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ScienceDirect Genomic heterogeneity in multiple myeloma Raphae¨l Szalat1 and Nikhil C Munshi1,2 Multiple myeloma (MM) is an incurable malignancy in majority of patients characterized by clonal proliferation of plasma cells. To date, treatment is established based on general conditions and age of patients. However, MM is a heterogeneous disease, featured by various subtypes and different outcomes. Thus, the understanding of MM biology is currently a major challenge to eventually cure the disease. During the last decade, karyotype studies and gene expression profiling have identified robust prognostic markers as well as a widespread genomic landscape. More recently, studies of epigenetic, transcriptional modifications and next generation sequencing have allowed characterization of critical genes and pathways, clonal heterogeneity and mutational profiles involved in myelomagenesis. Altogether, these findings constitute important tools to develop new targeted and personalized therapies in MM. Addresses 1 Medical Oncology, Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, United States 2 VA Boston Healthcare System, Boston, MA, United States Corresponding author: Munshi, Nikhil C ([email protected])

Current Opinion in Genetics & Development 2015, 30:56–65 This review comes from a themed issue on Cancer genomics Edited by Christine A Iacobuzio-Donahue and Elaine A Ostrander

extra-copies of specific chromosomes (3, 5, 7, 9, 11, 15, 19 or 21) are present [1]. Mechanisms of chromosome abnormalities have not been clearly identified so far however, it may be due to uncontrolled recombination, specific translocation mechanisms such as jumping translocation [2,3] and abnormal somatic hypermutation. The latter mechanism is suggested by frequent involvement of both IGH and IG light chain locus [4]. Other recurrent chromosome abnormalities described are deletions (del(1p), del(6q), del(8p), del(12p), del(14q), del(13q) and del(17p) and gains (amp(5q) and amp(1q)) [5]. Of note, the del(17p) leads to TP53 deletion. 1q gain, t(4;14) and del 17p are to date the cytogenetic markers of poor prognosis [6]. Gene expression profile (GEP) studies have allowed distinguishing different subgroups of patients with different clinical and biological patterns. It has also led of identification pathways and genes critically involved in MM biology [7,8,9]. Recently, a new era has been opened thanks to new technologies such as next generation sequencing (NGS) and whole genome epigenetic profiling. Recurrent mutated genes, corresponding to oncogenes and tumor suppressor genes, and critical pathways involved in myelomagenesis have been identified. Furthermore, the clonal architecture of MM and its evolution over time in patients have been characterized. In this review, we present the current knowledge of genomic data in MM and discuss its therapeutically implications (Figure 1).

http://dx.doi.org/10.1016/j.gde.2015.03.008

Gene expression profiles

0959-437X/# 2015 Published by Elsevier Ltd.

Gene expression profiling has provided important information defining molecular subgroups and identifying genes and pathways carrying a significant impact on patient’s survival in MM. Different methods have been used to characterize GEP: including array-based expression profiling that evaluate whole transcribed genome or RNA-sequencing based studies. All of these studies identified genes that are commonly overexpressed, e.g. cyclin D genes family [10] in malignant plasma cells as compare to normal plasma cells [11] or genes that are only overexpressed in certain subgroups as MMSET in the t(4;14) MM. Importantly, some differentially expressed genes that have been identified in malignant plasma cells are present since the earliest stage of the disease (MGUS). These genes includes oncogenes, tumor-suppressor genes, cell signaling genes (RAS family members, B-cell signaling and NF-kB genes), DNA binding and transcription-factor genes, and developmental genes. Importantly, NF-kB pathway is one of the most recurrently affected pathways in the different reported studies [12,13].

