Genetic polymorphisms of EPHX1, Gsk3beta, TNFSF8 and myeloma cell DKK-1 expression linked to bone disease in myeloma

Abstract

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 Gsk3beta. SNP signatures were linked to the number of bone lesions, log(2) DKK-1 myeloma cell expression levels and patient survival. Using stepwise multivariate regression analysis, the following SNPs: EPHX1 (P=0.0026); log(2) DKK-1 expression (P=0.0046); serum lactic dehydrogenase (LDH) (P=0.0074); Gsk3beta (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.

Figure 1

Recursive partitioning using ‘Top SNPs’ with Total Therapy 2 (TT2) model. Recursive partitioning branching tree displaying the four single nucleotide polymorphisms (SNPs) used in the model: rs3766934 (EPHX1); rs3783408 (Gsk3β); rs1052637 (DDX18); and rs3181366 (TNSF8). The SNP genotypes are identified: EPHX1(GT/TT versus GG); Gsk3 β (GG versus AG/AA); DDX18 (CC versus CG/CC); and TNFSF8 (CC versus CT/TT). The appended table shows the univariate P-values for each SNP and SNP function.

Figure 2

Baseline focal bone lesions and baseline log₂ DKK-1 by predicted disease using the recursive-partitioning model. (a) The number of focal bone lesions (per patient) is plotted for patients with limited bone disease and extensive bone disease predicted by the four single nucleotide polymorphism (SNP) model illustrated in Figure 1. The mean values are identified. The P-value for the difference is P = 0.001. (b) The directly measured log₂ DKK-1 expression values are plotted for patients with limited bone disease and extensive bone disease predicted by the four SNP model illustrated in Figure 1. The P-value for the difference is P = 0.05.

Figure 3

Overall survival (OS) and Event-free survival (EFS) for both actual and predicted bone disease (Total Therapy 2 (TT2) model). (a) OS is shown for patients with known limited and extensive bone disease and compared with the survival for patients predicted by the four single nucleotide polymorphism (SNP) model to have limited and extensive disease. The listed P-values indicate that OS is statistically inferior for patients with both actual and predicted extensive versus limited bone disease (P = 0.0183). The actual versus predicted outcomes are not different (P-values 0.693 and 0.881, respectively). (b) EFS is shown for patients with known limited and extensive bone disease and compared with EFS for patients predicted to have limited and extensive bone disease based on the four SNP model (Figure 1). The P-values indicate that EFS is not different for limited versus extensive disease, but this is true for both the actual and predicted patient populations (P-values: overall 0.185; and 0.327 and 0.924 for comparisons).