Search

Progression and persistence of malignancies are influenced by the local tumor microenvironment, and future eradication of currently incurable tumors will, in part, hinge on our understanding of malignant cell biology in the context of their nourishing surroundings. Here, we generated paired single-cell transcriptomic datasets of tumor cells and the bone marrow immune and stromal microenvironment in multiple myeloma. These analyses identified myeloma-specific inflammatory mesenchymal stromal cells, which spatially colocalized with tumor cells and immune cells and transcribed genes involved in tumor survival and immune modulation. Inflammatory stromal cell signatures were driven by stimulation with proinflammatory cytokines, and analyses of immune cell subsets suggested interferon-responsive effector T cell and CD8+ stem cell memory T cell populations as potential sources of stromal cell–activating cytokines. Tracking stromal inflammation in individuals over time revealed that successful antitumor induction therapy is unable to revert bone marrow inflammation, predicting a role for mesenchymal stromal cells in disease persistence. Multiple myeloma disease progression and therapy response are influenced by the bone marrow niche in which the tumor cells reside. To characterize this supportive niche, Cupedo and colleagues use single-cell transcriptomic analysis of bone marrow stromal cell populations from individuals with multiple myeloma. They identify a myeloma-specific inflammatory mesenchymal stromal cell (iMSC) population that spatially colocalizes with tumor cells. Anti-myeloma induction therapy does not influence iMSC presence, suggesting a role for bone marrow inflammation in myeloma persistence or relapse.

Introduction Multiple myeloma (MM) is a malignant plasma cell disorder of which the prognosis has significantly improved since the introduction of proteasome inhibitors (PIs) and immune modulatory drugs (IMiDs) in standard-of-care treatment protocols. Despite this progress, many patients still suffer from progressive disease, of which the underlying biological mechanisms are mainly unknown. To elucidate these, we have studied the genomic evolution of MM tumor samples in 29 patients before and after receiving a PI-based and/or IMiD-based treatment, using whole exome sequencing (WES) and mRNA sequencing (RNA-Seq). Methods Patient samples were selected from the Norwegian Biobank for Multiple Myeloma and the HOVON-87/NMSG-18 MM and EMN-02/HOVON-95 MM studies. Tumor DNA was isolated from CD138-positive MM cells with control DNA from peripheral blood samples. WES libraries were prepared using the SureSelectXTsample prep kit and the SureSelectXT Human All Exon V5 target 50 Mb kit (Agilent), followed by paired-end sequencing on a HiSeq2500 instrument (Illumina). Somatic, non-synonymous variants (SNSVs) were called using MuTect and Strelka. Copy number aberrations (CNAs) were estimated using Sequenza. RNA-Seq libraries were generated using the TruSeq® Stranded mRNA kit (Illumina).DESeq2 paired analysis was performed in R Studio to find differentially expressed genes. RNA-Seq expression data from diagnosis/relapse pairs from patients treated with a PI and/or IMiD were selected from the CoMMpass IA10 release database and used as validation cohort. Results We obtained 21 diagnosis/relapse pairs, as well as 8 relapse/relapse pairs, with a median time between samples of 21 months, respectively 16 months. In addition, for 3 of the patients, we had a 3rd sample included. We found a median of 54 SNSVs in our cohort, with an increase in mutational load from the first to the second sample (median 44 to 61). Three different patterns of tumor evolution were observed, confirming previous reports:stable evolution (29% of patients), where the tumor had no or minor changes;linear evolution (29% of patients), where there were acquired mutations and/or CNAs at relapse;differential clonal response (42% of patients), where there was a disappearance of certain mutations/CNAs at relapse and appearance of new ones, suggesting a shift in dominance of different clones. Of interest, of the 7 relapse-relapse tumor pairs that were included in the analysis, 5 were defined to have a differential clonal response, while the remaining 2 had linear evolution, suggesting that the tumors are more prone to genomic change later in the disease course.Tumors shifting their clonal dominance tended to select for a clone with more high-risk features later in the disease course, as illustrated by the appearance of a deletion of chromosome 17p, TP53 mutations and a gain of chromosome 1q. There was a shorter average time interval between sample 1 and 2 for those having a stable evolution pattern (average 12 months, range [5-16]), than those having a differential clonal response (19 months [5-70]), and the highest interval was in patients with linear evolution patters (29 months [15-50]). Tumors having a differential clonal response and linear evolution, showed more often a deeper treatment response (43% CR/nCR, 40% VGPR and 22% CR/nCR, 56% VGPR, respectively) compared to those with stable evolution patterns (14% VGPR), suggesting that tumors that respond well to treatment are more prone to evolve. RNA-Seq data showed a higher expression of genes involved in G2M checkpoint, E2F targets and mitotic spindle at relapse. In line with this, relapsed tumors were found to have an increased proliferation index (GEP; Zhan et al, Blood, 2006). This was confirmed in RNA-Seq data from 27 diagnosis-relapse samples from the CoMMpass dataset. Conclusion This study has performed a comprehensive genomic and transcriptomic analysis of the clonal evolution of MM tumors after treatment with PIs and IMIDs. Our data suggest that clones with high-risk factors and increased expression of genes involved in proliferation and cell cycle regulation are selected for under the pressure of these treatment regimens. The data also suggest that there is a relation between the pattern of genomic evolution and the obtained depth of response, which deserves further investigation. Disclosures Sonneveld: Janssen: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Karyopharm: Honoraria, Research Funding; BMS: Honoraria, Research Funding.

