- Email: [email protected]
Next Generation Sequencing in Multiple Myeloma
Abstracts evaluation analysis is an analytic tool to inform health technology assessment processes. There are three main types of economic evaluation that differ in their approach to measure and value health benefits. Cost-effectiveness analysis defines health benefits in natural units / clinical outcomes (e.g. relapse free days, remittance duration, symptom severity, complications, etc.) Preference base measures of HRQoL are measures of benefit used in costutility analysis (e.g. QALYs). Cost-benefit analysis aims to measure health benefit in monetary terms (e.g. willingness to pay estimated in discrete choice experiments). “Piggyback” economic evaluations - i.e. those conducted alongside a clinical randomised controlled trial - allow collecting individual patient level primary economic data on resource use and preference based measures of health related quality of life (e.g. EuroQol-5D- 3L or 5L and health utility index) in parallel to clinical outcome measures. In turn, this facilitates both: investigation of the relationship between clinical and economic outcomes and development of mapping algorithms for extrapolation. To inform healthcare decision making, trial based economic evaluations need to be complemented with model based economic evaluations. Decision models provide and analytical framework that - for any given decision problem - enables consideration of all relevant alternative competing treatments over an appropriate time horizon for different populations of interest. Examples of the way in which different methods of EE could be implemented in the context of current healthcare interventions for Multiple Myeloma will be discussed during the presentation. Conclusion: The experience of health technology assessment agencies internationally indicates that trial based economic evaluation is a valuable tool to: measure the economic impact of healthcare interventions; and inform key parameters of decision analytic models. Model based economic evaluation is however increasingly recognised as the preferred tool to inform healthcare decision making.
Genomics and Microenvironment
PS-003 Next Generation Sequencing in Multiple Myeloma N.C. Munshi, N. Bolli, S. Minvielle, K.C. Anderson, G. Parmigiani, P. Campbell, H. Avet-loiseau Dana-Farber Cancer Institute and VA Boston Healthcare System, Harvard Medical School, Boston, MA, USA; Cancer Genome Project, Welcome Trust Sanger Instituite Hinxton UK; Centre de Recherche en Cancérologie Nantes-Angers UMR Inserm 892 - CNRS 6299 and Institut de Recherche Thérapeutique de l’Université de Nantes (IRTUN) 44007 Nantes, France; Unité de Génomique du Myélome, CHU Rangueil, Toulouse, France
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Initial oncogenomic studies utilizing a high-resolution analysis of recurrent copy number alterations, coupled with expression analysis in primary Multiple Myeloma (MM) cells has revealed a complex disease process accompanied by numerous genetic and epigenetic alterations. Number of highly recurrent and focal copy number alterations have been identified and these regions of amplification/
15th International Myeloma Workshop, September 23-26, 2015
deletions have been evaluated for involvement in MM pathogenesis and prognosis. With the availability of massively parallel sequencing, these oncogenomic studies are now further expanded to include various genomic changes including evaluation of mutational profile to study changes that may drive the disease as well as clonal content in MM. An earlier publication in 29 patients (22 whole genomes and 17 whole exomes) used deep sequencing and identified unique recurrent mutations that may have biological importance. These genes include histone methyltransferases, transcription factor IRF4, BRAF, genes involved in protein translation, and surprisingly genes involved in blood coagulation. Two subsequent larger studies including one from our group have identified various genomic characteristics. Myeloma cells on an average has between 50-60 mutations; there is no universal mutation that drives the disease in a large majority of patients; in fact frequency of no single mutation is greater than 15-20%, in fact most are less than 10%. Importantly, the 3 most common mutations involve MEK/ERK pathway genes namely N-Ras, K-Ras and BRAF. An important observation from this study has been significant genomic heterogeneity in myeloma. Mutations were often present in subclonal populations, and multiple mutations within the same pathway (e.g., KRAS, NRAS, and BRAF) were observed in the same patient. In vitro