Citations

Abstract H-MM affects about 40–50% of patients, and a similar proportion of MGUS/SMM. The genetic evolution of the disease and the clinical implications of the co-existence of 13q- or t(14q32) are unknown. We conducted a global survey of genetic abnormalities in H-MM in order to describe genetic evolution pathways. H-MM cases from the Mitelman cancer genetic database were combined with cases from the Mayo Clinic MM genetic database. All abnormalities (regional/whole chromosome gains/losses, breakpoints and translocations) were plotted against a 344-chromosome band profile created in a matrix format, and the number of genetic abnormalities per tumor (NAPT) logged. The abnormalities present in more than 5% of tumors were considered recurrent and each karyotype was scored for the presence or absence of each of the recurrent abnormalities. To investigate the temporal pattern of acquisition of genetic abnormalities, all tumors with a given abnormality were selected and the distributions of NAPT plotted. The modes of these distributions were used as a value of ‘lateness’, referred to as time of occurrence (TO). The impact of co-existence of 13q- and t(14q32) on progression free survival (PFS) and overall survival (OS) in H-MM was determined for MM patients entered into an Eastern Cooperative Oncology Group chemotherapy trial. Four hundred and sixty-nine H-MM patients were included in the karyotypic analysis. The median chromosome number was 53 (range 48–74) and the median NAPT was 10 (range 1–25). The distribution of NAPT revealed a normal distribution, suggesting an obligatory acquisition of a given number of genetic abnormalities. The most common abnormalities were trisomies of chromosomes 3,5,7,9,11,15,19 and 21 affecting a third or more of the patients. Deletions and abnormalities of even-numbered chromosomes occur in 20% or less of patients. None of the more than 300 specific translocations detected were recurrent. However, 5 translocation breakpoints were recurrent including 14q32, 8q24 and 11q13. TO analysis suggest that for H-MM, the trisomies are early genetic events, translocations occur midway and deletions tend to be later events. Amongst the trisomies, correlation analysis does not suggest a particular order of acquisition. Clustering analysis using principal component analysis suggests that in H-MM, IgH translocations are secondary events associated with disease evolution rather than defining unique biological entities. Consistent with this, survival of H-MM patients is not affected by 13q- status but is negatively impacted by the presence of t(14q32) especially those with unknown partners (p<0.05). The data presented suggest that H-MM fit a proposed aneuploid model of cancer due to auto-catalytic chromosome reassortment (Duesberg et al Cell Cycle2003:2:202–210). The presence of tumor specific trisomies and the apparent similar phenotype induced by various combinations of trisomies are consistent with this model.

Abstract Background: Thalidomide and dexamethasone combination has been shown to be an effective therapy for multiple myeloma (MM). In newly diagnosed patients with MM, the combination results in overall response rates of over 70% of patients. However, a considerable number of patients do not respond and will need to proceed to other therapies. The ability to identify patients who are unlikely to respond to particular therapies will allow tailoring of therapeutic approaches and in turn will reduce unnecessary toxicity and morbidity from lack of rapid disease control. With the availability of new technology such as gene expression profiling (GEP), this has become a possibility. We employed this approach to identify genes that can reliably predict lack of response to the thalidomide dexamethasone combination. Methods: Patient samples from the Eastern Co-operative Oncology Group clinical trial (E1A00), that compared thalidomide-dexamethasone combination with dexamethasone, and patient samples from the phase II Mayo Clinic study of thalidomide and dexamethasone, both for newly diagnosed MM, were used for this study. Thirty newly diagnosed patients who were evaluable for response were included in the analysis. GEP was performed using the Affymetrix U133A microarray platform as per manufacturer’s recommendation. The Affymetrix output (CEL files) was imported into Genespring 7.2 (Agilent Technologies) microarray analysis software, normalized across chips using GCRMA followed by per gene normalization to median. For the purposes of this study, responses were defined as reduction in the serum paraprotein (or the urinary M protein in