Background The introduction of proteasome inhibitors (PIs) and immune modulatory drugs (IMiDs) to multiple myeloma (MM) treatment protocols has drastically improved the overall quality and duration of response. This rationalized challenging the role of upfront high dose melphalan (HDM) followed by autologous stem cell transplantation (ASCT) versus chemotherapy alone as intensification treatment in four recent phase III trials. Yet, these showed uniformly that upfront HDM is still superior to non-transplant intensification alternatives including PIs and/or IMiDs. However, HDM's mechanism of action involves induction of interstrand crosslinks and double-strand DNA breaks that cause collateral damage in both healthy cells (toxicity) and tumor cells, which may induce strong selection pressure on the outgrowth of resistant clones at relapse. We therefore hypothesized that certain low-risk patients could save HDM as salvage treatment and that this would improve their overall survival (OS). Methods We chose to combine three robust classification tools in MM that historically have shown a consistent performance across diverse patient cohorts: (1) International Staging System (ISS), (2) deletion of chromosome 17p (del17p) by Fluorescent in Situ Hybridization (FISH) (cutoff ≥10%) and (3) SKY92 high-risk (HR) classifier, based on gene expression profiling (GEP) of MM cells. By combining these scores, we classified ultra-low risk (uLR), intermediate-risk (IR) and HR MM as follows: uLR: ISS = 1, del17p = absent, SKY92 HR = absent. IR: ISS = 2 or 3, del17p = absent, SKY92 HR = absent. HR: ISS = 1, 2 or 3, del17p and/or SKY92 HR = present. The effect of intensification treatment on progression-free survival (PFS) and OS in these risk groups was evaluated in the phase III EMN-02/HOVON-95 MM trial (EudraCT 2009-017903-28). We focused on chemotherapy-naive MM patients aged ≤65 years, who received bortezomib, cyclophosphamide and dexamethasone (3-4xVCD) as induction therapy, followed by randomization 1 (R1) between bortezomib, melphalan and prednisone (4xVMP) and 1xHDM+ASCT, R2 between bortezomib, lenalidomide and dexamethasone (2xVRD) versus no consolidation and lenalidomide maintenance for all. At baseline, bone marrow was collected in the MM biobank at Erasmus MC Cancer Institute, the Netherlands. On this, CD138+ enrichment was performed, followed by a flowcytometric purity check, FISH analysis for del17p and GEP using HG U133 Plus 2.0 arrays (Affymetrix). PFS was defined as the time from R1 to progression or death, whichever occurred first. P-values were not adjusted for multiple testing. Results In our biobank region, 435 patients were randomized between VMP and 1xHDM, of whom ISS data were available for all, del17p status for 87%, SKY92 classification for 41% and all three risk factors for 38% of patients. Of these, 33% were ISS stage I, 47% ISS stage II, 20% ISS stage III, 10% had a del17p and 20% were SKY92 HR. A total of 43 (26%), 83 (50%) and 41 (25%) patients were classified as uLR, IR and HR, respectively. Our risk classification was both significantly associated with PFS (logrank p < 1x10-5; 4-year PFS of 64% in uLR, 49% in IR and 24% in HR) and OS (p < 1x10-4; 4-year OS of 85% in uLR, 77% in IR and 47% in HR). HR patients had a superior PFS with 1xHDM over VMP (p = 0.003), confirming previous reports. OS was related to intensification arm in both uLR and HR patients, however, in opposite direction: uLR patients treated with VMP had a better OS than those treated with 1xHDM (p = 0.047, 4-year OS of 95% with VMP versus 72% with 1xHDM); whereas OS was better after 1xHDM in HR patients (p = 0.017, 4-year OS of 68% with 1xHDM versus 22% with VMP). We found a significant interaction between intensification treatment and risk group for both PFS (likelihood ratio p = 0.03) and OS (p = 0.005). This indicates that there is indeed