modeling predicts only partial treatment efficacy of targeting subclonal mutations, and even growth promotion of mutated subclones in some cases. Interestingly, analysis of the mutational profile data have also identified a complex subclonal structure at diagnosis which evolves further over time, driven by inherent tumor characteristics and/or under the selection pressure from therapeutic intervention. Further analysis of the exome sequencing data, in serial sampling revealed diverse patterns of clonal evolution: linear evolution, differential clonal response, and branching evolution. Diverse processes contributing to the mutational repertoire including kataegis and somatic hypermutation have been identified, and their relative contribution changed over time. The analysis of the myeloma mutational profile suggest that the disease may be driven by diverse processes which may require different therapeutic intervention, raising the need and possibility of individualized therapy based on the driver mutations. The ability to utilize massively parallel sequencing has allowed interrogation of various other genomic correlates. For example large size RNA-seq data has identified a complex but reproducible spliced isoforms patterns with differential expression between normal plasma cells and myeloma cells as well as between various myeloma subtypes. Evaluation of the expression of mutated genes in MM using RNA-seq has identified a pattern of differential and limited expression of mutant alleles. We observe that only quarter of the mutations are expressed and among mutated genes that are expressed, there are often allele-specific patterns of expression. These results highlight the important contribution of RNA-sequencing to identify clinically significant mutations and for their therapeutic applications. Moreover, sequencing of long noncoding RNA, microRNA, global UTR-sequencing and sequencing of epigenomic markers have now begun to unravel disease process as well as highlight differences in various genomic subtypes. In summary, the early mutational analyses of clinically annotated samples have provided insight into molecular mechanism of disease
Abstracts behavior, and help identify novel therapeutic targets for the development of molecularly-based therapies to improve outcome in myeloma.
PS-004 The Risk Classification based on Gene Expression Profiling: a Tool for Prediction of High- and Low-risk Multiple Myeloma across International Trials P. Sonneveld, R. Kuiper, A. Broijl, M. van Duin Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
Patients with multiple myeloma have variable survival, and require reliable prognostic and predictive scoring systems. Currently, clinical and biological risk markers are used independently. Here, ISS, FISH markers and gene expression (GEP) classifiers were combined to identify novel risk classifications in a discovery/validation setting. We used the datasets of HOVON-65/ GMMG-HD4, UAMS-TT2, UAMS-TT3, MRC-IX, APEX and IFM-G (total number of patients: 4750) to test the relative prognostic impact of individual markers alone and in combination. A total of 20 risk markers were evaluated including t(4;14) and deletion of 17p (FISH), EMC92 and UAMS70 (GEP classifiers) and ISS. It was observed that ISS is a valuable partner to GEP classifiers and FISH. Ranking all novel as well as existing risk markers showed that the EMC92-ISS combination is the strongest predictor for overall survival, resulting in a four group risk classification. The median survival was 24 months for the highest risk group, 47 and 61 months for the intermediate risk groups and median not reached after 98 months for the lowest risk group. The EMC92-ISS classification is a novel prognostic tool, based on biological and clinical parameters, which is superior to current markers and offers a robust clinically relevant 4-group model. The relative value of GEP based risk classification will be discussed in the context of alternative classification models
PS-005 SNP/microRNA C. Croce The Ohio State University, Ohio, USA
Several reports and our data suggest that MDM2 overexpression in MMs, but not its gene amplification could be responsible for p53 inactivation in cells retaining functional p53 pathways. This supports the idea that induction of p53 in this setting might be a suitable treatment for MM. We studied the role of miRNAs in the p53 apoptotic pathway upon nongenotoxic activation of p53 in MM cells, using small molecular inhibitors of MDM2 (Nutlin-3a, MI-219) and identified two related microRNA clusters located in regions considered important for MM (miR-194-2-192 at 11q13.1 and miR-194-1-215 at 1q41.1). Through characterization of the miR-194-2-192 cluster promoter region and definition of a noncanonical p53 consensus site, we have shown that these miRNAs are direct p53 targets. In patient samples, the expression of these