Introduction Multiple myeloma (MM) is featured by a multi-step transformation from normal plasma cell to monoclonal gammopathy of undetermined significance (MGUS), Smoldering MM, symptomatic MM and extramedullary disease (including plasma cell leukemia). Based on karyotype studies, MM can be divided in 2 groups: Hyperdiploid MM (HDMM) harboring 48–75 chromosomes and non-hyperdiploid MM (NHDMM) usually featured with less than 48 or more than 75 chromosomes. NHDMM harbors rearrangements involving the immunoglobulin heavy chain (IGH) locus with different partners (CCND1, CCND3, cMAF, MAFB, MMSET and FGFR3) in 70% of cases. In HDMM, Current Opinion in Genetics & Development 2015, 30:56–65

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Genomics in multiple myeloma Szalat and Munshi 57

Figure 1

Karyotype FISH

WGS aCGH SNP array Methylation Acetylation

GEP array RNAseq, Methylation array

Exon array microRNA arrays

NoncodingRNA microRNA A T C G A T C C

A U

Transcription

C G A

RNA processing

RNA modification

Translation

U C C

Hyperdiploid 50%

Mutations

Trisomies 3, 5, 7, 9, 11, 13, 15 17, 19, and 21

NRAS, KRAS, TP53, BRAF, DIS3, FAM46C

Non Hyperdiploid t(4;14) 15% t(11;14) 20% t(14;16) 3% t(14;20) 1% t(6;14) 1%

CNA

RNAt Molecular subgroups Prognosis markers

Others 1q gain 35% 1p del 30% Del 17p 8% Del 13q 45%

Current Opinion in Genetics & Development

Spectrum of genomic studies in multiple myeloma.

GEP studies identified several prognostic factors that significantly influence patient outcome [14–16]. To date, three main studies reported 3 different clusters of genes associated with poor outcome in MM. The Arkansas group identified a 70 genes signature, IFM group a 15 genes signature and the HOVON group a 92 genes signature [8,17,18]. Interestingly, in those studies there were very few overlapping genes, suggesting redundancy in genes and pathways that lead to cancer progression. GEP is strongly influenced by chromosomal lesions, such as IGH translocations and hyperdiploidy or chromosome duplications and it was recently shown that it does not allow predicting complete response to chemotherapy [19]. For these reasons, important efforts have been made to study alternative mechanisms involved in gene expression, principally, the transcriptome modifiers such as alternative splicing, microRNAs and epigenetic profiles. Our group is currently developing a novel approach to discover genes that show significant isoform switching using high throughput RNA-sequencing. A first study of www.sciencedirect.com

328 newly-diagnosed patients with multiple myeloma and 18 normal bone marrow donors has shown significant changes in relative isoform abundances between normal and malignant plasma cells in over 600 genes. Importantly, an alternative splicing profile seems to be associated with different molecular sub-groups and with survival, highlighting the need to better understand the mechanisms involved in post-translational regulation [20].

DNA-based studies DNA-based methods such as array comparative genomic hybridization (aCGH) and high-density single nucleotide polymorphism (SNP) array have been utilized to assess copy number alterations (CNA) [5,7,11–13,21–24]. In MM, the conventional cytogenetic studies are relevant only in a limited number of patients due to a lack of proliferative cells. SNP arrays that determine the CNA, represent an important option to molecularly characterize the MM cells. These studies have been crucial to identify Current Opinion in Genetics & Development 2015, 30:56–65