a differential treatment effect on survival between risk groups. Conclusions Although our findings are preliminary and need further validation, we are the first to identify a low-risk, transplant-eligible MM subgroup that - in contrast to high-risk MM patients - may benefit from receiving upfront VMP versus 1xHDM+ASCT. Moreover, this illustrates for the first time how combined molecular and clinical subclassification in MM may identify patients that benefit from alternative treatment strategies, such as prolonged bortezomib and lenalidomide. Ultimately, this may result in risk-adapted treatment approaches. Disclosures Beksac: Janssen Cilag: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Deva: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Ludwig:BMS: Speakers Bureau; Cilag-Janssen: Speakers Bureau; Celgene: Speakers Bureau; Amgen: Research Funding, Speakers Bureau; Takeda: Research Funding, Speakers Bureau. Kuiper:SkylineDx: Employment. van Vliet:SkylineDx: Employment. Hajek:Takeda: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding. Dimopoulos:Janssen: Honoraria; Celgene: Honoraria; Takeda: Honoraria; Amgen: Honoraria; Bristol-Myers Squibb: Honoraria. Palumbo:Takeda Pharmaceuticals Inc.: Employment. Cavo:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; AbbVie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Sonneveld:Karyopharm: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; BMS: Honoraria, Research Funding.

Background Deletion of chromosome 17p (del17p) is detected in 10% of multiple myeloma (MM) patients at diagnosis and is associated with both a dismal prognosis and increased prevalence after treatment. Even though this suggests that it might be a driver of disease progression, relatively little is known about the genomic landscape of these tumors. With this study, we aimed to identify recurrent aberrations in a large cohort of del17p MM patients and to assess their prognostic value within this patient group. Methods The study design consisted of a discovery phase and a validation phase. For the discovery phase, 44 newly diagnosed MM (NDMM) patients were included with a del17p in at least 50% of plasma cells, as detected with fluorescent in situ hybridization (FISH). From 12 del17p patients, 2 or 3 tumor samples were available to analyze clonal evolution during disease progression. DNA was isolated from peripheral blood and CD138+ enriched bone marrow mononuclear cells, followed by a custom capture of the whole exome, Chr17p and the IgH, Igk, IgL and MYC regions (SeqCap EZ Exome Plus, Nimblegen) and paired-end sequencing. Significantly mutated genes were determined with MutSigCV and significantly deleted or amplified genomic regions with GISTIC2. Single nucleotide variants (SNVs) in TP53, FAM46C, KRAS, NRAS, DIS3 and BRAF were validated using a custom amplicon panel (TruSeq Custom Amplicon Assay v1.5, Illumina), followed by deep sequencing on a MiSeq System. Findings were validated in a cohort of 463 NDMM patients of the UK Myeloma XI trial, from which whole exome sequencing data were available for paired tumor and germline DNA (Walker et al. - J Clin Oncol 2015). All samples in both the discovery and the validation cohort were reanalyzed with one bioinformatic pipeline, from alignment to variant calling. The copy number status of TP53 was determined with Sequenza, followed by selection of del17p samples after manual inspection of the results. From a third cohort of 233 MM patients with progressive disease (PDMM) treated at the University of Arkansas for Medical Sciences (UAMS), 406 cancer-related genes were paired-end sequenced from tumor DNA with the FoundationOne Heme assay (He et al. - Blood 2016). Results In the discovery cohort, we identified a commonly deleted region (CDR) on Chr17p of 235 kb, in which one or more somatic, nonsilent aberrations (SNSA) in TP53 were detected