Grindle, Suzanne

Abstract Patients with multiple myeloma show significant heterogeneity with respect to progression, therapeutic response and toxicities. Part of the Bank On A Cure project is to examine potential genetic polymorphisms that may be associated with common toxicities monitored in clinical trials. The SWOG/ECOG intergroup trial S9321 therapy includes VAD induction followed by randomization to high dose melphalan with autologous transplant support. Paticularly important toxicities with VAD include infection, thrombosis and hyperglycemia; and with melphalan toxicities in GI function are noted. Toxicities and genotypes were assessable during VAD induction on 569 patients; and during high dose melphalan on 161 patients. Toxicities examined included an array of symptoms: cardiovascular, flu-like, GI, neurologic, infection, lung, metabolic, and pain. Grade 3 toxicities found in at least 20 patients were compared to SNP genotypes. For VAD induced toxicities,TNF-alpha SNP genotypes showed association with fatigue, dyspnea and thrombosis; CYP3A4 SNP genotypes showed association with fatigue; DNA repair SNP genotypes in XRCC1 showed associations with infection, hyperglycemia and dyspnea; LT-alpha SNP genotypes showed association with dyspnea; and IL-6 and IL-10 SNP genotypes were marginally associated with neuropathy. After high dose melphalan, diarrhea was associated with SNP genotypes in TGF-beta, CYP3A4 and ERCC2. Interestingly, IL-6 polymorphisms were significantly associated with infection. The p values on the above associations ranged from .05 to .004. In addition, we noted ethnic distributions of some SNP genotypes were significantly different; and significant ethnic disparities in therapy induced hyperglycemia, fatigue, dyspnea and thrombosis were noted (p values range from .04 to .009). Of particular note is that the high producer IL-6 genotype is present in over 90% African Americans, compared to 35% Caucasians. Details of each association will be presented. Not all associations can easily be explained by known biologic function of the genotype, and it is important to qualify these results, as the likelihood of seeing some genotype associations by chance is quite high given the number of comparisons made. Further, we are continuing to examine additional prognostic factors that may, together with genotypes, provide collective predictors of toxicities. We consider these associations as targets for further study through the increasing sample acquisition in the Bank On A Cure project.

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.

Mechanical unloading of the heart with a left ventricular assist device (LVAD) significantly decreases mortality in patients with heart failure. Moreover, it provides a human model to define the critical regulatory genes governing myocardial remodeling in response to significant reductions in wall stress. Statistical analysis of a gene expression library of 19 paired human heart samples harvested at the time of LVAD implant and again at explant revealed a set of 22 genes that were downregulated and 85 genes that were upregulated in response to mechanical unloading with a false discovery rate of less than 1%. The analysis revealed a high percentage of genes involved in the regulation of vascular networks including neuropilin-1 (a VEGF receptor), FGF9, Sprouty1, stromal-derived factor 1, and endomucin. Taken together these findings suggest that mechanical unloading alters the regulation of vascular organization and migration in the heart. In addition to vascular signaling networks, GATA-4 binding protein, a critical mediator of myocyte hypertrophy, was significantly downregulated following mechanical unloading. In summary, these findings may have important implications for defining the role of mechanical stretch and load on autocrine/paracrine signals directing vascular organization in the failing human heart and the role of GATA-4 in orchestrating reverse myocardial remodeling. This unbiased gene discovery approach in paired human heart samples has the potential to provide critical clues to the next generation of therapeutic treatments aimed at heart failure.