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oncogenes, tumor suppressor genes (TSG) and polymorphisms that are involved in myelomagenesis and genetic susceptibility. Copy number alterations that corresponds to the gain or the loss of DNA, have been extensively used. Indeed, CNA leads to gene expression alterations directly (through deletion or amplification) or indirectly (mediated by transcription factors or epigenetic modifiers) and allows for identifying potential oncogenes and tumor suppressor genes and critical pathways [25] (Figure 1). The IFM group has performed a high-density SNP array study in 192 newly-diagnosed uniformly treated MM patients. The multivariate analysis identified genetic lesions located on chromosomes 1q, 5q, and 12p as important prognostic factor. Indeed, in this study, patients with the 5q31.3 amplification had a better overall survival. Importantly, five highly significant prognostic genes that identified high-risk patients were discovered in this work: ILF2, ADAR, ALDH9A1, and UBAP2L located on 1q23.3 that are overexpressed and CD27, that mapped to 12p13.31 is underexpressed in the subgroup of patients with poor outcome. Thus, suggesting the role for SNP array in determining prognosis and possibly therapeutic options [5]. Genome wide association studies (GWAS) in large cohort of patients have identified seven risk loci (2p23.3, 3p22.1, 3q26.2, 6p21.33, 7p15.3, 17p11.2 and 22q13.1) that confer a genetic susceptibility to MM [26,27]. Some of the identified SNPs affect genes that have a known or a potential biological role in MM or in cancer [28,29]. The 2p23.3 polymorphism involves a DNA methyl transferase gene, namely DNMT3A that is highly expressed in MM. The 3p22.1 association affects the A542T polymorphism in the ULK4 gene that is highly expressed in MM. ULK4 is involved in mTOR-mediated autophagy. The 3q26.2 polymorphism involves the telomerase RNA component gene (TERC) that constitutes with the telomerase, the telomerase reverse transcriptase (TERT) that maintains the telomerase ends. Telomerase dysfunction has been shown in MM and other malignancies [30,31]. The 17p11.2 SNP association involves the tumor necrosis factor receptor superfamily member 13B (TNFRSF13B) also known as TACI (transmembrane activator and calcium modulator and cyclophilin ligand interactor) that is an important actor in B cell differentiation and auto-immunity. The 22q13.1 SNP association is related to the chromobox homologue 7 gene (CBX7) that is involved in lymphomagenesis [29,32]. Interestingly, risk for developing t(11;14) MM which results in the CCND1 relocation downstream of the IGH gene, is associated with a CCND1 constitutional polymorphism [33]. Current Opinion in Genetics & Development 2015, 30:56–65

MicroRNA studies (Table 1) MicroRNAs (miRNAs) constitute an important class of small RNAs, and understanding their functions has become a major area of research to develop potential targeted therapies [34]. In MM, each step of the disease is characterized by a specific miRNAs expression pattern and may reflect prognosis [35,36]. Here again, miRNA profile is correlated with chromosomal abnormalities: patients carrying the t(4;14) translocation have an overexpression of miR-let 7e, 125–5p, and 99b located at 19q13.33 [37] whereas patients with t(14;16) harbor overexpression of miR1 and miR133a [38]. Regarding miRNA functions, some recent findings provide important data to understand MM pathogenesis: - bone marrow stromal cells modulate miR-21, miR-15a/ 16 expression through secretion or transfer of miRNAcontaining exosomes [39]. - in case of t(4;14) MM, the miR-126 which inhibits cMYC translation is repressed, promoting cMYC overexpression [40]. - downregulation of specific miRNAs (miR-425, miR-152 and miR-24) in HDMM enhances the same oncogenic effect of IGH translocations, especially cyclin D pathway dysregulation [41]. - MiRs-192, -194, and -215, that enhance transcriptional activation of p53 and modulation of MDM2 expression, are downregulated in a subset of MM patients, suggesting an important role in MM development [42].

miRNA are easy to access and represent an important option to be used as prognostic biomarkers. Furthermore, treatments that can restore miRNA (in case of tumor suppressor miRNA) or inhibit miRNA (in case of oncogene miRNA) are being developed and may constitute a major therapeutic option in the future [43]. Other mechanisms involved in transcriptional and posttranscriptional regulation are also under investigation, including the role of other non-coding RNA, RNA splicing and epigenetic processes. The latter has provided so far the most relevant information.