the absence of a serum M protein) of >=50% (PR), 25 to 49% (MR), increase of >=50% (PD) and stable disease for the remaining. Results: Five of the 30 patients had no response to the thalidomide Dexamethasone therapy. Using the class prediction tool available in Genespring (Support Vector Machines), we identified 25 genes that reliable predicted non responders (PD, NC) from the responders (MR, PR, and CR). See table for a list of predictive genes with identified genes. Conclusion: Using a combination of two datasets we have identified a set of genes that can be used to reliably predict lack of response to thalidomide and dexamethasone in patients with newly diagnosed MM. We think that this represents a step towards creation of custom microarrays spotted with genes that are capable of predicting lack of response (or response) for the purpose of tailoring therapy to the patient. Gene Predictive strength hypothetical protein FLJ20719 1.655 Tubulin alpha 6 1.653 SEC3-like 1 (S. cerevisiae) 1.649 Ribosomal protein L18 1.546 Ribosomal protein L4 1.432 Tubulin alpha 6 1.409 cleavage stimulation factor 1.393 Tubulin, alpha, ubiquitous 1.393 CD99 antigen 1.38 hmel2 1.346 Leptin receptor 1.291 Integrin-linked kinaseSMC4 structural maintenance of chromosomes 4-like 1 1.269 Cornichon homolog 1.255 Williams-Beuren syndrome chromosome region 5 1.217 Ubiquitin specific protease 1 1.2 Sarcoma antigen NY-SAR-91 1.2

Abstract Waldenström’s macroglobulinemia (WM) is an incurable low-grade lymphoproliferative disorder characterized by bone marrow (BM) infiltration of a clonal population of small B-lymphocytes, plasmacytoid lymphocytes and plasma cells that secrete monoclonal IgM antibody. Because it is difficult to obtain tumor metaphases for karyotype studies, few recurrent chromosomal abnormalities have been reported and the genetic basis of the disease remains poorly defined. Therefore, we performed a comprehensive high-resolution study to identify genomic abnormalities involved in WM pathogenesis. Fifty-seven WM patients were analyzed using a combination of array-based comparative genomic hybridization (aCGH)(N=42); gene expression profiling (GEP)(N=22), DNA sequencing (N=24) and cIgM-FISH (N=57). Agilent 244A and Affymetrix U133 platforms were used in the aCGH and GEP experiments, respectively. An NF-κB index was calculated from GEP data, as a surrogate marker of NF-κB transcription activity. NFKB2 sub cellular localization was determined by immunofluorescence staining. Overall, 83% of samples have aCGH defined chromosomal abnormalities, with a median of 3 abnormalities per patient (range 0 to 27). We identified 16 recurrent regions of copy number change found in >5% (3 or more patients); 10 deleted and 6 amplified regions. The most common abnormality was the entire or partial deletion of 6q, identified in 40% of cases. Four nonoverlapped minimal deleted regions were identified on 6q (MDR1 to MDR4), each of them being present in at least 14 of 17 patients with the abnormality. Gain of 6p was the second most common abnormality (17%) and its presence was always concomitant with 6q loss. Other recurrent deletions were 13q14 (10%) and 7q22, 8p, 11q22-q23, 11q23-q24 and 17p11-p13 (7% each). Copy gains were identified as partial or entire gains of chromosomes 18 (17%), 4 (12%) and 3 (10%), 8q (10%) and Xq27.1-q28 (10%). Three patients had either homozygous deletions or LOH with mutations affecting both alleles of TRAF3 on 14q32. TRAF3 inactivation was correlated with an increased NF-kB transcriptional signature and it was associated with activation of the non-canonical NFkB pathway. Additionally, we identified the inactivation of TNFAIP3, another negative regulator of the NF-kB pathways, in one of 24 patients. Finally, interstitial deletions identified in 4 patients at 13q14 identified a 1.1 Mb MDR, including MIRN15A and MIRN16-1. These findings confirm that focal 13q14 deletion is not restrict to B-CLL and that the MIRN15A/MIRN16-1 abnormalities might be common to several indolent B-cell diseases. Overall, we identified TRAF3 and TNFAIP3 inactivation in 5.3% and 2.4%, respectively. To our knowledge, this is the first study showing the inactivation of bona fide tumor suppressor genes in WM patients. Furthermore, these genes are negative regulators of NF-kB signaling pathway, highlighting its biologic importance in sustaining and limiting growth in WM. Mutational activation of this pathway, which is normally activated by ligand-receptor interactions within the BM microenvironment, suggest a therapeutic role for inhibitors of NF-KB pathway activation in the treatment of WM.

