecule inhibitors and RNA‐based therapies, offer the potential for precise inhibition of TFs themselves, enabling more selective modulation of oncogenic transcriptional programs in MM.

The most advanced small‐molecule strategies have focused on directly disrupting TF–protein or TF–DNA interactions
72
,
102
,
117
,
118
(Figure  4D ). For example, inhibition of MYC dimerization with its partner MAX by targeting their interaction interface using the small molecule 10058‐F4 has been shown to reduce MM cell survival in vitro.
117
,
118
Similarly, small molecule 7417, which blocks PBX1 binding to its consensus DNA motifs, impairs PBX1 function and downregulates FOXM1 expression, demonstrating antimyeloma efficacy both in vitro and in vivo.
43

RNA‐based therapeutic approaches, which involve the delivery of RNA molecules to selectively regulate cancer‐specific gene expression, have emerged as a versatile strategy for directly targeting TFs in MM. Among these, antisense oligonucleotides (ASOs) are particularly promising due to their capacity for cellular uptake without the need for transfection and to induce sequence‐specific mRNA degradation. Notably, an ASO targeting IRF4 effectively prevented myeloma regeneration in preclinical in vivo models, highlighting the therapeutic potential of this approach.
107
Despite their therapeutic potential, RNA‐based molecules are often limited by poor stability, a short half‐life, and suboptimal pharmacokinetic properties, which necessitate the development of efficient delivery systems to protect them from degradation and ensure intracellular delivery. Lipid nanoparticles (LNPs) have emerged as the leading delivery platform for RNA‐based therapies. In the context of MM, more sophisticated systems using LNPs conjugated to antibodies targeting MM‐specific surface antigens, such as CD38, enable selective RNA molecule delivery to malignant PCs. In murine models, CD38‐targeted LNPs delivering Cas9 mRNA together with single‐guide RNAs against IRF4 efficiently suppressed TF expression and induced MM cell collapse,
108
providing a compelling proof of concept for in vivo CRISPR/Cas9‐mediated targeting of oncogenic TFs (Figure  4E ).

New perspectives for TF degradation in MM

Despite being key TFs for MM development, some of the aforementioned proteins are also essential for other malignancies, driving the expansion of targeted research beyond the myeloma setting. A primary example is OMO‐103, a mini‐peptide that has demonstrated potent antitumoral activity across diverse solid tumors by mimicking the MYC dimerization domain and preventing functional transcriptional complex formation.
119

Beyond established therapeutic approaches, rapid advances in targeted protein degradation technologies have generated additional strategies that, although not yet explored in MM, hold considerable promise for future TF targeting.
106
Peptide‐based proteolysis‐targeting chimeras (PROTACs) directed against FOXM1 have demonstrated that TFs can be directly eliminated through E3‐ligase recruitment, providing proof of principle that these traditionally challenging targets are amenable to induced proteasomal degradation.
120
,
121
More experimental systems, such as transcription factor targeting chimeras (TRAFTACs) or oligonucleotide‐based PROTACs, exploit DNA or RNA recognition motifs to selectively bind TFs and promote their degradation.
106
In addition, aptamer‐ and threose nucleic acid (TNA)‐DNA‐based degraders targeting MYC have demonstrated high specificity and efficacy in preclinical models, further underscoring the versatility of nucleic acid–guided degradation strategies.
122
,
123
Building upon this nucleic acid‐based versatility, inhibitory aptamers (iAptamers) are emerging as a precise tool for disrupting critical TF–cofactor protein–protein interactions, such as the MYC–WDR5 complex.
124
Collectively, these emerging technologies substantially expand the landscape of TF‐directed therapeutic interventions and may inspire innovative strategies for MM treatment.

In summary, ongoing advances in direct TF‐targeted therapies are progressively redefining TFs, transforming them from historically “undruggable” entities into actionable regulators within MM biology, and providing new opportunities for combinatorial and precision‐based therapeutic strategies. An overview of these approaches is provided in Table  4 .

Table 4 Therapeutic strategies targeting TFs in MM. Group Compound TF target Mechanism References Inhibiting TF dependencies
U0126
AZD6244
MAF MEK1/2 inhibition suppresses ERK signaling, leading to reduced MAF expression. [ 72 ] FHD‐286 IRF4 Inhibition of the SWI/SNF ATPases SMARCA2/4 disrupts IRF4 programs. [ 109 ] G‐5758 XBP1 IRE1α Inhibition prevents XBP1 splicing. [ 105 ] Modulating TF chromatin accessibility
JQ1
OTX015

IRF4
MYC
FLI1
BETi impairs enhancer function, resulting in transcriptional downregulation of IRF4 , MYC , and FLI1 . [ 51 , 110 , 111 ]
SGC‐CBP30
I‐CBP112
KB528
KB529