Epigenetic *CpG methylation profile

In MM, a global DNA hypomethylation associated with a gene-specific DNA hypermethylation has been identified [44,45,46], with distinct profile according to the stage of the disease. Those specific genes include a panel of tumor suppressor genes as RBP1, SPARC, and TGFBI that are involved in MM progression [44]. Interestingly, genes involved in cell adhesion are remethylated in cells from extramedullary MM (PCL), suggesting this mechanism as www.sciencedirect.com

Genomics in multiple myeloma Szalat and Munshi 59

Table 1 Deregulated microRNAs in MGUS and multiple myeloma compared to normal plasma cells Downregulated

Upregulated MGUS (monoclonal gammopathy of undetermined significance)

miR-21 role in BMSC-mediated drug resistance in MM cells partially through NFkB pathway and by targeting RhoB miR-200b miR210 miR9 miR-222 miR-376

miR-339 miR-328

Multiple myeloma

mIR-135b is up-regulated in MM bone marrow mesenchymal stem cells following interaction with MM cells, impairing osteogenesis by targeting SMAD5 miR-25 miR-32 miR-95 miR-20a miR-27a miR-26b miR-93 miR-208 miR-221 miR-382 miR-181a/b

miR-15a regulates MM cell proliferation through AKT, MAPKs and NFkB pathways and by targeting cyclin D1, cyclin D2 and CDC25A miR-16 act in BMSC-mediated drug resistance in MM cells, possibly through IL-6 miR-199a, 24-3p, 15a-5p, 16-5p contribute to impaired osteogenesis miR-149 miR-323-5p miR-139 miR-199a-5p regulates bone marrow angiogenesis through targeting HIF-1a in MM cells and modulating interaction with BMSCs and bone marrow endothelial cells miRs-192, miR194 and miR215 are involved in transcriptional activation of p53 and modulation of MDM2 expression miR-425, miR-152 and miR-24 act in Cyclin pathway dysregulation

Adapted from [34,42,76,77]

important to contribute to independence from bone marrow microenvironment [46]. However, the mechanisms of DNA methylation patterns in MM remain unclear. *Histone modifications

Two major processes have been principally studied in MM. First, histone acetylation that results from the balance of histone acetyltransferases (HATs) and histone deacetylases (HDACs) activities [47], in which acetylation enhances gene expression. So far, HDAC enzymes include 11 different types and another related family, (the Sirtuin family) and are divided in four different classes. Although specific patterns of HDAC and HAT expressions and activities are not clearly defined in MM, HDAC inhibitors when combined with other conventional treatments for MM may constitute an important therapeutic option [45]. Second, histone methylation that results from a more complex system in which gene expression is regulated according to the combination of different number and sites (arginine or lysine) of methylations. For example, H3K36me3 methylation is associated with active transcription whereas H3K27me3 is associated with a silencing of transcription. Most of the studies in MM have www.sciencedirect.com

focused on multiple myeloma SET domain (MMSET or NSD2 or WHSC1) gene that is overexpressed in all cases with t(4;14)MM accounting for 15% of all patients. MMSET is a histone methyltransferase that has been involved in dimethylation of H4K20 and H3K36 leading to a specific histone methylation profile and to the overpression of genes involved in cell cycle progression, apoptosis, cell adhesion, oncogenesis and DNA damage response. Importantly, MMSET activity has an impact on HDAC1, HDAC2, and the histone demethylase LSD1 activities [48–50]. Also, MMSET influences H3k27 methyltransferase enhancer of zeste homolog 2 (EZH2), that is part of the protein complex known as polycomb repressive complex 2 (PRC2), and that has been shown to have a potential critical role in oncogenesis of lymphoma and Germinal-center B cell disease [51,52]. Indeed, high rate of H3K36 methylation that is observed in case of high MMSET expression is globally associated with a low rate of H3K27 methylation profile at the exception of certain critical loci carrying the transcription inhibition [52]. Epigenetic modifier drugs including HDAC inhibitors, demethylating agents and EZH2 inhibitors are already under investigation and may constitute major therapeutic options for MM in the future [52,53]. Current Opinion in Genetics & Development 2015, 30:56–65