miRNAs changed during transition from normal PC, via MGUS to intramedullary MM and these miRNAs were significantly downregulated in a cohort of newly diagnosed MMs versus MGUS. We also noted, as in the case of KMS28BM cells, that their biological action could be associated with the MDM2 status in MM cells, and Luciferase assays using plasmids harboring the MDM2 30UTR sequence confirmed that MDM2 is the direct target of these miRNAs. In a subset of newly diagnosed MMs, elevated levels of MDM2 mRNA were inversely associated with miR-192 expression. We proved, in vivo and in vitro, that the combination of these miRNAs with p53 pharmacological activator (MI-219), leading to MDM2 downregulation and subsequent p53, p21, and Puma upregulation, could be a successful therapeutic strategy. In fact, it produced anti-tumor results that could not be achieved solely by increasing the drug concentration. We also found that miR-192 and miR-215 expression, by overriding MDM2 ubiquitination of IGF1R, directly targets the IGF-1 axis in MM cells, controlling mobility and invasive properties of MM cells in vitro and in vivo. We proposed a model in which these miRNAs are (1) regulators of the autoregulatory loop, increasing the window of time between p53 apoptotic action and p53 degradation by MDM2; and (2) at the same time targeting the IGF axis, antagonizing the MDM2 ubiquitin ligase function on IGF-1R. In summary, our results have defined a mechanism of p53 regulation through miRNAs acting on MDM2 expression, providing the basis for the development of miRNA-targeted therapies for MM.
PS-006 The Vk*MYC Mouse Model to study Drug and Immunotherapy Response and Resistance M. Chesi, P.L. Bergsagel Mayo Clinic, Arizona, USA
A genetic rearrangement of the MYC locus is among most common mutations in human MM. The genetically engineered Vk*MYC mouse model is based on dysregulation of MYC, and has been extensively validated as a clinically and biologically faithful model of untreated MM. Eleven drugs or classes of drugs e Selinexor, Pim kinase inhibitor (LGH447), DNA alkylators, Glucocorticoids, Proteasome Inhibitors, IMiDs, paclitaxel, HDACi, TACIIg, perifosine and SNS-032- have more than a 20% PR rate in Vk*MYC MM. Among these, eight also have greater than 10% PR rate as single agents, or increased PR rate when used in combinations in patients with MM for a positive predictive value of 73%. In contrast, 11/12 drugs that have less than 20% PR in Vk*MYC MM also have less than 20% PR in patients with MM for a NPV of 92%. Confident that drugs with activity in Vk*MYC mice will likely be effective in the treatment of MM, we have used this model to study novel drugs. We found that bromodomain inhibitors which compete with acetylated histones for the binding to BRD4, inhibiting superenhancer activity and MYC transcription were also active in the Vk*MYC model. The histone methyltransferase EZH2 inhibitor CPI-‘169 is active against Vk*MYC MM, identifying EZH2 as a promising new epigenetic target in MM. EDO-S101 is a molecular
15th International Myeloma Workshop, September 23-26, 2015
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Genomics and Microenvironment
PS-003 Next Generation Sequencing in Multiple Myeloma N.C. Munshi, N. Bolli, S. Minvielle, K.C. Anderson, G. Parmigiani, P. Campbell, H. Avet-loiseau Dana-Farber Cancer Institute and VA Boston Healthcare System, Harvard Medical School, Boston, MA, USA; Cancer Genome Project, Welcome Trust Sanger Instituite Hinxton UK; Centre de Recherche en Cancérologie Nantes-Angers UMR Inserm 892 - CNRS 6299 and Institut de Recherche Thérapeutique de l’Université de Nantes (IRTUN) 44007 Nantes, France; Unité de Génomique du Myélome, CHU Rangueil, Toulouse, France
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Initial oncogenomic studies utilizing a high-resolution analysis of recurrent copy number alterations, coupled with expression analysis in primary Multiple Myeloma (MM) cells has revealed a complex disease process accompanied by numerous genetic and epigenetic alterations. Number of highly recurrent and focal copy number alterations have been identified and these regions of amplification/
15th International Myeloma Workshop, September 23-26, 2015