Abstract Our understanding of the molecular pathogenesis of myeloma is largely based on observations made from the available human myeloma cell lines. Cell lines have proved invaluable to the characterization of the known immunoglobulin translocations, recurrent deletions and amplifications, and the development of novel therapies. However, it has long been perceived that the cell lines are not representative of patient samples as they often have complex genomes and not even a single cell line has been described with a typical hyperdiploid karyotype. The absence of a hyperdiploid model system is significant as conventional cytogenetic studies of myeloma patient samples has established that patients can be almost evenly split into two broad categories of hyperdiploid and non-hyperdiploid based on their chromosome counts, with the hyperdiploid patients having recurrent trisomies of chromosomes 3, 5, 7, 9, 11, 15, 19, and 21 plus periodic gains of 1q, 18, 20 and loss of 13. Though all of the cell lines have abnormal genomes none of the previously tested cell lines had the characteristic pattern of chromosomal gains seen in hyperdiploid patients and the majority have immunoglobulin translocations, which are more commonly associated with non-hyperdiploid patients. These observations have provided the basis for the assumption that the cell lines are only representative of the non-hyperdiploid patient population. Furthermore, even though very few cell lines have been directly compared to the patient sample from which they were derived it is widely believed that the cell line genomes are unstable and have diverged significantly from the patient samples from which they were derived. Therefore, we decided to compare patient-cell line pairs available from the Mayo Clinic using Agilent 244k array-based comparative genomic hybridization (aCGH) and Affymetrix U133Plus2.0 gene expression profiling and repeated the analysis of our previously studied 46 cell lines on the higher resolution Agilent 244k platform. To date we have completed the analysis of four patient cell line pairs (ALMC-1; ALMC-2; KP-6; KAS-6/1, KAS-6/2) and have repeated our entire cell line panel on the higher resolution array. Four additional patient-cell line pairs (DP-6, JMW-1, SPMC, and VPC-6) are currently being completed. The first compelling observation from this study was that the patient sample from which KP-6 was derived is a perfect match to the characteristic hyperdiploid karyotype with a CGH defined karyotype (51, XY, −1p, +1q, +3, +7, +11, −13, +15, −16q, −17p, +19, +21). The KP-6 cell line showed a similar aCGH defined karyotype (50, X, −Y, −1p, +1q, +3q, +7, −8p, +9p, +11, +15, −16q, −17p, +17q, +19, +21) with the most significant changes occurring on the trisomic chromosomes as many transitioned from trisomies to single arm gains. Therefore, KP-6 appears to be the first myeloma cell line derived from a patient with a characteristic hyperdiploid phenotype. The ALMC patient cell line series is comprised of patient samples at diagnosis and relapse and cell lines derived from both stages. The two patient-cell line pairs only show five and two aCGH definable changes, respectively. In comparison the two matched patient sample pairs have diverged at six regions in the genome. The KAS patient-cell line series is actually two cell lines derived from pre- (KAS-6/1) and post-transplant (KAS-6/2) samples and the KAS-6/2 matching post-transplant patient sample. The comparison of the paired patient sample and derived cell line shows only four aCGH detectable changes. Similarly, there are only three changes between the KAS-6/1 cell line and post-transplant patient sample suggesting that the evolution of this tumor in both the patient and tissue culture is very limited. In conclusion, this study has identified the first bona fide hyperdiploid cell line, thereby providing a valuable investigative tool to better understand the biological differences between the two broad genetic categories of myeloma. Moreover, we demonstrate that the genomes of myeloma cell lines are typically stable and highly representative of the patient sample that was placed into culture to establish the cell line thereby validating their use in the study of this disease.

Abstract Events mediating transformation from pre-malignant MGUS to MM is currently not well defined. Recurrent genetic abnormalities such as t(11;14), t(4;14), hyperdiploidy and chromosome 13 deletion are already present in MGUS at relatively similar frequency to MM. The unified deregulation of D-type cyclins is also already present in MGUS. Previous GEP studies have revealed little differences between MGUS and MM. A more recent study using a large patient cohort and new generation Affymetrix genechip identifies an MGUS signature but the functional and biological significance underlying this signature is unknown. In the current study, we analyze a cohort of 22 MGUS and 101 MM from the Mayo Clinic with GEP performed on Affymetrix U133A genechip using gene set enrichment analysis, a method that analyze differentially expressed gene between 2 phenotypes of interest in the context of published or curated genesets that represent specific biological, chemical, or molecular perturbation to cells. This method increases the sensitivity of identifying low but significant changes in gene expression. We made further modification to the original method that allows assessment in individual samples rather than the average across a phenotype further increasing the specificity of the output. In this analysis, 313 genesets were significant enriched for genes over-expressed in MM compared to MGUS, representing potential activated pathways that mediate transformation. When MM samples and genesets were clustered using the enrichment score for each genesets and samples, 4 cluster of genesets emerged, one including a number of MYC genesets, one including a number of cell cycle related genesets, one including genesets related to metabolic activity and another including a number of IFN related genesets. Further dissection of these correlated genesets to identify common enriched genes (leading edge genes) led to identification of a MYC core signature, tRNA core signature, Proteosome core signature and metabolic core signature which are highly correlated. From known literature and biology, it is likely that MYC activation leads to downstream activation of protein synthesis (tRNA signature), degradation (proteasome signature), and metabolic pathway (metabolic signature). This is verified by GEP results from in vitro modulation of MYC activation in cell lines. In addition, a cell cycle core signature and IFN core signature was identified. Activation of IFN and MYC core signatures accounts for almost 90% of MM patients. The remaining patients have a metabolic signature without MYC or IFN activation. The activation of the different core signatures is significantly correlated with certain TC classes when assessed by Chi-Square test. IFN activation is significantly correlated with D1 subtypes and negatively correlated with D2 subtypes. MYC activation is negatively correlated with t(11;14). Similar patterns were observed in a validation dataset of 351 MM patients from UAMS (GSE2677) with GEP performed on the U133plus2.0 chip. These results are validated at the protein level using IHC on TMA of the Mayo cohort. The activation of the IFN and MYC pathway may represent predominant mechanism in MGUS to MM progression.

