Citations

Abstract Although multiple myeloma is clinically defined as the accumulation of clonal, malignant plasma cells in the bone marrow, the disease shows significant heterogeneity with regard to progression and therapeutic response. It is likely that germline genetic polymorphisms contribute significantly to an individual’s disease course and response. Bank On A CureTM (BOAC) is a collaborative project initiated with the International Myeloma Foundation (IMF) to develop a DNA bank of myeloma patient samples, through international cooperation. As the bank continues to expand, it provides a resource for the development of cooperative partnerships to assess specific clinical trials as well as conglomerate data. In this study, we have combined data from 3 phase III trials: ECOG trial E9486 (VBMCP + cyclophosphamide or interferon); SWOG trial 9321 (VAD induction followed by randomization to PBSC-supported high dose therapy versus standard dose therapy of VBMCP); and the MRC7 trial (comparing conventional chemotherapy [ABCM] with intravenous chemotherapy and high dose melphalan [CVAMP + HDM +PBSCT]). Five single nucleotide polymorphisms were examined based on associations demonstrated in previous individual trials: GSTP1, IL-6, LT-a, TNF-a, and ERCC2 (DNA repair). Patient samples included 412 from E9486, 569 from S9321, and 232 from MRC7 (total=1213). As a combined data set, genotype associations with overall survival did not reach statistical significance, suggesting SNP associations with survival may be therapy specific. One single association that did reach significance in the conglomerate data was TNF-a genotype association with age of disease onset (the high producer variant AA genotype showing a 5 year later age of onset than the AG/GG genotypes, or the overall mean of the trial, age 61 vs 56; p=.03). This is interesting in light of reports suggesting high production of TNF-a is found in myeloma patients and may actually promote myeloma. Yet, high production may also delay disease onset due to its role in other immunologic processes. Additional parameters including genotype associations with bone disease, CR rates, toxicities, and stage are being evaluated and will be presented. Preliminary results show that when SNPs from S9321 were included in a linear regression model, genotype risk groups could be identified; showing 73% correct association with ISS stage 1, and 75% correct association with ISS stage 3. This model, however, was not validated in the E9486 trial, with less than 50% genotype predictive ISS stage association. A number of highly significant ethnic genotype associations were noted, and are presented in a separate abstract. Given the likely complex interactions of multiple genetic variations, collective genotype comparisons may be required from larger pooled data sets BOAC is assembling to increase significant associations.

Abstract There is a high background risk of venous thrombotic events (VTE) in patients with Multiple Myeloma (MM) and this is significantly increased following treatment with Thalidomide. The risk may be mediated by the production of a prothrombotic state, via an angiopathic mechanism, or alternatively it may arise from the release of prothrombotic factors from dying myeloma cells targeted by the treatment. No unifying evidence of a prothrombotic state has been demonstrated to date and it remains important to understand the mechanism underlying VTEs in order to prevent them effectively. Inherited genetic variants in the form of SNPs can affect the behaviour of clotting factors. These SNPs are functional and well characterised in the coagulation system and we have used them to analyse the mechanism underlying thalidomide induced VTE. As part of the Bank On A Cure TM project we have carried out an analysis of SNPs in 11 genes: GPIIA, ITGA, MTHFR, MTR, PPARG2, TFP1, VCAM, factor V, HABP2, prothrombin and THDB in a case series of 90 patients treated with thalidomide, with and without DVTs. This study showed a significant association with MTHFR and factor V polymorphisms. In order to validate and extend these initial observations we carried out an analysis of a second nested case control study using 131 Myeloma patients from within the MRC Myeloma IX trial, comprising 47 cases with a VTE and 94 age and sex matched controls exposed to the same treatment. We used a SNPlex panel containing 16 functional venous thrombosis associated SNPs, all of these functional polymorphisms have reported mechanisms and biology. We looked at polymorphisms in the genes: fibrinogen A (Ala331Thr), B (-455G>A, Lys478Arg) and G polypeptides (His140Tyr); Coagulation factors V(Arg534Gln), VIII (Glu1260Asp), IX(Ala194Thr), XI (Phe339Cys) and XII(-4G>T); PROCR(Gly219Ser); prothrombin(19911A>G ,20210G>A); MTHFR(Glu429Ala, Ala222Val); Serpine1(-844G>A) and TFPI(Met292Val). We have typed our selected SNPs using the SNPlex™ Genotyping System, which is based on the oligonucleotide ligation/PCR assay with a universal fluorescently labeled ZipChute™ probe detection. The probes are hybridized to complementary ZipCode™ sequences that are part of genotype-specific amplicons. Probes are eluted and detected on a Applied Biosystems 3130x DNA Analyser. This approach is an attractive alternative to existing genotyping methodologies, as it requires only three unlabeled probes per SNP, and consumes very little gDNA. The data analysis on the polymorphisms frequencies is ongoing to examine associations of thalidomide treatment with VTE events and will be presented. These datasets will allow a better definition of the pathogenesis of thalidomide related VTE, so that we can intervene therapeutically in a rational fashion.