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Mutational profile in MM (Table 2 and Figure 2) Next generation sequencing has allowed the study of the genomic landscape and clonal evolution in MM. Two important recent studies involving respectively 203 and 67 patients [54,55], have used whole genome and whole exome sequencing to identify recurrent mutated genes in MM. Importantly, those studies were concordant with previous study in smaller cohort [56,57]. KRAS, NRAS, FAM46C, DIS3, TP53 and BRAF were identified as the 5 more recurrent mutated genes. Interestingly, whereas NRAS, KRAS, BRAF and TP53 are frequently mutated genes in other human cancers [58], FAM46C and DIS3 are not and they are associated with a distinct cytogenetic profile in MM: FAM46C is more frequently mutated in HDMM whereas DIS3 mutations are more frequent in NHDMM (Table 2). However, their specific roles in MM remain to be defined. Interestingly, those studies have shown that recurrent mutations could be present at diagnosis or could appear at relapse conferring a selective advantage to the mutated clone that may be due to the influence of treatments. Two genes were found to be mutated recurrently in only one study namely PRDM1 and RB1, respectively in 12/ 203 and 7/203 [54]. Interestingly RB1 is located in chromosome 13q and del(13q) occurs in 45% of MM. Also RB1 has been previously identified to be under expressed in MM by GEP studies [11]. Both the studies have shown that TP53 mutations occur frequently in case of del(17p) reinforcing the hypothesis of its critical role in MM evolution [59–61].

Mitogen-activated protein kinase (MAPK) pathway appears to be the most affected pathway, through recurrent (NRAS, KRAS, BRAF) or less frequent (NF1, RASA2) mutations. Off note, some patients harbored 2 or more activating mutations in this pathway. Other pathways are also recurrently altered including NF-kB, chromatin-modifying enzymes pathway, cell-cycle machinery and RNA-processing molecules by different mutations. For example, in NF-kB pathway, TRAF3, BIRC2, BIRCC3, CYLD were found mutated but not recurrently. The biological effects of all those mutations in overall and relapse-free survival remain to be evaluated in larger cohort. However, NRAS mutations at relapse appear to be associated with less sensitivity to bortezomib in a cohort of 133 relapsed myeloma patients [62]. Altogether, those results provide major perspectives to develop new targeted therapies.

Mutational signatures in MM Based on the different nucleotide combinations and nucleotide changes, whole exome sequencing allows characterization of the type of mutational process that occurs [54,55,56]. In MM, 2 types of signature were observed preponderantly: the enrichment of C>T transitions at CpG dinucleotides, which reflect deamination of methylated cytosine to thymine, and the C>T transition associated with C>A and C>G transversion in TpC context. This latter process was found to occur across

Table 2 Recurrent mutated genes in multiple myeloma Gene NRAS KRAS TP53 DIS3 a FAM46C BRAF SF3B1 CYLD TRAF3 ROBO1 EGR1 SP140 LTB RASA2 FAT3 CCND1

Function/pathway MAP Kinase pathway MAP Kinase pathway Tumor suppressor Exosome endoribonuclease Recurrently mutated in NHDMM Unknown Recurrently mutated in HDMM MAP Kinase pathway RNA splicing machinery NFkB inhibitors NFkB inhibitors Transmembrane receptor, MET signaling Transcription factor Antigene response in mature B cells Lymphoid development MAP Kinase pathway suppressor of RAS Function Cadherin superfamily member Cell cycle progression

Prevalence Bolli et al. [55] (n = 67 patients)

Prevalence Lohr et al. [54] (n = 203 patients)

25% (17/67) 25% (17/67) 15% (10/67) 1.5% (1/67)

20% (40/203) 23% (52/203) 8% (18/203) 11% (23/203)

12% (8/67)

11% (24/203)

