Background: We have engaged in an international program designated the Bank On A Cure, which has established DNA banks from multiple cooperative and institutional clinical trials, and a platform for examining the association of genetic variations with disease risk and outcomes in multiple myeloma.

A venous thromboembolism (VTE) with the subsequent risk of pulmonary embolism is a major concern in the treatment of patients with multiple myeloma with thalidomide. The susceptibility to developing a VTE in response to thalidomide therapy is likely to be influenced by both genetic and environmental factors. To test genetic variation associated with treatment related VTE in patient peripheral blood DNA, we used a custom-built molecular inversion probe (

We sampled 384 sequences related to the Solanum pimpinellifolium (=Lycopersicon pimpinellifolium) disease resistance (R) gene 12 from six species, potato, S. demissum, tomato, eggplant, pepper, and tobacco. These species represent increasing phylogenetic distance from potato to tobacco, within the family Solanaceae. Using sequence data from the nucleotide binding site (NBS) region of this gene, we tested models of gene family evolution and inferred patterns of selection acting on the NBS gene region and I2 gene family. We find that the I2 family has diversified within the family Solanaceae for at least 14 million years and evolves through a slow birth-and-death process requiring approximately 12 million years to homogenize gene copies within a species. Analyses of selection resolved a general pattern of strong purifying selection acting on individual codon positions within the NBS and on NBS lineages through time. Surprisingly, we find nine codon positions strongly affected by positive selection and six pairs of codon positions demonstrating correlated amino acid substitutions. Evolutionary analyses serve as bioinformatic tools with which to sort through the vast R gene diversity in plants and find candidates for new resistance specificities or to identify specific amino acid positions important for biochemical function. The slow birth-and-death evolution of I2 genes suggests that some NBS-leucine rich repeat-mediated resistances may not be overcome rapidly by virulence evolution and that the natural diversity of R genes is a potentially valuable source for durable resistance.

This case report details how melphalan and prednisone can be administered in the successful treatment of necrobiotic xanthogranuloma with lambda paraproteinemia.

Bone disease in myeloma occurs as a result of complex interactions between myeloma cells and the bone marrow microenvironment. A custom-built DNA single nucleotide polymorphism (SNP) chip containing 3404 SNPs was used to test genomic DNA from myeloma patients classified by the extent of bone disease. Correlations identified with a Total Therapy 2 (TT2) (Arkansas) data set were validated with Eastern Cooperative Oncology Group (ECOG) and Southwest Oncology Group (SWOG) data sets. Univariate correlates with bone disease included: EPHX1, IGF1R, IL-4 and Gsk3β SNP signatures were linked to the number of bone lesions, log2 DKK-1 myeloma cell expression levels and patient survival. Using stepwise multivariate regression analysis, the following SNPs: EPHX1 (P = 0.0026); log2 DKK-1 expression (P = 0.0046); serum lactic dehydrogenase (LDH) (P = 0.0074); Gsk3β (P = 0.02) and TNFSF8 (P = 0.04) were linked to bone disease. This assessment of genetic polymorphisms identifies SNPs with both potential biological relevance and utility in prognostic models of myeloma bone disease.

Background: Bone disease in myeloma occurs as a result of complex interactions between myeloma cells and the bone marrow microenvironment. To date, no studies have evaluated the potential impact of genetic polymorphisms upon and/or within this microenvironment. Patients and Methods: Peripheral blood DNA from 282 patients enrolled in the Total Therapy 2 (TT2) protocol was studied using the previously reported Affymetrix 3k BOAC custom chip to evaluate relevant genetic polymorphisms. DKK1 gene expression and high risk GEP gene signatures were assessed as previously reported (Blood109:4470–4477 and 109:2276–2284 2007). Patients were classified using both full skeletal x-rays and MRI findings. The lower cut-off used was absence of focal abnormalities on x-ray and/or <7 focal lesions on MRI (see JCO25:1121–1128 2007). Results: The top 200 SNPs were first evaluated based upon univariate P values linked to limited or extensive bone disease. The top 50 SNPs with the smallest P values were then selected (eliminating closely linked genes) for recursive partitioning analysis. The recursive partitioning was conducted both with and without the insertion of known biologically relevant SNPs. The pruned tree developed with recursive partitioning proved to be quite stable and incorporated 4 dominant SNPs: rs 3766934 Epoxide hydrolase (EPHX1); sr3783408 MAP kinase; sr 1062637 RNA helicase DDX18; and sr3181366 TNFSF8-TNF-α. No alternate SNP substituted for EPHX1 in the recursive model. The 4 SNP signature of EPHX1 GG, MAP4K5 AG/AA, DDX18 GG/CC plus TNFSF8 CT/TT was highly correlated with the number of MRI lesions: mean 8.66 lesions versus 3.33 for alternate SNPs (P<.001). In the univariate association of standard prognostic factors, 4 SNP signature and 70 and 17 gene models for high risk, the best correlation with bone disease was with the 4 SNPs (P<.0001) followed by the 17 gene GEP model (P=0.05). Using stepwise multivariate regression analysis the best correlation with bone disease was Log2DKK-1 expression (P=.0001) but closely followed by SNPs EPHX1 (P=.0009); MAP4K5 (P=.0071) plus TNFSF8 and serum LDH (P=.02). The various analyses training (2/3) and validation sets were used with assessment of sensitivity and specificity. The microenvironmental 4 SNP signature combined with GEP DKK1 provided the best prediction of myeloma bone disease and overall outcome. Conclusions: This first assessment of genetic polymorphisms linked to myeloma bone disease in myeloma has led to the identification of polymorphisms with both potential biologic relevance and utility in prognostic models of myeloma bone disease including risk stratification for bisphosphonate use. Validation of these findings may allow a search for potential therapeutic targets.