Abstract While there are certain common clinical features in myeloma, the disease shows significant heterogeneity with regard to disease progression, and responses to therapy, affecting both survival and toxicities. Heritable variations in a wide variety of genes and pathways affecting cellular functions and drug responses likely impact patient outcomes. In the Bank On A Cure (BOAC) program we have developed a custom chip that assesses 3,404 SNPs representing variations in cellular functions and pathways that may be involved in myeloma progression and response. The chip has gone through rigorous quality controls checks for high call rates, accuracy, and reproducibility that will be presented. Using the BOAC chip, we have conducted studies to look for SNPs that may identify biologic variations that are associated with good or poor response across a variety of treatments. In this study we looked for SNPs that may distinguish short term and long term survivors in two phase III clinical trials: ECOG E9486 and intergroup trial S9321. E9487 patients were treated with VBMCP followed by randomization to no further treatment, IFN-alpha, or cylcophosphamide; and, although there was variation in survival, no significant differences in survival were noted among the 3 arms of the trial. Patients included in this SNP study from S9321 received VAD induction followed by randomization to VBMCP or high dose melphalan + TBI. SNP profiles were obtained for patients with less than 1 year EFS (n=20 in E9487; n=50 in S9321) and patients showing greater than 3 years EFS (n=32 in E9486; n=41 in S9321). Statistical approaches were performed to identify single and groups of SNPs that best discriminated the survival groups. Previous studies have suggested genetic variations in drug metabolism genes, p-glycoprotein transport, and DNA repair genes may influence survival outcomes. Our results show significant survival associations of genetic variations in genes within these functional categories (eg. GST, XRCC, ABCB, and CYP genes). Although genetic variations were found that were uniquely associated with each clinical trial, several of these genetic variations show survival associations that increase in significance when the two trials were examined as a conglomerate data set. Grouping genetic variations through common pathway approaches using gene set enrichment analysis, as well as clustering or partitioning algorithms, further improve the value of the SNPs as potential prognostic markers of survival outcomes. These results and statistical approaches will be presented, and represent steps toward identifying patient variations in biologic mechanisms important in predicting therapeutic outcomes.