Abstract We have successfully generated the first immuno-competent transgenic mouse model of multiple myeloma (MM), Vk*MYC, in which sporadic MYC activation in the germinal center is AID dependent and mediated by the somatic hypermutation process. All of Vk*MYC mice develop monoclonal PC expansion by 50 weeks of age, that is manifested by high levels of serum IgGs and major M-spikes by SPEP. The PCs in Vk*MYC mice are fully differentiated, somatically mutated, have a very low proliferation index and are found exclusively in the BM. Associated with the long lifespan (medium survival = 661d), Vk*MYC mice develop anemia and diffuse bone disease (osteoporosis with low bone mineral density), with sporadic occurrence of lytic bone lesions and hind limb paralysis. The phenotypic fidelity of the Vk*MYC mice translates in a therapeutic fidelity, as Vk*MYC mice show response to known clinically active anti-myeloma drugs (bortezomib, melphalane, dexamethasone), but not to drugs that have shown no clinical activity as single agents (vincristine, hydroxyurea, fludarabine). Furthermore, acquired bortezomib resistance could efficiently be induced in Vk*MYC mice after only four cycles of suboptimal treatment, and studies are in progress to identify genetic events associated with bortezomib resistance. Preliminary aCGH experiments on a high resolution Agilent 244K array, using genomic DNA from six Vk*MYC CD138+ selected PCs, showed that the genomic complexity of Vk*MYC tumors is quite low, with only few unbalanced rearrangements, such as trisomy of chromosome 15 detected in two samples or trisomy 9 present in another tumor. The most common abnormalities found are small focal monoallelic deletions, six of which are present in more than one tumor. A focal homozygous deletion of several exons of a gene was identified in two tumors samples. Remarkably, a comparative analysis of the syntenic chromosomal region in human MM cell lines and primary patient samples identified similar recurrent homozygous deletion in this putative novel tumor suppressor gene. Overall, these data suggest that the genomic complexity in this inbred strain of transgenic mice is significantly less then in patients with MM, simplifying the search for critical loci involved in MM tumorigenesis and drug resistance and further validate the Vk*MYC mice as a particularly faithful model of human MM.