15% (10/67) V600E in 3/10 3% (2/67) 3% (2/67) 3% (2/67) 7% (5/67) 6% (4/67) 7% (5/67) 4.5% (3/67) 3% (2/67)

6% (12/203)

7% (5/67) 3% (2/67)

4.4% (9/203) 3% (6/203)

1.5% (3/203) 2.5% (5/203) 5.5% (11/203) 2% (4/203) 3.5% (7/203) 4.4% (9/203) 1% (2/203) 3% (6/203)

The differences observed in the 2 studies are due to a small representation of patients harboring IGH translocation in the study of Bolli et al. [55], DIS3 mutations being significantly associated with NHDMM.

a

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Genomics in multiple myeloma Szalat and Munshi 61

Figure 2

Translocation Duplication Activating mutations Epigenetic regulation Transcription activation: miRNA cMYC MMSET FGFR3 Cyclin D family

MAF family NRAS KRAS BRAF

Oncogenes

Deletion Silencing mutations Epigenetic regulation Transcription inhibition: miRNA

MEK inhibitors BRAF inhibitors Akt inhibitors HDAC inhibitors Demethylating agents miRNA therapeutics

TP53 RB1 DIS3 SP140 FAM46C LTB Tumour supressor genes

Genomic instability Current Opinion in Genetics & Development

Processes involved in genomic imbalance between oncogenes and tumor suppressor genes in multiple myeloma.

the whole genome but also in select cases clusters at specific intervals in a phenomenon known as kataegis. The discovery of the processes (SHM, Kataegis) involved in mutagenesis in MM may potentially lead to development of treatments that can stop MM progression. Interestingly, another cluster of mutations in specific motifs suggested activation-induced deaminase (AID) targeted changes, suggesting that somatic hypermutation (SHM) process may be involved. Mutational signatures have also been evaluated over the time in 15 patients and were frequently changed, probably under the influence of treatments according to a dynamic evolution.

Clonal heterogeneity and clonal evolution (Figure 3) Intraclonal heterogeneity, the coexistence of tumor cells harboring different mutations is now well described in all cancer and has been clearly identified in MM with an increasing level of complexity according to the stage of the disease [63,64,65]. Off note, all patients seem to carry a variable number of subclones, whatever the stage of the disease. By studying SNP arrays, whole-exome sequencing data and mutations in known driver genes as NRAS or KRAS, the phylogeny between the clones has been established, confirming the complexity of MM evolution. Of note, intraclonal heterogeneity was also studied and confirmed by single cell analysis [66]. www.sciencedirect.com

Evolution of clonal heterogeneity has also been evaluated in 15 patients [55] over time with serial samples. This has allowed to identify 4 distinct evolutive patterns: first, no change in the clonal and subclonal composition between two time points; second, ‘differential clonal response’, in which each subclone was identified at the two time points, but their relative proportions changed over time; third, linear evolution, in which a new subclone emerged in the late sample that was not obvious despite the deep sequencing in the earlier sample; and fourth, branching evolution corresponding to the emergence of one or more new clones whereas others have declined in frequency or disappeared. The understanding of the subclonal evolution pattern associated with the MM progression may be helpful to eventually predict evolution under the selective pressure of treatments, and to choose appropriate treatment for a patient. As an example, if a previous subclone that has been sensitive to a combination of drugs became the major clone at relapse, the use of the same combination could be considered, whereas if not, alternative drugs need to be used.