Abstract Bank On A CureTM is a collaborative project initiated with the International Myeloma Foundation to develop a DNA bank through international cooperation. The Bank provides a resource for the development of cooperative partnerships to assess genetic associations with disease etiology and outcomes. It is well established that genetic variation can have a significant ethnic association, and such variations may account for differences in disease incidence and outcomes. Indeed, African Americans have historically shown a 2.5–3 fold increase population incidence of myeloma compared to the Caucasian population. We have identified a number of potentially biologically relevant genetic variants that show significant differences in ethnic distribution. Using both clinical trials as well as the Coriel [normal] cell line data base, we find in all three cases the same highly significant differences (Fishers Exact Test) between African Americans and Caucasians in functionally relevant genetic polymorphisms, as represented by E9486 univariate analysis of IL-6 (p<.00001), LT-a (p<.0001), ERCC312 (p<.0001), XRCC399 (p=.006), IL-1RA (p<.00001), GST-M (p=.0008), and ERCC751 (p<.02). Subsequently, from trial S9321 we have found differences in a number of clinical outcomes associated with ethnicity. When toxicities between Caucasians and African Americans were examined, similar severe toxicity rates were noted after VAD induction related to neuropathies, nausea, and bone pain; whereas statistically significant differences were noted for infection rates, hyperglycemia, fatigue, dyspnea, and thrombosis (p<.04). During high dose melphalan treatment toxicities were not statistically different. Because significant association between IL-6 genotype and ethnicity was noted, we also examined serum levels of sIL-6R and CRP, available from trial E9486. African Americans patients show significantly lower sIL-6R levels compared to Caucasian patients (mean 149 vs 213 ng/ml; p<.0001). Interestingly, there is a significant association between IL-6 SNP genotype and sIL-6R distribution, with the high IL-6 producer GG genotype (in 90% African Americans) having the lowest sIL-6R compared to the CC or CG genotypes (p=.02). Regression analysis of IL-6 SNP and ethnicity on sIL-6R reveals that ethnicity is significantly associated with sIL-6R distribution after adjustment for IL-6 SNP genotype (p=.001) but not vice versa (p=.91), indicating the association of IL-6 SNP genotype with sIL-6R is due to its association with ethnicity. Together the data demonstrate that while associations may result from co-segregation of ethnic genotypes, they may influence disease risk and outcomes related to important genetic factors distributed unequally in different ethnic populations. Such differences may, for example, alter IL-6 responses. Further, multivariate analysis will be developed. Validation of genotype associations found in different ethnic populations will be an important consideration in evaluating myeloma etiology and outcomes.

17516 Background: The p53 tumor suppressor is commonly inactivated by mutations. Even in tumors without mutations, there are defects in the response to p53 activation. In MM, the prognostic significance of p53 mutation is unknown, while there has been no systematic study of p53 function. We seek to address these issues in this study. Methods: p53 mutation was studied by conformation sensitive gel electrophoresis with primers encompassing exons 1 to 10 followed by sequencing of DNA fragments with altered electrophoretic pattern in newly diagnosed MM patients entered into ECOG E9486 trial where patients were randomized to receive variations of melphalan-based conventional chemotherapy (VBMCP). Fisher’s exact tests were used to compare variables between patients. Kaplan-Meier survival curves were compared using the log-rank test. To investigate p53 function, we analyzed the expression of p53, and 3 of its transcriptional targets, APAF1, p21 and MDM2, in a separate cohort of 15 normal plasma cells (PC), 14 MGUS, 13 smoldering myeloma (SMM) and 101 MM (73 new and 28 relapsed) from the Mayo Clinic who had gene expression profiling performed on the Affymetrix U133A chip (Santa Clara, Ca). Results: Two hundred and sixty-eight patients had enough materials for study and were included in the analysis. The prevalence of p53 mutation was 3% (n = 9). Five of the 9 patients (56%, p = 0.001) with mutations also had p53 deletion (studied by fluorescent in-situ hybridization) resulting in bi-allelic loss of p53. Soft tissue plasmacytomas (37% v 7%, p = 0.018), and among the common translocations, t(4;14) and t(14;16) (50% v 18%) were more common in patients with p53 mutations. Despite similar response to treatment, those with p53 mutation had very short OS (16.7 v 41.4 months, p < 0.001). There was induction of p53 expression in MGUS and SMM with concurrent induction of APAF1, p21 and MDM2 whereas loss of this pattern was frequent in MM (45% in new MM and 60% in relapse MM compared to 15% in MGUS/SMM (p = 0.03)). Conclusions: p53 mutations are relatively rare in newly diagnosed MM patients but portend a short survival. However, functional abnormalities of p53 are prevalent and may be important in progression from MGUS/SMM to MM. [Table: see text]

