High-dose melphalan treatment significantly increases mutational burden at relapse in multiple myeloma.

High-dose melphalan (HDM) improves progression-free survival in multiple myeloma (MM), yet melphalan is a DNA-damaging alkylating agent; therefore, we assessed its mutational effect on surviving myeloma cells by analyzing paired MM samples collected at diagnosis and relapse in the IFM 2009 study. We performed deep whole-genome sequencing on samples from 68 patients, 43 of whom were treated with RVD (lenalidomide, bortezomib, and dexamethasone) and 25 with RVD + HDM. Although the number of mutations was similar at diagnosis in both groups (7137 vs 7230; P = .67), the HDM group had significantly more mutations at relapse (9242 vs 13 383, P = .005). No change in the frequency of copy number alterations or structural variants was observed. The newly acquired mutations were typically associated with DNA damage and double-stranded breaks and were predominantly on the transcribed strand. A machine learning model, using this unique pattern, predicted patients who would receive HDM with high sensitivity, specificity, and positive prediction value. Clonal evolution analysis showed that all patients treated with HDM had clonal selection, whereas a static progression was observed with RVD. A significantly higher percentage of mutations were subclonal in the HDM cohort. Intriguingly, patients treated with HDM who achieved complete remission (CR) had significantly more mutations at relapse yet had similar survival rates as those treated with RVD who achieved CR. This similarity could have been due to HDM relapse samples having significantly more neoantigens. Overall, our study identifies increased genomic changes associated with HDM and provides rationale to further understand clonal complexity.

Whole genome copy number analysis in search of new prognostic biomarkers in first line treatment of mantle cell lymphoma. A study by the LYSA group.

Mantle cell lymphoma (MCL) is a lymphoproliferative disorder characterized by the t(11;14)(q13;q32) CCND1/IGH translocation. This lymphoma is however extremely heterogeneous in terms of molecular alterations. Moreover, the course of the disease can vary greatly between indolent forms with slow progression and aggressive conditions rapidly pejorative. The identification of early markers allowing to predict individual patients outcome has however been unsuccessful so far. The LyMa trial treated homogeneously a cohort of young MCL patients. This appeared as a good opportunity to search for biomarkers of response to therapy. DNA extracted from diagnostic paraffin-embedded lymph node biopsies from 100 patients with newly diagnosed MCL, homogeneously treated in this prospective clinical trial, were investigated for copy number alterations and copy neutral loss of heterozygosity using the Oncoscan SNP-array scanning the whole genome. An independent confirmatory cohort was used to strengthen the possibly relevant anomalies observed. Here we describe the recurrent anomalies identified with this technique. Deletions of 17p(TP53) and 9p(CDKN2A) were more frequent in refractory or early relapsing patients (10%), but had no significant impact in univariate analysis on progression-free (PFS) or overall survival (OS). Regardless of the presence of TP53 or CDKN2A deletions, gains in 7p22 (8,5%) were associated with better PFS in univariate but not in multivariate analysis including MCL International Prognostic Index and treatment. Gains of 11q(CCDN1), suggesting gains of the CCND1/IGH fusion, were associated with worse OS and PFS in univariate and multivariate analyses. This worse prognosis impact was confirmed by FISH in an independent confirmatory cohort. This work, using a whole genome approach, confirms the broad genomic landscape of MCL and shows that gains of the CCND1/IGH fusion can be considered as a new prognostic structural variant. Genomic abnormalities of prognostic impact could be useful to strengthen or de-escalate treatment schedules or choosing targeted therapies or CART-cells.

Role of additional chromosomal changes in the prognostic value of t(4;14) and del(17p) in multiple myeloma: the IFM experience.

In multiple myeloma, cytogenetic changes are important predictors of patient outcome. In this setting, the most important changes are deletion 17p, del(17p), and translocation of chromosomes 4 and 14, t(4;14), conferring a poor outcome. However, a certain degree of heterogeneity is observed in the survival of these high-risk patients. We hypothesized that other chromosomal changes may impact the outcome. We retrospectively analyzed a large series of 242 patients displaying either t(4;14) (157 patients) or del(17p) (110 patients), 25 patients presenting both abnormalities, using single nucleotide polymorphism array. In patients with t(4;14), del(1p32), del22q, and >30 chromosomal structural changes negatively impacted progression-free survival (PFS). For overall survival (OS), del(13q14), del(1p32), and the number of chromosomal structural changes worsened the prognosis of patients. For patients with del(17p), del6q worsened the prognosis of patients, whereas trisomy 15 and monosomy 14 were found to have a protective effect on PFS. For OS, del(1p32) worsened the prognosis of patients, whereas having >8 numerical changes was found to have a protective effect on survival. This study, which is the largest series of high-risk patients analyzed with the most modern genomic technique, identified 1 main factor negatively impacting survival: del(1p32).