IRF4
MYC
Selective inhibition of CBP/p300 leads to a decreased expression of IRF4 . [ 113 , 116 ] Y502‐2304 MYC Stabilization of the G‐quadruplex structures within the MYC promoter interferes with its transcriptional initiation. [ 103 ]
GSK126
EP7‐6438
IRF4 Dual inhibition of EZH2 and G9a impairs H3K27and H3K9 methylation marks, leading to a decrease of the IRF4–MYC axis. [ 114 ] MS‐275 IRF4 HDAC1 inhibition increases histone acetylation at regulatory regions, leading to transcriptional repression of IRF4 . [ 115 ] Regulating TF degradation IMiDs
IKZF1
IKZF3
Cereblon‐binding IMiDs promote proteasomal degradation of IKZF1 and IKZF3. [ 65 , 112 ] MI‐63 p53 MDM2 inhibition disrupts p53 ubiquitination, leading to stabilization of accumulation of transcriptionally active p53. [ 104 ] Small molecules 10058‐F4 MYC Direct disruption of MYC–MAX dimerization impairs MYC activity. [ 117 , 118 ] 7417 PBX1 Inhibition of PBX1–DNA binding suppresses the PBX1–FOXM1 axis. [ 43 ] RNA‐based therapies ASO‐IRF4 IRF4 ASO‐mediated degradation of IRF4 expression and activity. [ 107 ] LNP‐CD38 (CRISPR/Cas9) IRF4 LNP‐mediated delivery of RNA guide targeting IRF4 induces gene disruption in malignant PCs. [ 108 ]
Note : Summary of the different strategies and compounds for targeting TFs in MM. Abbreviations: ASO, antisense oligonucleotide; BETi, bromodomain and extraterminal protein inhibitors; IMiDs, immunomodulatory drugs; LNP, lipid nanoparticle; MM, multiple myeloma; PC, plasma cell; TF, transcription factors. John Wiley & Sons, Ltd.

Therapeutic strategies targeting TFs in MM.

U0126

AZD6244

JQ1

OTX015

IRF4

MYC

FLI1

SGC‐CBP30

I‐CBP112

KB528

KB529

IRF4

MYC

GSK126

EP7‐6438

IKZF1

IKZF3

Note : Summary of the different strategies and compounds for targeting TFs in MM.

Abbreviations: ASO, antisense oligonucleotide; BETi, bromodomain and extraterminal protein inhibitors; IMiDs, immunomodulatory drugs; LNP, lipid nanoparticle; MM, multiple myeloma; PC, plasma cell; TF, transcription factors.

CONCLUSIONS AND FUTURE DIRECTIONS

TFs play central roles in the physiological process of B‐cell differentiation, orchestrating lineage commitment, activation, and terminal maturation into PCs. Disruption of these tightly regulated transcriptional programs through genetic or epigenetic alterations leads to aberrant TF activity, thereby contributing to initiation and disease progression of MM. In malignant PCs, deregulated TF signaling sustains survival, proliferation, migration, and invasive behavior, reinforcing transcriptional dependencies that define the myeloma phenotype. Beyond their biological significance, aberrant expression of specific TFs has been associated with adverse clinical outcomes. Importantly, integration of TF expression patterns into molecular risk models has improved patient stratification compared with conventional cytogenetic classifications. These findings highlight the dual value of TFs as both mechanistic drivers of disease and clinically relevant prognostic biomarkers. Interestingly, recent advances in targeted therapeutic strategies are increasingly challenging the long‐standing perception of TFs as “undruggable” proteins. Emerging approaches, including RNA‐based therapies and targeted protein degradation technologies, are revealing new opportunities to directly and selectively modulate TF functions that were previously inaccessible to conventional therapies. These innovations not only provide new opportunities for therapeutic intervention in MM but also raise the prospect of selectively disrupting oncogenic transcriptional dependencies while preserving normal PC function.

In summary, this review underscores the multifaceted roles of TFs in MM pathobiology and their potential as both prognostic biomarkers and actionable therapeutic targets. Continued investigation into TF‐regulatory networks, coupled with the development of next‐generation targeting strategies, will be essential for translating these advances into clinical benefit. Ultimately, such progress holds promise for the development of more precise, effective, and personalized treatment approaches for patients with MM, with the goal of improving long‐term disease control and patient outcomes.

AUTHOR CONTRIBUTIONS

Nahia Gómez‐Echarte : Conceptualization; writing—original draft; validation; visualization; writing—review and editing; data curation. Edurne San José‐Enériz : Conceptualization; funding acquisition; writing—original draft; validation; visualization; writing—review and editing; formal analysis; supervision; data curation. Estíbaliz Urizar‐Compains : Conceptualization; writing—original draft; validation; visualization; writing—review and editing; data curation. Paula Rodriguez‐Otero : Validation; conceptualization; visualization; writing—review and editing. Felipe Prósper : Conceptualization; funding acquisition; writing—original draft; validation; visualization; writing—review and editing; formal analysis; project administration; supervision. Xabier Agirre : Conceptualization; funding acquisition; writing—original draft; validation; visualization; writing—review and editing; formal analysis; supervision; project administration; data curation.

CONFLICT OF INTEREST STATEMENT

The authors declare no conflict of interest.

FUNDING

This research was funded by grants from the Instituto de Salud Carlos III (ISCIII) and co‐financed by the European Union: PI22/00947, PI23/00488, PI23/00516, PI25/01281, PMP21/00015 (PREGENLINF), and CIBERONC CB16/12/00489. Gobierno de Navarra: Department of Health (GNS_44‐2021; GN2023/11) (also co‐financed by FEDER) and Department of Economic Development 0011‐1411‐2022‐000068, 0011‐1411‐2022‐000077 (NANO‐RC), 0011‐1411‐2023‐000074, 0011‐1411‐2023‐000105 (DIAMANTE), and NANO‐Protacs, and with support from 616/C/2019 Fundació La Marató de TV3. The study was also supported by the Paula and Rodger Riney Foundation. N.G‐E. was supported by Gobierno de Navarra (0011‐0537‐2021‐000032) and FIMA AC 2020.