Abstract We studied the prognostic significance of plasmablastic (PB) multiple myeloma (MM) in Eastern Cooperative Oncology Group Phase III trial E9486. Two reviewers independently reviewed 453 cases. They agreed on 37 PB (8.2%) cases and 416 non-PB cases, achieving an 85% concordance (P < .0001). These PB cases had significantly lower hemoglobin and serum albumin levels, higher calcium and β 2-microglobuin levels, and higher percentage BM plasma cells (PC) by immunofluorescence. They had higher bone marrow PC labeling indices, higher serum soluble interleukin-6 receptor (sIL-6R) levels, and a higher probability of ras mutations. Three treatment regimens were used: vincristine, bis-chloro-ethyl nitrosourea (BCNU) melphalan, cyclophosphamide, and prednisone (VBMCP) alone; VBMCP with added cyclophosphamide (HiCy); or recombinant interferon α 2 (rIFNα2). Although the numbers are low, patients with PB had a significantly lower response rate versus non-PB MM when treated with VBMCP (treated, 47.1% v nontreated, 66.5% [P = .015]). Patients with nonresponding PB had a significantly higher progression rate than non-PB cases (30.6%v 11.8% [P < .0001]), especially with VBMCP alone (35.3% v 15.8% [P = .002]), and with added HiCy (37.5% v 9.8% [P < .0001]), but not with added rIFNα2. Event-free and overall survival of PB MM was shorter (median years, 1.1 v 2.7 and 1.9 v 3.7, respectively [P < .0001 for both]). In multivariate analysis, PB classification was also highly prognostic. There is no survival difference between the patients who were classified as PB by both reviewers versus patients classified as PB by only one reviewer. We conclude that PB MM is a discrete entity associated with more aggressive disease and shortened survival. Tumor cell rasmutations and increased sIL-6R may contribute to a higher proliferation rate and reduced survival. There were significant improvements in response and progression with the addition of HiCy and rIFNα2 to VBMCP, but the numbers were small and improved survival could not be shown.

Recent analyses of circulating blood B cells in myeloma have generated controversy concerning the exact levels of these cells and whether they may represent circulating clonal tumor B cells. Previous reports suggested that CD19+ B cells are markedly increased in myeloma patients and that this population shares clonotypic rearrangements with the malignant plasma cell. We studied the numbers of CD19+ B cells by flow cytometry in previously untreated newly diagnosed myeloma patients in Eastern Cooperative Oncology Group (ECOG) phase III trial E9486. There were 628 patients who were eligible for the clinical protocol E9486, but of these 521 were also entered on the companion laboratory study (E9487) and had CD19 data. In comparison with normal controls, the myeloma patients exhibited a marked heterogeneity in the number of circulating CD19+ B cells as detected by flow cytometry. Approximately 20% of patients had significantly increased levels of circulating CD19+ B cells. However, the total CD19+ blood population from myeloma was not significantly different from the median of age-matched, normal controls. Analysis of CD19+ blood cells in relationship to circulating clonal cells was done in 13 myeloma patients using a clonotypic, quantitative allele-specific oligonucleotide-polymerase chain reaction (PCR) assay. No correlation was found between the numbers of CD19+ B cells (range, 5% to 51%) and PCR estimates of the number of clonal cells in the peripheral blood (range, .009% to 3.6%). Low CD19+ B-cell level (<125 μL) was associated with clinical stage III (P = .033). A significant relationship exists between higher levels (≥125/μL) of CD19 cells and longer overall survival (P < .0001). In addition, high CD19 levels also predicted a clinical response and longer event-free survival. There was a strong inverse association between the level of CD19 values at diagnosis and infections within the first 2 months of diagnosis. Importantly, the number of deaths related to infections was significantly greater in the low versus high CD19 group (P < .0202). Also, CD19 is an independent prognostic factor in addition to plasma cell labeling indices, β2 -microglobulin, hemoglobin, and plasmablastic morphology. Patients with infections were more likely to have low levels of CD19+ cells. In summary, higher CD19+ cell levels are a favorable prognostic sign with no apparent relationship to circulating tumor cells. In addition, this analysis strongly suggests that low peripheral blood levels of CD19+ cells are an adverse prognostic sign in myeloma. The CD19+ cell levels in myeloma patients is an important parameter in the overall assessment of these patients.