Understanding the role of hyperdiploidy in myeloma prognosis: which trisomies really matter?

The prognosis of multiple myeloma is mainly dependent upon chromosomal changes. The 2 major abnormalities driving poor outcome are del(17p) and t(4;14). However, the outcome of these high-risk patients is not absolutely uniform, with some patients presenting long survival. We hypothesized that these better outcomes might be related to concomitant "good-risk" chromosomal changes exploring hyperdiploidy. We analyzed a large series of 965 myeloma patients, including 168 patients with t(4;14) and 126 patients with del(17p), using high-throughput single-nucleotide polymorphism arrays after plasma cell sorting. As expected, trisomic chromosomes were highly associated. Using the LASSO model, we found that only chromosome 3, when trisomic, was associated with a longer progression-free survival and that 3 trisomies modulated overall survival (OS) in myeloma patients: trisomies 3 and 5 significantly improved OS, whereas trisomy 21 worsened OS. In patients with t(4;14), trisomies 3 and/or 5 seemed to overcome the poor prognosis. For the first time, using a specific modeling approach, we show that not all trisomies display the same prognostic impact. This finding could be important for routine assessment of prognosis in myeloma, and some high-risk patients with a traditional evaluation could in fact be standard-risk patients.

Differential and limited expression of mutant alleles in multiple myeloma.

Recent work has delineated mutational profiles in multiple myeloma and reported a median of 52 mutations per patient, as well as a set of commonly mutated genes across multiple patients. In this study, we have used deep sequencing of RNA from a subset of these patients to evaluate the proportion of expressed mutations. We find that the majority of previously identified mutations occur within genes with very low or no detectable expression. On average, 27% (range, 11% to 47%) of mutated alleles are found to be expressed, and among mutated genes that are expressed, there often is allele-specific expression where either the mutant or wild-type allele is suppressed. Even in the absence of an overall change in gene expression, the presence of differential allelic expression within malignant cells highlights the important contribution of RNA-sequencing in identifying clinically significant mutational changes relevant to our understanding of myeloma biology and also for therapeutic applications.

The shaping and functional consequences of the dosage effect landscape in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) is a malignant proliferation of plasma B cells. Based on recurrent aneuploidy such as copy number alterations (CNAs), myeloma is divided into two subtypes with different CNA patterns and patient survival outcomes. How aneuploidy events arise, and whether they contribute to cancer cell evolution are actively studied. The large amount of transcriptomic changes resultant of CNAs (dosage effect) pose big challenges for identifying functional consequences of CNAs in myeloma in terms of specific driver genes and pathways. In this study, we hypothesize that gene-wise dosage effect varies as a result from complex regulatory networks that translate the impact of CNAs to gene expression, and studying this variation can provide insights into functional effects of CNAs. RESULTS: We propose gene-wise dosage effect score and genome-wide karyotype plot as tools to measure and visualize concordant copy number and expression changes across cancer samples. We find that dosage effect in myeloma is widespread yet variable, and it is correlated with gene expression level and CNA frequencies in different chromosomes. Our analysis suggests that despite the enrichment of differentially expressed genes between hyperdiploid MM and non-hyperdiploid MM in the trisomy chromosomes, the chromosomal proportion of dosage sensitive genes is higher in the non-trisomy chromosomes. Dosage-sensitive genes are enriched by genes with protein translation and localization functions, and dosage resistant genes are enriched by apoptosis genes. These results point to future studies on differential dosage sensitivity and resistance of pro- and anti-proliferation pathways and their variation across patients as therapeutic targets and prognosis markers. CONCLUSIONS: Our findings support the hypothesis that recurrent CNAs in myeloma are selected by their functional consequences. The novel dosage effect score defined in this work will facilitate integration of copy number and expression data for identifying driver genes in cancer genomics studies. The accompanying R code is available at http://www.canevolve.org/dosageEffect/.

Chromothripsis identifies a rare and aggressive entity among newly diagnosed multiple myeloma patients.