in 25/44 (57%) patients (adj. p In the UK Myeloma XI cohort, we detected a del17p in 32/463 (7%) of patients. Of these, 15/32 (47%) had an SNSA in the remaining allele. Follow-up data were available of 73/76 del17p NDMM patients from both cohorts (n=46 transplant-eligible (TE), n=27 nontransplant-eligible (NTE)), with a median follow-up time of 17 months. TP53 mutated patients had a worse overall survival (OS) than TP53 wildtype patients (p=0.02), of which the strongest effect on OS was seen of TP53 missense mutations (p We went on to look in the FoundationOne cohort of PDMM patients and detected a del17p in 37/233 (16%) of patients and an SNSA in TP53 in 25/37 (68%) of del17p PDMM patients, which is a higher rate than in the 2 NDMM cohorts. Conclusions (1) TP53 is somatically mutated in half of del17p MM patients at diagnosis, validated in 2 independent cohorts, and this percentage is higher in del17p MM patients at progression. (2) Particularly TP53 missense mutations have a significant, negative impact on both PFS and OS in del17p MM patients. (3) The rest of the genomic landscape of del17p MM is characterized by significant mutations in FAM46C and KRAS, as well as deletions of RB1, TRAF3 and FAM46C. Disclosures Ashby: University of Arkansas for Medical Sciences: Employment. He:Foundation Medicine, Inc: Employment, Equity Ownership. Bailey:Foundation Medicine, Inc: Employment, Equity Ownership. Mughal:Foundation Medicine: Employment, Equity Ownership. Waage:Novartis, Amgen, Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen: Speakers Bureau; Celgene: Consultancy, Honoraria. Avet-Loiseau:celgene: Consultancy; sanofi: Consultancy; janssen: Consultancy; amgen: Consultancy. Jackson:Takeda: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Other: Travel support, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; MSD: Consultancy, Honoraria, Speakers Bureau; Roche: Consultancy, Honoraria, Speakers Bureau. Morgan:Univ of AR for Medical Sciences: Employment; Takeda: Consultancy, Honoraria; Janssen: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Bristol Meyers: Consultancy, Honoraria. Sonneveld:Amgen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding.

Introduction: Customized gene panel sequencing is an attractive approach to genomic tumor characterization in clinical care. Based on published MM exome data we developed a MM Mutation Panel (M3 P) that includes the most commonly mutated genes, actionable drug targets, genes targeted by current standard of care (SOC) therapies and which allows tracking of clonal evolution, copy number and sample purity. Methods and Material: M3 P (v3.0) covers 88 genes (1327 amplicons, 181kb). MM samples from 504 patients (pts) have been analyzed (corresponding germline in 81%) through collaborations between Mayo Clinic and Hospital-12-de-Octubre (Madrid, Spain), the DSMM and GMMG (Würzburg, Ulm, Freiburg and Heidelberg, Germany) and the HOVON trial groups (Rotterdam, The Netherlands). The investigated cohort includes 410 untreated pts (81%), which includes a high risk cohort of 72 pts with del17p, 25 paired samples with later follow up from the same cohort, and 94 relapsed patients, of which 50 were relapsed and refractory. Results: Overall coverage per mutation averaged >500x depth. We identified 945 variants (1.9 per pt) and in 83% of the pts a mutation was found. Clonal heterogeneity was assessed with mutations ranging from 3%-100% variant reads suggesting the presence of a significant number of subclones (e.g. 21% of mutations were in < 10% of reads). The mutation incidence was compared with and closely resembles the most recent MM comprehensive genomic data from the MMRF CoMMpass study: We compare here all pts sequenced by M3 P, untreated pts sequenced by M3 P and CoMMpass: KRAS (24%/23%/24%), NRAS (20%/20%/18%), DIS3 (13%/14%/10%), BRAF (9%/7%/6%), FAM46C (6%/6%/8%) and TRAF3 (6%/6%/7%). TP53 mutation incidence, however, was significantly increased in our cohort (14%/12%/4.2%), a difference explained by the inclusion of del17p (untreated) and relapsed refractory MM in panel sequenced pts, cohorts with elevated incidences of TP53 mutations (32% / 26% respectively). Potentially actionable targets include BRAF mutationsin 43 patients (9%), with druggable p.V600E in 19 or 5%, 8 pts (2%) with FGFR3 (p.R248C and p.G375C one patient each), p.R132 mutation in 4 out of 5 IDH1 (1%) and p.R172K IDH2 mutation in 1 of 3 (1%) pts. Mutations in the MAPK pathway (NRAS, KRAS, BRAF) were detected in 59% of pts, ranging from 36% untreated MM to 72% in refractory MM. Similarly, the CRBN/CUL4B/IKZF1/IKZF3/IRF4 pathway, important for IMiD function, harbored a significant enrichment of mutations in advanced disease (6% untreated vs 17% relapsed), including CRBN mutations (0.5% vs 7%). Nine of 17 IRF4 mutations were located at the p.K123R hotspot, with minor difference between early or late disease (1% vs 3%). Notably, in 8 of 9 pts with CRBN mutation and clinical information, all were unresponsive to IMiD therapy, supporting association of these mutations with resistance to IMiDs. Conversely, M3 P genes related to other SOC therapies, including NR3C1 (targeted by steroids) and 5 proteasome subunit genes (proteasome inhibitors), were rarely mutated across the cohorts not exceeding 1% mutation incidence for each gene. Significant differences in DIS3 and FAM46C mutation incidences were observed across cohorts: DIS3 mutations are more common in untreated pts with a 1.7 fold increased predominance (14% untreated and 8% treated). FAM46C has an expected incidence of 8% but was rarely mutated in untreated del17p high risk disease with only one of 100 patients harboring both mutations. The significance of this finding needs to be determined but implies a possible overlap in function. Finally we assessed impact on survival of the mutation variants identified in 142 untreated Mayo patients and found STAT3 mutations negatively impacting PFS (p=0.034) and OS (p=0.001). This gene is rarely mutated in MM (2% of the total cohort) thus the sample size was small and this finding needs further validation. Conclusion: We here describe 504 MM patients sequenced using the M3 P gene panel, which identified mutations in >80% of investigated patients, overlaps well with published whole exome sequence data and provides clinically relevant information. New findings were the high frequency of minor clones, the relative lack of overlap of del17 and FAM46C mutation, a higher frequency of DIS3 mutation at diagnosis compared to relapse, the prognostic significance of STAT3 mutation and the frequent presence of CRBN pathway mutation in drug resistant relapsed patients. Disclosures Sonneveld: Janssen-Cilag, Celgene, Onyx, Karyopharm: Honoraria, Research Funding; novartis: Honoraria. Mai:Janssen-Cilag: Other: Travel Grant; Onyx: Other: Travel Grant; Mundipharma: Other: Travel Grant; Celgene: Other: Travel Grant. Goldschmidt:Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Onyx: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Millenium: Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Chugai: Honoraria, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau. Knop:Celgene Corporation: Consultancy. Kull:Bristol-Myers Squibb: Membership on an entity's Board of Directors or advisory committees. Martinez-Lopez:Novartis: Honoraria, Research Funding; Bristol-Meyer Squibb: Honoraria; Celgene: Honoraria; Janssen: Honoraria. Einsele:Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau; Amgen/Onyx: Consultancy, Honoraria, Speakers Bureau. Raab:Novartis: Research Funding. Stewart:Oncospire Inc.: Equity Ownership; Celgene: Consultancy; Novartis: Consultancy; BMS: Membership on an entity's Board of Directors or advisory committees.