We studied the prognostic significance of plasmablastic (PB) multiple myeloma (MM) in Eastern Cooperative Oncology Group Phase III trial E9486. Two reviewers independently reviewed 453 cases. They agreed on 37 PB (8.2%) cases and 416 non-PB cases, achieving an 85% concordance (P < .0001). These PB cases had significantly lower hemoglobin and serum albumin levels, higher calcium and β 2-microglobuin levels, and higher percentage BM plasma cells (PC) by immunofluorescence. They had higher bone marrow PC labeling indices, higher serum soluble interleukin-6 receptor (sIL-6R) levels, and a higher probability of ras mutations. Three treatment regimens were used: vincristine, bis-chloro-ethyl nitrosourea (BCNU) melphalan, cyclophosphamide, and prednisone (VBMCP) alone; VBMCP with added cyclophosphamide (HiCy); or recombinant interferon α 2 (rIFNα2). Although the numbers are low, patients with PB had a significantly lower response rate versus non-PB MM when treated with VBMCP (treated, 47.1% v nontreated, 66.5% [P = .015]). Patients with nonresponding PB had a significantly higher progression rate than non-PB cases (30.6%v 11.8% [P < .0001]), especially with VBMCP alone (35.3% v 15.8% [P = .002]), and with added HiCy (37.5% v 9.8% [P < .0001]), but not with added rIFNα2. Event-free and overall survival of PB MM was shorter (median years, 1.1 v 2.7 and 1.9 v 3.7, respectively [P < .0001 for both]). In multivariate analysis, PB classification was also highly prognostic. There is no survival difference between the patients who were classified as PB by both reviewers versus patients classified as PB by only one reviewer. We conclude that PB MM is a discrete entity associated with more aggressive disease and shortened survival. Tumor cell rasmutations and increased sIL-6R may contribute to a higher proliferation rate and reduced survival. There were significant improvements in response and progression with the addition of HiCy and rIFNα2 to VBMCP, but the numbers were small and improved survival could not be shown.

Abstract Multiple myeloma (MM) is characterized by significant genetic diversity at subclonal levels that likely plays a defining role in the heterogeneity of tumor progression, clinical aggressiveness and drug sensitivity. Such heterogeneity is a driving factor in the evolution of MM, from founder clones through outgrowth of subclonal fractions. DNA Sequencing studies on MM samples have indeed demonstrated such heterogeneity in subclonal architecture at diagnosis based on recurrent mutations in pathologically relevant genes that may ultimately to lead to relapse. However, no study so far has reported a predictive gene expression signature that can identify, distinguish and quantify drug sensitive and drug-resistant subpopulations within a bulk population of myeloma cells. In recent years, our laboratory has successfully developed a gene expression profile (GEP)-based signature that could not only distinguish drug response of MM cell lines, but also was effective in stratifying patient outcomes when applied to GEP profiles from MM clinical trials using proteasome inhibitors (PI) as chemotherapeutic agents. Further, we noted myeloma cell lines that responded to the drug often contained residual sub-population of cells that did not respond, and likely were selectively propagated during drug treatment in vitro, and in patients. In this study, we performed targeted qRT-PCR analysis of single cells using a gene panel that included PI sensitivity genes and gene signatures that could discriminate between low and high-risk myeloma followed by intensive bioinformatics and statistical analysis for the classification and prediction of PI response in individual cells within bulk multiple myeloma tumors. Fluidigm's C1 Single-Cell Auto Prep System was used to perform automated single-cell capture, processing and cDNA synthesis on 576 pre-treatment cells from 12 cell lines representing a wide range of PI-sensitivity and 370 cells from 7 patient samples undergoing PI treatment followed by targeted gene expression profiling of single cells using automated, high-throughput on-chip qRT-PCR analysis using 96.96 Dynamic Array IFCs on the BioMark