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.

Peripheral neuropathy is a major adverse effect seen in multiple myeloma (MM) patients treated with thalidomide, with rates varying between trials from 15% to 70%. Peripheral neuropathy can often lead to ongoing impairment of quality of life and can lead to discontinuation of treatment. Identifying patients at risk of neuropathy and understanding its pathogenesis would be a significant step forward in the management of thalidomide based therapy. Proposed mechanisms have included: Anti-angiogeneic properties of thalidomide leading to a reduction in nerve blood supply; direct toxic effects of thalidomide on neurons of the posterior root ganglia and dysregulation of neurotrophin activity through effects of thalidomide on NFkB. Genetic variation in genes important in the mechanism of thalidomide neurotoxicity are likely to impact on whether an individual patient develops this adverse effect. Taking a nested case control approach we used peripheral blood DNA from 388 Caucasian MM patients all who had received induction thalidomide (200mg) as part of the Myeloma IX trial. Samples from 80 patients that developed sensory-motor peripheral neuropathy in response to thalidomide therapy were available for this analysis, these were age and sex matched with a ratio of one case to 4 controls. We assayed 3403 SNPs in coding and predicted regulatory regions selected in 1266 genes previously shown to be involved in the pathogenesis, treatment response and side effects associated with myeloma and its therapy. SNPs were present on a custom-built Affymetrix® targeted genotyping chip (designed by “Bank on a Cure” (BOAC)), which utilizes molecular inversion probe technologies. We carried out a univariate analysis by Fischer exact tests. Due to the large number of SNPs and relatively small number of samples, we chose to correct for multiple testing using label swapping permutation using the program PLINK. The most significant SNPs associated with thalidomide related peripheral neuropathy are listed with p=permutated empirical p-value and OR=Odds Ratio: ABCC2-Ile1324Ile (p&lt;9.71×10−5;OR=1.972,1.39−2.8); DGKH-Ala1201Val (p&lt;1.05×10−3;OR =4.267,1.85−9.87); EXO1-Arg354His (p&lt;1.4×10−3;OR=1.79,1.25−2.55) and NPC2-3′UTR (p&lt;1.6×10−3, OR=0.42,0.24−0.75). DGKH, EXO and NPC2 are genes previously reported to play a role in peripheral neurotoxicity. The ABCC2-Ile1324Ile SNP forms part of previously reported functional haplotype. Significant associations were also seen in a number of other ADME genes (drug absorption, distribution, metabolism, and excretion): ABCB1, ABCB11, ABCC1, CYP1A1, CYP20A1, CYP20A1, CYP2C9, CYP3A7, CYP4F2, FMO2, FMO3, FMO6, SLC12A6, SLC22A3 and SLC7A7. Significant associations were also seen in genes important in neurological system processes and central nervous system development: ERBB2, NQO1, MY03A, PPARD, DBH, NGFR, GSTP1, TCF8 and ICF1R. Our results indicate the importance of thalidomide dose and cumulative exposure, and highlight the metabolism of thalidomide as playing a pivotal role in dictating neuropathy events and open the way for predictive testing and dose adjustment. The results also implicate a direct toxicity mechanism for thalidomide related peripheral neuropathy, as we see a number of associations with SNPs in genes with known importance in peripheral neuron function.