Multiple Myeloma (MM) is considered a heterogeneous disease with substantial variation in response to therapy and survival among different patients. A variety of biomarkers exist that can help predict MM prognosis including cytogenetic markers and gene expression signatures. MM is known to be a partially heritable trait and recent genome wide association studies (GWAS) have identified eight SNPs that are associated with MM susceptibility. However, it is unknown whether germ line variants may also affect MM survival. We used a genome wide association (GWAS) approach to determine whether there are any germ line genetic variants that may affect survival among 592 MM patients. We identified a genome-wide significant association with a locus on 16p13 (p=2.8x10-10). The finding was replicated in a separate cohort of 772 patients. This proposal will seek to expand on these findings. We have formed a consortium of investigators with studies of multiple myeloma including over 3000 patients with data on survival. First, we will investigate the effect of the genotypes discovered by GWAS in the context of other clinical predictors of survival and different therapies. We will adjust for known predictors of survival such as stage, cytogenetic abnormalities. We will also assess the effects in the context of the latest treatments. These analyses will help us the genetic association result in the context of the changing landscape of myeloma prognostic factors and evolving treatment, Second, we will experimentally investigate the gene at the locus identified. The SNPs at the top locus are associated with expression of the nearest gene. In addition, a coding non-synonymous variant is part of the high risk haplotype. Therefore, we will experimentally manipulate in cell line models both the gene expression and the coding sequence and investigate the effect on the pathways that this gene is part of as well as overall cell proliferation rate.
Our proposal investigates a novel inherited genetic variant that is associated with survival among multiple myeloma patients. We will determine how this genetic variant affects survival after accounting for other known predictors of survival among myeloma patients. We will also evaluate the gene experimentally in myeloma cell lines. The studies and experiments we propose should help us understand why some patients myeloma may have poorer prognosis.
| Rand, Kristin A; Song, Chi; Dean, Eric et al. (2016) A Meta-analysis of Multiple Myeloma Risk Regions in African and European Ancestry Populations Identifies Putatively Functional Loci. Cancer Epidemiol Biomarkers Prev 25:1609-1618 |
| Ziv, Elad; Dean, Eric; Hu, Donglei et al. (2015) Corrigendum: Genome-wide association study identifies variants at 16p13 associated with survival in multiple myeloma patients. Nat Commun 6:10203 |
| Ziv, Elad; Dean, Eric; Hu, Donglei et al. (2015) Genome-wide association study identifies variants at 16p13 associated with survival in multiple myeloma patients. Nat Commun 6:7539 |