Introduction Multiple myeloma (MM) is characterized by a highly variable disease course, which can be traced to initiating and acquired genomic events. Whole exome analysis of matched tumor and germline DNA from 287 MM patients identified recurrently somatically mutated genes (RSMGs) (Lohr et al. - Cancer Cell 2014, Bolli et al. - Nat Commun 2014). Despite the fact that these RSMGs affect pathways that are biologically important in MM, the clinical relevance of many of these genes in the context of conventional prognostic markers remains to be elucidated. Aims The aims of this pilot study were: (1) To validate the prevalence of RSMGs in our newly diagnosed MM patient cohort; (2) To assess the correlation between RSMGs, clinical parameters and outcome; (3) To thereby identify the potential clinical usefulness of introducing RSMG mutational profiling in larger MM trial cohorts. Material and Methods CD138+ enriched MM cells and peripheral blood were obtained with informed consent from chemotherapy-naive patients, participating in 3 clinical trials: HOVON-65/GMMG-HD4, HOVON-87/NMSG-18 and Carthadex (EudraCT number 2004-000944-26, 2007-004007-34 and 2009-014922-40, respectively). Matched tumor and germline DNA were sequenced on an Ion Torrent sequencing platform (PGM, Life Technologies), using the M3 P Mutational Panel v3.0, comprising 1327 customized oligos (Life Technologies), targeted at the coding sequences of 88 MM-relevant genes, including the RSMGs. Somatic mutations were considered positive when present in >=10% of tumor reads and All statistical analyses were performed in SPSS version 23, using the log-rank and Mann-Whitney U-test, with the Bonferroni test to correct for multiple comparisons. Results A total of 206 DNA samples were sequenced from 103 patients (HOVON-65/GMMG-HD4 (n=16), HOVON-87/NMSG-18 (n=67), Carthadex (n=20)) with an average coverage of 574x in tumor DNA, 451x in germline DNA and an overall coverage of 98%. We collected follow-up data from 102/103 patients, with a median follow-up time of 30 months. 168 somatic mutations were detected in 44/88 genes. 82% of patients had at least 1 somatic mutation. Genes most frequently mutated were: (1) NRAS (26%), (2) KRAS (22%), (3) DIS3 (14%), (4) FAM46C (9%), (5) TP53 (7%) and (6) BRAF (6%) (Figure 1). Of note, NRAS and KRAS mutations were mutually exclusive in our cohort. Moreover, all TP53 mutations were located in its DNA binding domain. Three out of 6 BRAF mutations were predicted to cause a V600E amino acid change. We focused on these 6 RSMGs in all further analyses. Correlating mutational status with Progression Free Survival (PFS) and Overall Survival (OS) showed that TP53 mutated patients had a significantly shorter PFS compared to those with wildtype TP53 (adj. p-value=0,018; n=7 versus n=95). Comparing the mutational status of the 6 RSMGs, transplant versus non-transplant protocol, number of mutated genes in the M3 P panel, del17p and t(4;14) status, EMC92 score and ISS stage between patients with a PFS 1 year (n=23 versus n=79), only showed a significant correlation with TP53 mutational status (adj. p-value=0,012). TP53 mutational status remained the only significant prognostic factor when comparing patients with an OS 1 year (adj. p-value=0,003; n=13 versus n=89). When comparing the number of mutated genes, del17p and t(4;14) status, EMC92 score, transplant versus non-transplant protocol and ISS stage between TP53 mutated and wildtype MM, TP53 mutated patients had a significantly higher number of mutated genes in the M3 P panel (adj. p-value=0,001). Conclusions (1) With the M3 P Mutational Panel, we confirm the published prevalence of RSMGs in MM in our cohort of chemotherapy-naive patients. NRAS, KRAS, DIS3, FAM46C, TP53 and BRAF are the most frequently mutated genes. (2) TP53 mutational status is the strongest unfavorable prognostic factor in our cohort and it seems to be associated with greater mutational burden. Validation in a more extensive population is planned. (3) This warrants further investigation of the mutational status of these genes in larger clinical trial cohorts, enabling a more robust comparison with conventional prognostic markers in a multivariate analysis. Disclosures Broijl: Celgene: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees. Zweegman:Takeda: Research Funding; Janssen: Research Funding; Celgene: Research Funding. Sonneveld:Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Karyopharm: Research Funding; SkylineDx: Membership on an entity's Board of Directors or advisory committees.