deletions have been evaluated for involvement in MM pathogenesis and prognosis. With the availability of massively parallel sequencing, these oncogenomic studies are now further expanded to include various genomic changes including evaluation of mutational profile to study changes that may drive the disease as well as clonal content in MM. An earlier publication in 29 patients (22 whole genomes and 17 whole exomes) used deep sequencing and identified unique recurrent mutations that may have biological importance. These genes include histone methyltransferases, transcription factor IRF4, BRAF, genes involved in protein translation, and surprisingly genes involved in blood coagulation. Two subsequent larger studies including one from our group have identified various genomic characteristics. Myeloma cells on an average has between 50-60 mutations; there is no universal mutation that drives the disease in a large majority of patients; in fact frequency of no single mutation is greater than 15-20%, in fact most are less than 10%. Importantly, the 3 most common mutations involve MEK/ERK pathway genes namely N-Ras, K-Ras and BRAF. An important observation from this study has been significant genomic heterogeneity in myeloma. Mutations were often present in subclonal populations, and multiple mutations within the same pathway (e.g., KRAS, NRAS, and BRAF) were observed in the same patient. In vitro modeling predicts only partial treatment efficacy of targeting subclonal mutations, and even growth promotion of mutated subclones in some cases. Interestingly, analysis of the mutational profile data have also identified a complex subclonal structure at diagnosis which evolves further over time, driven by inherent tumor characteristics and/or under the selection pressure from therapeutic intervention. Further analysis of the exome sequencing data, in serial sampling revealed diverse patterns of clonal evolution: linear evolution, differential clonal response, and branching evolution. Diverse processes contributing to the mutational repertoire including kataegis and somatic hypermutation have been identified, and their relative contribution changed over time. The analysis of the myeloma mutational profile suggest that the disease may be driven by diverse processes which may require different therapeutic intervention, raising the need and possibility of individualized therapy based on the driver mutations. The ability to utilize massively parallel sequencing has allowed interrogation of various other genomic correlates. For example large size RNA-seq data has identified a complex but reproducible spliced isoforms patterns with differential expression between normal plasma cells and myeloma cells as well as between various myeloma subtypes. Evaluation of the expression of mutated genes in MM using RNA-seq has identified a pattern of differential and limited expression of mutant alleles. We observe that only quarter of the mutations are expressed and among mutated genes that are expressed, there are often allele-specific patterns of expression. These results highlight the important contribution of RNA-sequencing to identify clinically significant mutations and for their therapeutic applications. Moreover, sequencing of long noncoding RNA, microRNA, global UTR-sequencing and sequencing of epigenomic markers have now begun to unravel disease process as well as highlight differences in various genomic subtypes. In summary, the early mutational analyses of clinically annotated samples have provided insight into molecular mechanism of disease
Abstracts behavior, and help identify novel therapeutic targets for the development of molecularly-based therapies to improve outcome in myeloma.
PS-004 The Risk Classification based on Gene Expression Profiling: a Tool for Prediction of High- and Low-risk Multiple Myeloma across International Trials P. Sonneveld, R. Kuiper, A. Broijl, M. van Duin Department of Hematology, Erasmus MC Cancer Institute, Rotterdam, The Netherlands
Patients with multiple myeloma have variable survival, and require reliable prognostic and predictive scoring systems. Currently, clinical and biological risk markers are used independently. Here, ISS, FISH markers and gene expression (GEP) classifiers were combined to identify novel risk classifications in a discovery/validation setting. We used the datasets of HOVON-65/ GMMG-HD4, UAMS-TT2, UAMS-TT3, MRC-IX, APEX and IFM-G (total number of patients: 4750) to test the relative prognostic impact of individual markers alone and in combination. A total of 20 risk markers were evaluated including t(4;14) and deletion of 17p (FISH), EMC92 and UAMS70 (GEP classifiers) and ISS. It was observed that ISS is a valuable partner to GEP classifiers and FISH. Ranking all novel as well as existing risk markers showed that the EMC92-ISS combination is the strongest predictor for overall survival, resulting in a four group risk classification. The median survival was 24 months for the highest risk group, 47 and 61 months for the intermediate risk groups and median not reached after 98 months for the lowest risk group. The EMC92-ISS classification is a novel prognostic tool, based on biological and clinical parameters, which is superior to current markers and offers a robust clinically relevant 4-group model. The relative value of GEP based risk classification will be discussed in the context of alternative classification models