Abstract Table 1. Samples to p53 deletions p 53 deletion FISH aCGH FISH and aCGH MGUS 142 - - SMM 108 - - Newly diagnosed MM - 182 - Relapsed/refractory MM 62 156 19 HMCLs - 48 - Total 312 386 19 Background: Inactivation of p53 by mutation or allelic loss is a rare event in multiple myeloma (MM) at the time of disease diagnosis and believed to be more common in the late stages of the disease. Here we defined the prevalence of p53 deletions in monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), newly diagnosed MM, relapsed MM and human myeloma cell lines (HMCLs). Indirect mechanisms of p53 inactivation such as amplification of MDM2, or deletion of CDKN2A (p14ARF) were also investigated. Patients and Methods: A total of 631 MM samples and 48 HMCLs were analyzed for p53 abnormalities (Table 1) and compared with a cohort of plasma cell leukemia (PCL) previously published by us. Interphase fluorescence in situ hybridization (FISH) and highresolution array-based comparative genomic hybridization (aCGH) were used to detect p53 deletions. MDM2 amplification and p14ARF loss were evaluated by aCGH. Overall survival (OS) was estimated through Kaplan Meier method. Results: The prevalence of p53 deletions was 1.4%, 3.7%, 8.9%, 20% and 87.5% in MGUS, SMM, newly diagnosed MM, relapsed MM and HMCLs respectively (Figure 1). Of interest patients in first relapse showed a p53 deletion prevalence of 18% in comparison with 33% for patients in second relapse or more. We obtained p53 deletion status in 8 patients noted to have deletion at the time of relapse and in whom we had previous samples stored. In 7 of 8 cases deletions had been acquired (absent in the previous samples). The median OS for relapsed MM patients with or without p53 deletion were 4.2 months and 37.8 months respectively (p <0.001). MDM 2 amplification and p14ARF loss was detected in 0.4% and 2% of new diagnosed MM, 0.6% and 5.1% of relapsed MM and 2% and 29% of HMCLs respectively. Discussion: Emergence of p53 deletion/mutations denotes progression genetic events in MM. Importantly we show for the first time the overriding importance of p53 deletions as prognostic markers in relapsed MM. A molecular staging system that is based on the presence of p53 inactivation may be more powerful than classifying patients based on the loss of p53. Other abnormalities involving p53 pathway regulators like MDM2 gain and p14ARF loss are infrequent events in MM, even in advanced disease. Figure 1. Prevalence of p53 deletions Figure 1. Prevalence of p53 deletions

Abstract Introduction: Clinical development of bortezomib in multiple myeloma (MM) included pharmacogenomic gene expression profiling (GEP) of pre-treatment tumor biopsies in order to evaluate the feasibility of developing predictive classifiers in prospective clinical trials and to better define the biological pathways related to drug sensitivity. By partitioning the samples into train (n=101) and test (n=80) datasets, statistically significant classifiers of response and survival were identified and then validated [Mulligan G, et al: Blood. 2007; 109:3177–88]. Here we describe specific genes and biological pathways associated with bortezomib efficacy in relapsed MM. Methods: Using tumor GEP data from 188 patients treated with single-agent bortezomib we identified genes associated with overall survival (OS), as well as genes associated with response (R) or progressive disease (PD) after bortezomib therapy. These clinical endpoints were also analyzed with biological pathway algorithms including GSEA [Subramanian A, et al: Proc Natl Acad Sci2005; 102:15545–50] Ingenuity Pathway Analysis and Gene Ontology/GATHER. These results were then compared to GEP data from a patient subset (n=76) treated with single-agent dexamethasone and also cell lines selected for differential sensitivity to bortezomib. Results: A comparison of R and PD highlighted numerous differentially expressed genes; approximately 200 were over-expressed in R and 500 were over-expressed in PD (t-test <0.01). R-associated genes include signaling molecules like TRADD, CFLAR and TANK, while PD-associated genes included oncogenes (NRAS), apoptotic regulators (DAP3) and cancer antigens (CTAG). Pathway tools helped to integrate and extend these observations, consistently identifying NFkB activation and overexpression of adhesion pathways as R-associated. Overexpression of protein synthesis and mitochondrial pathways were PD-associated. The overexpression of pathways such as NFkB, adhesion and cytokines appear linked specifically with bortezomib and not dexamethasone sensitivity. These approaches were also applied to patient survival. In contrast to analyses of single genes, the pathway tools highlighted links between response and survival, including adhesion and inflammatory cytokine pathway expression. Conclusions: This study highlights the diversity of biological pathways expressed in MM and the utility of clinical genomics to associate pathways with activity of single-agent bortezomib.