HD System. Probability of resistance for each individual cell was predicted using a pipeline that employed the machine learning methods Random Forest, Support Vector Machine (radial and sigmoidal), LASSO and kNN (k Nearest Neighbor) for making single-cell GEP data-driven predictions/ decisions. The weighted probabilities from each of the algorithms were used to quantify resistance of each individual cell and plotted using Ensemble forecasting algorithm. Using our drug response GEP signature at the single cell level, we could successfully identify distinct subpopulations of tumor cells that were predicted to be sensitive or resistant to PIs. Subsequently, we developed a R Statistical analysis package (http://cran.r-project.org), SCATTome (Single Cell Analysis of Targeted Transcriptome), that can restructure data obtained from Fluidigm qPCR analysis run, filter missing data, perform scaling of filtered data, build classification models and successfully predict drug response of individual cells and classify each cell's probability of response based on the targeted transcriptome. We will present the program output as graphical displays of single cell response probabilities. This package provides a novel classification method that has the potential to predict subclonal response to a variety of therapeutic agents. Disclosures Kumar: Skyline: Consultancy, Honoraria; BMS: Consultancy; Onyx: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Novartis: Research Funding; Takeda: Consultancy, Research Funding; Celgene: Consultancy, Research Funding.

Abstract We have taken a genetic strategy to define the mechanisms underlying the increased risk of VTE in myeloma patient treated with thalidomide using clinical trial data derived from the MRC, ECOG, Little Rock and HOVON trial groups. Baseline VTE rates in the MRC IX study, (CTD vs CVAD; n=748 no prophylactic anticoagulation), were 14%. Rates in both arms were equal but in the thalidomide arm, thrombotic events were all DVT’s or PE’s, whereas in the CVAD arm they split equally between line related and VTE’s. In the other comparison (CTD vs MP; n=542), the VTE rate was 17%, all in the thalidomide arm. Rates were similar or higher (30%) in the other trials depending on the intensity of treatment used. We carried out a nested case control on DNA from MRC IX on 90 VTE (45 thalidomide, 45 non-thalidomide related), matched to 180 controls. SNPlex analysis for 60 SNPs in the coagulation cascade, DNA repair, thalidomide, metabolism and myeloma specific pathways, identified 7 genes which affected risk (NBS1, MTHFR, Ku80, Cyp3A5, LGAL52 and IL12B). This suggests three major pathways contribute to the risk of thalidomide related VTE, metabolism of thalidomide, tumour responsiveness and some pro-thrombotic factors. These factors differ from non-thalidomide related risk where a strong pro-inflammatory response is most relevant. We tested this hypothesis further using an expanded panel of 3,404 SNPs (BOAC panel), using the Megalle system. Statistical analysis of this data defined the top 20 thalidomide and non-thalidomide associated SNPs, which were consistent with the initial hypothesis, the results of which exclude variation in the coagulation cascade as being a significant risk factor. We explored this hypothesis further using pathway-based analysis focussing on the MTHFR, DNA repair and WNT pathways on data from the ECOG, HOVON and Little Rock data sets. The biological relevance of the SNPs and genes identified was validated by correlating the level of expression using the Affymetrix U133 CHIP with genetic variation at the DNA level. To verify the relevance of DNA repair variability to tumour response further, we correlated gene expression profiling with response and again Ku80 was identified as one of a cluster of genes defining increased risk. The data suggests that the risk of thalidomide related VTE relates to rapid tumour lysis combined with a prothrombotic tendency, whereas in line related thrombosis, risk is dependent upon a strong proinflammatory response. We are building this genetic data into a clinical risk model in order to allow us to develop a rationale for intervention strategies.