PS-005 SNP/microRNA C. Croce The Ohio State University, Ohio, USA
Several reports and our data suggest that MDM2 overexpression in MMs, but not its gene amplification could be responsible for p53 inactivation in cells retaining functional p53 pathways. This supports the idea that induction of p53 in this setting might be a suitable treatment for MM. We studied the role of miRNAs in the p53 apoptotic pathway upon nongenotoxic activation of p53 in MM cells, using small molecular inhibitors of MDM2 (Nutlin-3a, MI-219) and identified two related microRNA clusters located in regions considered important for MM (miR-194-2-192 at 11q13.1 and miR-194-1-215 at 1q41.1). Through characterization of the miR-194-2-192 cluster promoter region and definition of a noncanonical p53 consensus site, we have shown that these miRNAs are direct p53 targets. In patient samples, the expression of these
miRNAs changed during transition from normal PC, via MGUS to intramedullary MM and these miRNAs were significantly downregulated in a cohort of newly diagnosed MMs versus MGUS. We also noted, as in the case of KMS28BM cells, that their biological action could be associated with the MDM2 status in MM cells, and Luciferase assays using plasmids harboring the MDM2 30UTR sequence confirmed that MDM2 is the direct target of these miRNAs. In a subset of newly diagnosed MMs, elevated levels of MDM2 mRNA were inversely associated with miR-192 expression. We proved, in vivo and in vitro, that the combination of these miRNAs with p53 pharmacological activator (MI-219), leading to MDM2 downregulation and subsequent p53, p21, and Puma upregulation, could be a successful therapeutic strategy. In fact, it produced anti-tumor results that could not be achieved solely by increasing the drug concentration. We also found that miR-192 and miR-215 expression, by overriding MDM2 ubiquitination of IGF1R, directly targets the IGF-1 axis in MM cells, controlling mobility and invasive properties of MM cells in vitro and in vivo. We proposed a model in which these miRNAs are (1) regulators of the autoregulatory loop, increasing the window of time between p53 apoptotic action and p53 degradation by MDM2; and (2) at the same time targeting the IGF axis, antagonizing the MDM2 ubiquitin ligase function on IGF-1R. In summary, our results have defined a mechanism of p53 regulation through miRNAs acting on MDM2 expression, providing the basis for the development of miRNA-targeted therapies for MM.
PS-006 The Vk*MYC Mouse Model to study Drug and Immunotherapy Response and Resistance M. Chesi, P.L. Bergsagel Mayo Clinic, Arizona, USA
A genetic rearrangement of the MYC locus is among most common mutations in human MM. The genetically engineered Vk*MYC mouse model is based on dysregulation of MYC, and has been extensively validated as a clinically and biologically faithful model of untreated MM. Eleven drugs or classes of drugs e Selinexor, Pim kinase inhibitor (LGH447), DNA alkylators, Glucocorticoids, Proteasome Inhibitors, IMiDs, paclitaxel, HDACi, TACIIg, perifosine and SNS-032- have more than a 20% PR rate in Vk*MYC MM. Among these, eight also have greater than 10% PR rate as single agents, or increased PR rate when used in combinations in patients with MM for a positive predictive value of 73%. In contrast, 11/12 drugs that have less than 20% PR in Vk*MYC MM also have less than 20% PR in patients with MM for a NPV of 92%. Confident that drugs with activity in Vk*MYC mice will likely be effective in the treatment of MM, we have used this model to study novel drugs. We found that bromodomain inhibitors which compete with acetylated histones for the binding to BRD4, inhibiting superenhancer activity and MYC transcription were also active in the Vk*MYC model. The histone methyltransferase EZH2 inhibitor CPI-‘169 is active against Vk*MYC MM, identifying EZH2 as a promising new epigenetic target in MM. EDO-S101 is a molecular
15th International Myeloma Workshop, September 23-26, 2015
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