Multiple myeloma (MM) develops from a premalignant plasma cell proliferative disorder, and with time can progress to a more aggressive disease in extramedullary locations. The gradually clinical evolution is supported by clonal expansion of cells that acquire genetic lesions over years. This model of cancer evolution based on ongoing genomic instability mechanism may apply to development of most MM cases. However, in a small fraction of newly diagnosed MM who relapse quickly and finally die within 2 years, the gradual model appears to be untenable. Analysis of high resolution copy number profiles obtained using single nucleotide polymorphism array data from 764 newly diagnosed MM identified large numbers of genomic rearrangements with the hallmarks of chromothripsis in 1.3% of samples. Moreover, this catastrophic event confers a poor outcome. Because chromothripsis appears to occur in a single crisis, our results suggest that high-risk MM patients use this novel way of cancer evolution.

Translocation t(14;16) and multiple myeloma: is it really an independent prognostic factor?

Many trials in myeloma are stratified on cytogenetic abnormalities. Among them, the most commonly chosen are the t(4;14), the del(17p), and the t(14;16). If data are well established for t(4;14) and del(17p), very few data support the use of t(14;16). To address this issue, we retrospectively analyzed 1003 patients with newly diagnosed myeloma for this abnormality. We identified 32 patients with the t(14;16). Compared with patients lacking the t(14;16), we did not observe any difference in overall survival (P = .28). Moreover, in multivariate analyses, the t(14;16) was not prognostic (P = .39). In conclusion, our data do not support the use of t(14;16)-specific probes in the diagnostic panels of multiple myeloma.

Exploring the impact of dexamethasone on gene regulation in myeloma cells.

Among glucocorticoids (GCs), dexamethasone (Dex) is widely used in treatment of multiple myelomas. However, despite a definite benefit, all patients relapse. Moreover, the molecular basis of glucocorticoid efficacy remains elusive. To determine genomic response to Dex in myeloma cells, we generated bulk and single-cell multi-omics data and high-resolution contact maps of active enhancers and target genes. We show that a minority of glucocorticoid receptor-binding sites are associated with enhancer activity gains, increased interaction loops, and transcriptional activity. We identified and characterized a predominant enhancer enriched in cohesin (RAD21) and more accessible upon Dex exposure. Analysis of four gene-specific networks revealed the importance of the CTCF-cohesin couple and the synchronization of regulatory sequence openings for efficient transcription in response to Dex. Notably, these epigenomic changes are associated with cell-to-cell transcriptional heterogeneity, in particular, lineage-specific genes. As consequences, BCL2L11-encoding BIM critical for Dex-induced apoptosis and CXCR4 protective from chemotherapy-induced apoptosis are rather up-regulated in different cells. In summary, our work provides new insights into the molecular mechanisms involved in Dex escape.

Acquired resistance to a GPRC5D-directed T-cell engager in multiple myeloma is mediated by genetic or epigenetic target inactivation.

Bispecific antibodies targeting GPRC5D demonstrated promising efficacy in multiple myeloma, but acquired resistance usually occurs within a few months. Using a single-nucleus multi-omic strategy in three patients from the MYRACLE cohort (ClinicalTrials.gov registration: NCT03807128 ), we identified two resistance mechanisms, by bi-allelic genetic inactivation of GPRC5D or by long-range epigenetic silencing of its promoter and enhancer regions. Molecular profiling of target genes may help to guide the choice of immunotherapy and early detection of resistance in multiple myeloma.

In-depth analysis of alternative splicing landscape in multiple myeloma and potential role of dysregulated splicing factors.

Splicing changes are common in cancer and are associated with dysregulated splicing factors. Here, we analyzed RNA-seq data from 323 newly diagnosed multiple myeloma (MM) patients and described the alternative splicing (AS) landscape. We observed a large number of splicing pattern changes in MM cells compared to normal plasma cells (NPC). The most common events were alterations of mutually exclusive exons and exon skipping. Most of these events were observed in the absence of overall changes in gene expression and often impacted the coding potential of the alternatively spliced genes. To understand the molecular mechanisms driving frequent aberrant AS, we investigated 115 splicing factors (SFs) and associated them with the AS events in MM. We observed that ~40% of SFs were dysregulated in MM cells compared to NPC and found a significant enrichment of SRSF1, SRSF9, and PCB1 binding motifs around AS events. Importantly, SRSF1 overexpression was linked with shorter survival in two independent MM datasets and was correlated with the number of AS events, impacting tumor cell proliferation. Together with the observation that MM cells are vulnerable to splicing inhibition, our results may lay the foundation for developing new therapeutic strategies for MM. We have developed a web portal that allows custom alternative splicing event queries by using gene symbols and visualizes AS events in MM and subgroups. Our portals can be accessed at http://rconnect.dfci.harvard.edu/mmsplicing/ and https://rconnect.dfci.harvard.edu/mmleafcutter/ .