Background The introduction of novel treatment strategies against multiple myeloma (MM) has resulted in a major improvement in the overall outcome, which has led to an increased need for highly sensitive methods to detect minimal residual disease (MRD) in each patient. MRD assessment by multicolor flowcytometry (MFC) has been shown to be of prognostic value in many treatment protocols over the last decade, making it an attractive method to assess response in clinical trials. However, it is currently not known (1) what the best timing is to perform MFC MRD analysis in the context of a treatment protocol including induction, intensification, consolidation and maintenance treatment, (2) which patients should be selected for this analysis, and (3) what its feasibility is in a large international trial. The ongoing EMN-02 MRD Study aims to answer these questions within the framework of the EMN-02/HOVON-95 MM trial. Here, we describe our methods and the results of our first quality assessment round to compare the sensitivity of the used protocols. Methods The EMN-02/HOVON-95 MM trial is a randomized, multicenter, phase 3 trial in which newly diagnosed MM patients 18-65 years received 4 cycles of bortezomib, cyclophosphamide and dexamethasone (VCD) as induction treatment, followed by a first randomization between either 4 cycles of bortezomib, melphalan and prednisone (VMP), or high dose melphalan (HDM) and 1 or 2 ASCT as intensification treatment. Subsequently, patients were randomized between 2 cycles of bortezomib, lenalidomide and dexamethasone (VRD) or no consolidation treatment, followed by lenalidomide maintenance treatment for all until progression or toxicity occurred. Patients undergoing a bone marrow (BM) aspiration for complete response (CR) confirmation according to the International Myeloma Working Group (IMWG) criteria (Rajkumar et al. - Blood 2011) anytime during the trial were eligible for the EMN-02 MRD Study. BM samples from patients from 13 European countries were sent to 4 central MFC MRD laboratories in the Netherlands (A), Czech Republic (B), Denmark (C) and Italy (D), either using the strict Euroflow protocol (A) (Van Dongen et al. - Leukemia 2012) or Euroflow-based methods (B, C & D). In order to check compatibility between protocols, 5 bone marrow samples from MM patients with a clinical response ranging from progressive disease (PD) to CR were each divided in equal volumes and sent to the respective laboratories on 3 different days. MFC MRD analysis was performed on a FACS Canto II (BD) (A-C) or Coulter Navios flowcytometer (D). Protocols A, B & C used the Euroflow Plasma Cell Disorder (PCD) tube 1 and 2 combination of antibodies, containing the backbone markers CD138-PO, CD38-FITC, CD45-PB and CD19-PE-Cy7, with CD56-PE, B2micro-PerCP-Cy5.5, cyIgK-APC and cyIgL-APC-C750 in tube 1, and CD28-PE, CD27-PerCP-Cy5.5, CD117-APC, CD81-APC-H7 in tube 2. Protocol D had the same backbone markers (CD138-PerCP-Cy5.5, CD38-PB, CD45-KO and CD19-PE-Cy7), together with CD27-PE, CD81-FITC and CD20-APC in tube 1 and cyIgK-FITC, cyIgL-PE, CD56-APC and CD117-APC-AF 750 in tube 2. Bulk lysis was performed in protocols A, B and D. Every laboratory acquired at least 2x10e6 leukocytes (or at least 1x10e4 plasma cells) and performed data-analysis in Infinicyt version 1.6 or higher (A, B & C) or Navios Kaluza (D), using a threshold ranging from 10-25 aberrant plasma cell events as cutoff for MFC MRD positivity. Results Acquisition of events occurred the day after BM aspiration for all samples. The total number of acquired events per sample was dependent on the level of MRD, ranging from 3x10e5 to 2x10e7 leukocytes. MFC MRD results were very comparable between labs with a 1:1 correlation between results at every level of residual disease, being 1x10e-2, 1x10e-4, 1x10-4, 1x10e-5 and 1 MRD negative sample at the level of Conclusions This is the first time that a European framework has been set up between laboratories to test MFC MRD analysis in the context of an international trial. The sensitivity of the protocols has been compared in a quality assessment round, which showed a high correlation of results. Disclosures Oliva: Amgen: Honoraria; Takeda: Honoraria; Celgene: Honoraria. Boccadoro:CELGENE: Honoraria, Research Funding; Mundipharma: Research Funding; Janssen: Honoraria, Research Funding; Amgen: Honoraria, Research Funding; Abbivie: Honoraria; SANOFI: Honoraria, Research Funding; Novartis: Honoraria, Research Funding; BMS: Honoraria, Research Funding. Hajek:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Sonneveld:Celgene: Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Karyopharm: Consultancy, Honoraria, Research Funding. Palumbo:Takeda: Employment, Honoraria; Janssen Cilag: Honoraria.