Therapeutic impact To date, guidelines for treatment of MM patients are based on age and general conditions. Patients under 65 years are treated with induction therapy followed by high-dose melphalan and auto-transplant (stem cell Current Opinion in Genetics & Development 2015, 30:56–65

62 Cancer genomics

Figure 3

Clonal heterogeneity

Positive selection: Chemotherapy Clonal competition Microenvironment

(MGUS, Smoldering MM, MM extraledullary MM and PML)

Clonal evolution

No change

Linear

Branching

Differential clonal response

Current Opinion in Genetics & Development

Clonal architecture in multiple myeloma: each stage of the disease is featured by a complex clonal heterogeneity with different subclones carrying different mutations and/or chromosomes abnormalities. Each color represents the proportion of each subclone. Evolution over time is marked by different patterns and influenced by different parameters. 4 different patterns have been observed: */no change */linear evolution, in which a new subclone, that was not obvious despite the deep sequencing in the earlier sample, emerges in the late sample */branching evolution corresponding to the emergence of one or more new clones whereas others have declined in frequency or disappeared */differential clonal response, in which each subclone remains present but in different proportions over the time. Adapted from Bolli et al. [55].

rescue) whereas, older patients or patients with comorbidities, are treated with a combination of drugs according to potential toxicity [67,68]. High risk patients defined by cytogenetic abnormalities (del(17p), t(4;14) and 1q gain) do not yet benefit from a specific treatment with the exception of bortezomib that has significantly improved outcome [69].

target. BRAF inhibitors in combination with MEK inhibitors enhances cell toxicity on BRAF mutated cell lines [54,55] and one patient carrying the BRAF V600E activating mutation was treated with vemurafenib and attained a prolonged response and survival [70] indicating possibility of targeted therapy based on mutational and genomic profile.

However, the understanding of genomic data has now significantly contributed to development of new myeloma therapies. Treatments targeting specific pathways that have been shown to be critical for MM progression, growth or survival, are now being developed, as well as treatment acting on transcription modifiers.

The NF-kB pathway, which is also recurrently activated through gene mutations or overexpression, has been an important target for therapeutic application including development and evaluation of inhibitors targeting TACI or IKKb for example [71,72].

Thus, extracellular signal regulated kinase (ERK)/mitogen activated protein kinase (MAPK), pathway is one of the most prominently affected pathway in MM and is currently under investigation as an important therapeutic Current Opinion in Genetics & Development 2015, 30:56–65

Survival via Janus activated kinase (JAK)/STAT and migration via PKC-dependent signaling cascades are also under investigation and/or under clinical studies [73,74]. The development of deubiquitinating Enzyme Inhibitors, BET Bromodomain Inhibitors that inhibits cMYC www.sciencedirect.com

Genomics in multiple myeloma Szalat and Munshi 63

transcription; Phosphoinosiide 3-kinase/Akt/Mammalian Target of Rapamycin pathway Inhibitors, Cyclin-Dependent Kinase Inhibitors and new monoclonal antibodies (anti CD38, anti CS1 and anti IL-6) constitute also new targeted and promising drugs in the next future [73,74]. Epigenetic modifiers are also becoming a very promising field of investigation. Pan-HDAC inhibitors (panobinostat and vorinostat) or specific HDAC inhibitors (as rocilinostat inhibiting HDAC6) appeared to be significantly efficient when used in combination with bortezomib or Imids in clinical trials [73,74]. More recently demethylating agents such as EZH2 inhibitors are being investigated in t(4;14) MM [52]. MicroRNA therapeutics, which include downregulation or inhibition of oncogenic miRNAs or upregulation of tumor-suppressive miRNAs, also represent an important future option. To achieve a specific miRNA restoration, coated nanoparticules or liposomal miRNA appear to be more efficient than epignetic modifiers or small molecules such as enoxacin [75]. Notably, MRX34, a liposomebased miR-34 mimic, has been studied in a Phase I clinical trial in hepatocellular carcinoma and a mIR-34a synthetic has been reported to be efficient in vitro and in vivo in MM [43]. To inhibit or to block overexpressed miRNA, the current preclinical investigation uses the delivery of anti-oligonucleotides, miRNA sponges or exosome secretion inhibition [75]. In conclusion, genomic landscape of multiple myeloma is complex and heterogeneous. However, identification of recurrent mutated genes, affected signaling pathways and clonal evolution provide the prospect of developing effective targeted and personalized therapies.

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