Molecular Signature of 18F-FDG PET Biomarkers in Newly Diagnosed Multiple Myeloma Patients: A Genome-Wide Transcriptome Analysis from the CASSIOPET Study.

The International Myeloma Working Group recently fully incorporated 18F-FDG PET into multiple myeloma (MM) diagnosis and response evaluation. Moreover, a few studies demonstrated the prognostic value of several biomarkers extracted from this imaging at baseline. Before these 18F-FDG PET biomarkers could be fully endorsed as risk classifiers by the hematologist community, further characterization of underlying molecular aspects was necessary. Methods: Reported prognostic biomarkers (18F-FDG avidity, SUVmax, number of focal lesions, presence of paramedullary disease [PMD] or extramedullary disease) were extracted from 18F-FDG PET imaging at baseline in a group of 139 patients from CASSIOPET, a companion study of the CASSIOPEIA cohort (ClinicalTrials.gov identifier NCT02541383). Transcriptomic analyses using RNA sequencing were realized on sorted bone marrow plasma cells from the same patients. An association with a high-risk gene expression signature (IFM15), molecular classification, progression-free survival, a stringent clinical response, and minimal residual disease negativity were explored. Results:18F-FDG PET results were positive in 79.4% of patients; 14% and 11% of them had PMD and extramedullary disease, respectively. Negative 18F-FDG PET results were associated with lower levels of expression of hexokinase 2 (HK2) (fold change, 2.1; adjusted P = 0.04) and showed enrichment for a subgroup of patients with a low level of bone disease. Positive 18F-FDG PET results displayed 2 distinct signatures: either high levels of expression of proliferation genes or high levels of expression of GLUT5 and lymphocyte antigens. PMD and IFM15 were independently associated with a lower level of progression-free survival, and the presence of both biomarkers defined a group of "double-positive" patients at very high risk of progression. PMD and IFM15 were related neither to minimal residual disease assessment nor to a stringent clinical response. Conclusion: Our study confirmed and extended the association between imaging biomarkers and transcriptomic programs in MM. The combined prognostic value of PMD and a high-risk IFM15 signature may help define MM patients with a very high risk of progression.

Genetic factors underlying the risk of bortezomib induced peripheral neuropathy in multiple myeloma patients.

Bortezomib induced peripheral neuropathy is a dose-limiting side effect and a major concern in the treatment of multiple myeloma. To identify genetic risk factors associated with the development of this side effect in bortezomib treated multiple myeloma patients, a pharmacogenetic association study was performed using a discovery set (IFM 2005-01; n = 238) and a validation set (HOVON65/GMMG-HD4 and a Czech dataset; n = 231). After multiplicity correction, none of the 2,149 single nucleotide polymorphisms tested revealed any significant association with bortezomib induced peripheral neuropathy. However, 56 single nucleotide polymorphisms demonstrated an association with bortezomib induced peripheral neuropathy with pointwise, uncorrected significance. Pathway analysis of these polymorphisms demonstrated involvement of neurological disease (FDR <20%). Also a clear enrichment of major bortezomib metabolizing genes was found. Univariate evaluation of these 56 polymorphisms in the validation set demonstrated one single nucleotide polymorphism with pointwise significance: rs619824 in CYP17A1. (IFM 2005-01 clinicaltrials.gov identifier: NCT00200681; HOVON-65/GMMG-HD4 isrctn.org identifier: ISRCTN64455289).

The DNA methylation landscape of multiple myeloma shows extensive inter- and intrapatient heterogeneity that fuels transcriptomic variability.