Abstract The Multiple Myeloma Research Consortium (MMRC) Genomics Initiative was instigated to harness the power of multiple genomic approaches to further the understanding of multiple myeloma. To date, 137 samples from patients with newly diagnosed and relapsed myeloma (out of an estimated final total of 250 by the end of the year) have been subjected to expression profiling and array comparative genomic hybridization. To identify regions of recurrent copy number alteration with a high degree of confidence, we have used the Genomic Identification of Significant Targets In Cancer (GISTIC) algorithm, which detects such regions and assigns a probability to each. Application of GISTIC to the MMRC collection identified 14 significant regions of amplification and 15 significant regions of deletion. The algorithm further detects peaks of copy number change that contribute to each region’s significance. Of genes that were expressed in our dataset, a total of 64 across the genome were found to lie within the boundaries of significant amplification peaks and 30 were found to lie within significant deletion peaks. Given the likelihood that this gene collection is highly enriched for genes important in the pathogenesis of myeloma and potential therapeutic targets, it has been prioritized for further validation with the amplified genes submitted for arrayed RNAi and the deleted genes expedited for re-sequencing. In order to define a poor prognosis group, we developed and applied a model based on the gene expression dataset of Shaughnessy and colleagues. To identify pathways activated in poor prognosis disease, we applied Gene Set Enrichment Analysis with the Molecular Signatures Database. This demonstrated enrichment of multiple canonical pathways within the poor prognosis group, including those associated with proliferation, cell cycle progression and DNA repair. A search for recurrent copy number events associated with poor prognosis disease revealed that by far the most significant event, and the only one surviving correction for multiple hypothesis testing, was mono- or bi-allelic deletion of CDKN2C (p18). Interestingly, the poor prognosis group also demonstrated higher expression of p18 in those samples without bi-allelic deletion and of CDKN2A (p16). Deletion and increased expression of p18 in high proliferation index myeloma samples has previously been described. However, our analyses demonstrate the pre-eminence of p18 loss for defining poor prognosis disease compared to other recurrent copy number changes. Furthermore, it expands on work in other tumors demonstrating feedback mechanisms between cyclin dependent kinase inhibitor pathways, suggesting a more complex model of interplay between the pathways than previously described. In conclusion, the MMRC reference collection is proving an important tool in the fight to understand key genetic events in multiple myeloma and would ultimately be anticipated to contribute towards development of improved therapy for the disease.

Abstract Melphalan (M), Prednisone (P) and Lenalidomide (R) are active in the treatment of multiple myeloma (MM). We evaluated the toxicity and efficacy of MPR in a phase I/II trial. Results of phase I part were previously reported (Blood2006, 108(11) abst 3558). M 5 mg/m2 on days (d) 1–4, 60 mg/m2 d 1–4 and R 10 mg d 1–21 of a 28 day cycle was determined as MTD for the phase II study. Methods: Patients with previously untreated MM who were not candidates for stem cell transplantation, age ≥18 yr, ECOG PS 0–3, evaluable or measurable disease, ANC >1500, platelets > 100,000 and creatinine ≤ 3.0 mg/dL were eligible. All patients received aspirin 325 mg/d as DVT prophylaxis. Routine antibacterial prophylaxis was not used. G/GM-CSF was used at the discretion of the treating physician for neutropenia. Response rate (RR), confirmed on two consecutive determinations was the primary end-point. The study had 90% power to detect a RR of at least 45%. Results: Twenty-six patients were accrued between July ’06 and Feb ’08. The median age was 74 y (64 – 87y), 17 (65%) were men. Six, 13, 6, 1 (23%, 50%, 23%, and 4%) patients had ECOG PS 0, 1, 2, and 3, respectively. Three (12%), 11 (42%) and 10 (38%) patients were ISS stage 1, 2 and 3. A total of 106 cycles were administered; median 4.5 (1–13). Seventy-seven % patients experienced at least 1 grade 3 or 4 toxicity. Neutropenia (42%/8%) and thrombocytopenia (20%/8%) were the most common grade 3/4 adverse events followed by anemia (16%/0%), fatigue (8%/4%), rash (11%/0%), and hyperglycemia (4%/0%). There were 20 treatment delays in 9 patients, and 18 dose reductions (9 in R, 11 in M and 1 P) occurred in 7 patients, most commonly because of neutropenia or thrombocytopenia. Eleven patients (42%) required G-CSF treatment. Eleven patients are currently receiving treatment; 15 have gone off study (4 completed per protocol, 3 refused, 3 adverse effects, 3 unrelated illnesses, 2 other). Median follow up of survivors is 8 m (0 – 22m). Eighteen (69 %; 95%CI 48–86) patients had a PR or better according to International Myeloma Working Group Uniform Response criteria; 3 (12 %) CR, 5 (19 %) VGPR and 10 (38%) PR. Median number of cycles before achieving a response was 2 (1 – 11). Median Progression Free and Overall Survival is 16.7m (95% CI 11.2–23.0), and 23 m (95% CI: 22 – 23), respectively. Conclusions: MPR combination is feasible with a manageable toxicity profile and has significant activity in the treatment of patients with MM who are not candidates for stem cell transplant, with an overall response rate of 69%, and a CR plus VGPR rate of 31%. Grade 3 or 4 neutropenia and thrombocytopenia was the most common toxicity, seen in up to 50% of patients in this cohort of predominantly elderly patients. Dose reduction in R and/or M was required in 27% patients. No patient developed neuropathy or thromboembolic complications.