BACKGROUND: Cancer evolution depends on epigenetic and genetic diversity. Historically, in multiple myeloma (MM), subclonal diversity and tumor evolution have been investigated mostly from a genetic perspective. METHODS: Here, we performed an analysis of 42 MM samples from 21 patients by using enhanced reduced representation bisulfite sequencing (eRRBS). We combined several metrics of epigenetic heterogeneity to analyze DNA methylation heterogeneity in MM patients. RESULTS: We show that MM is characterized by the continuous accumulation of stochastic methylation at the promoters of development-related genes. High combinatorial entropy change is associated with poor outcomes in our pilot study and depends predominantly on partially methylated domains (PMDs). These PMDs, which represent the major source of inter- and intrapatient DNA methylation heterogeneity in MM, are linked to other key epigenetic aberrations, such as CpG island (CGI)/transcription start site (TSS) hypermethylation and H3K27me3 redistribution as well as 3D organization alterations. In addition, transcriptome analysis revealed that intratumor methylation heterogeneity was associated with low-level expression and high variability. CONCLUSIONS: We propose that disrupted DNA methylation in MM is responsible for high epigenetic and transcriptomic instability allowing tumor cells to adapt to environmental changes by tapping into a pool of evolutionary trajectories.

Inhibition of mTORC1 activity by REDD1 induction in myeloma cells resistant to bortezomib cytotoxicity.

The combination of bortezomib and dexamethasone is becoming the reference induction treatment for multiple myeloma patients younger than 65 years. Despite its advantage over vincristin adryamicin dexamethasone induction treatment, bortezomib does not benefit all patients. We hypothesize that heterogeneity of the response experienced by myeloma patients is, at least in part, due to genomic variations in the malignant plasma cells. To test this hypothesis we used gene expression profiling to identify early responsive genes induced by bortezomib in resistant myeloma cells. Our study revealed: (i) a dramatic induction of REDD1, a negative regulator of mammalian target of rapamycin kinase complex 1 (mTORC1) activity, in these cells; (ii) a transient cell size decrease associated with REDD1 overexpression; and (iii) partial restoration of bortezomib sensitivity in REDD1 knockdown bortezomib-resistant myeloma cells. Together, these results identify a possible novel mechanism of bortezomib resistance in myeloma patients mediated by REDD1 overexpression involving inhibition of mTORC1 activity and suggest that the use of mammalian target of rapamycin inhibitors in myeloma patients could be deleterious.

Mutations in TP53 are exclusively associated with del(17p) in multiple myeloma.

Deletion of the 17p13 chromosomal region [del(17p)] is associated with a poor outcome in multiple myeloma. Most of the studies have targeted the TP53 gene for deletion analyses, although no study showed that this gene is the deletion target. In order to address this issue, we sequenced the TP53 gene in 92 patients with multiple myeloma at diagnosis, 54 with a del(17p) and 38 lacking del(17p). At least one mutation was found in 20 patients, all of them presenting a del(17p). The analysis of the mutation location showed that virtually all of them occurred in highly conserved domains involved in the DNA-protein interactions. In conclusion, we showed that 37% of the myeloma patients with del(17p) present a TP53 mutation versus 0% in patients lacking the del(17p). The prognostic significance of these mutations remains to be evaluated.

DNA hydroxymethylation is associated with disease severity and persists at enhancers of oncogenic regions in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) is a heterogeneous plasma cell malignancy that remains challenging to cure. Global hypomethylation correlates with an aggressive phenotype of the disease, while hypermethylation is observed at particular regions of myeloma such as B cell-specific enhancers. The recently discovered active epigenetic mark 5-hydroxymethylCytosine (5hmC) may also play a role in tumor biology; however, little is known about its level and distribution in myeloma. In this study, we investigated the global level and the genomic localization of 5hmC in myeloma cells from 40 newly diagnosed patients, including paired relapses, and of control individuals. RESULTS: Compared to normal plasma cells, we found global 5hmC levels to be lower in myeloma (P < 0.001). Higher levels of 5hmC were found in lower grades of the International Staging System prognostic index (P < 0.05) and tend to associate with a longer overall survival (P < 0.1). From the hydroxymethylome data, we observed that the remaining 5hmC is organized in large domains overlapping with active chromatin marks and chromatin opening. We discovered that 5hmC strongly persists at key oncogenic genes such as CCND1, CCND2 and MMSET and characterized domains that are specifically hydroxymethylated in myeloma subgroups. Novel 5hmC-enriched domains were found at putative enhancers of CCND2 and MYC in newly diagnosed patients. CONCLUSIONS: 5hmC level is associated with clinical aspects of MM. Mapping 5hmC at a genome-wide level provides insights into the disease biology directly from genomic DNA, which makes it a potent mark to study epigenetics on large patient cohorts.

Genome-Wide Somatic Alterations in Multiple Myeloma Reveal a Superior Outcome Group.

PURPOSE: Multiple myeloma (MM) is accompanied by heterogeneous somatic alterations. The overall goal of this study was to describe the genomic landscape of myeloma using deep whole-genome sequencing (WGS) and develop a model that identifies patients with long survival. METHODS: We analyzed deep WGS data from 183 newly diagnosed patients with MM treated with lenalidomide, bortezomib, and dexamethasone (RVD) alone or RVD + autologous stem cell transplant (ASCT) in the IFM/DFCI 2009 study (ClinicalTrials.gov identifier: NCT01191060). We integrated genomic markers with clinical data. RESULTS: We report significant variability in mutational load and processes within MM subgroups. The timeline of observed activation of mutational processes provides the basis for 2 distinct models of acquisition of mutational changes detected at the time of diagnosis of myeloma. Virtually all MM subgroups have activated DNA repair-associated signature as a prominent late mutational process, whereas APOBEC signature targeting C>G is activated in the intermediate phase of disease progression in high-risk MM. Importantly, we identify a genomically defined MM subgroup (17% of newly diagnosed patients) with low DNA damage (low genomic scar score with chromosome 9 gain) and a superior outcome (100% overall survival at 69 months), which was validated in a large independent cohort. This subgroup allowed us to distinguish patients with low- and high-risk hyperdiploid MM and identify patients with prolongation of progression-free survival. Genomic characteristics of this subgroup included lower mutational load with significant contribution from age-related mutations as well as frequent NRAS mutation. Surprisingly, their overall survival was independent of International Staging System and minimal residual disease status. CONCLUSION: This is a comprehensive study identifying genomic markers of a good-risk group with prolonged survival. Identification of this patient subgroup will affect future therapeutic algorithms and research planning.

A 38-gene expression signature to predict metastasis risk in node-positive breast cancer after systemic adjuvant chemotherapy: a genomic substudy of PACS01 clinical trial.

Currently, no prognostic gene-expression signature (GES) established from node-positive breast cancer cohorts, able to predict evolution after systemic adjuvant chemotherapy, exists. Gene-expression profiles of 252 node-positive breast cancer patients (median follow-up: 7.7 years), mostly included in a randomized clinical trial (PACS01), receiving systemic adjuvant regimen, were determined by means of cDNA custom array. In the training cohort, we established a GES composed of 38 genes (38-GES) for the purpose of predicting metastasis-free survival. The 38-GES yielded unadjusted hazard ratio (HR) of 4.86 (95% confidence interval = 2.76-8.56). Even when adjusted with the best two clinicopathological prognostic indexes: Nottingham prognostic index (NPI) and Adjuvant!, 38-GES HRs were 3.30 (1.81-5.99) and 3.40 (1.85-6.24), respectively. Furthermore, 38-GES improved NPI and Adjuvant! classification. In particular, NPI intermediate-risk patients were divided into 2/3 close to low-risk group and 1/3 close to high-risk group (HR = 6.97 [2.51-19.36]). Similarly, Adjuvant! intermediate-risk patients were divided into 2/3 close to low-risk group and 1/3 close to high-risk group (HR = 4.34 [1.64-11.48]). The 38-GES was validated on gene-expression datasets from three external node-positive breast cancer subcohorts (n = 224) generated from different microarray platforms, with HR = 2.95 (1.74-5.01). Moreover, 38-GES showed prognostic performance in supplementary cohorts with different lymph-node status and endpoints (1,040 new patients). The 38-GES represents a robust tool able to type systemic adjuvant treated node-positive patients at high risk of metastatic relapse, and is especially powerful to refine NPI and Adjuvant! classification for those patients.

Deciphering the chronology of copy number alterations in Multiple Myeloma.

Multiple myeloma (MM) and its precursor condition MGUS are characterized by chromosomal aberrations. Here, we comprehensively characterize the order of occurrence of these complex genomic events underlying MM development using 500 MGUS, and MM samples. We identify hyperdiploid MM (HMM) and non-HMM as genomically distinct entities with different evolution of the copy number alterations. In HMM, gains of 9,15 or 19 are the first and clonal events observed as clonal even at MGUS stage. These events are thus early and may underlie initial transformation of normal plasma cells to MGUS cells. However, CNAs may not be adequate for progression to MM except in 15% of the patients in whom the complex subclonal deletion events are observed in MM but not MGUS. In NHMM, besides the driver translocations, clonal deletion of 13 and 1q gain are early events also observed in MGUS. We combined this information to propose a timeline for copy number alteration.