Identification of Prognostic Markers by Gene Expression Profiling In Myelodysplastic Syndrome Hematopoietic Stem Cells

Abstract

298 The myelodysplastic syndromes (MDS) are a heterogeneous group of clonal hematopoietic stem cell malignancies that are characterized by ineffective hematopoiesis resulting in peripheral cytopenias and a hypercellular bone marrow. Approximately 40% of patients with MDS will develop an acute myeloid leukemia. It is important to establish prognosis of MDS patients since the treatment options vary from supportive care to bone marrow transplantation. In order to determine the relationship of gene expression levels to prognosis and so identify new molecular markers, we have used gene expression profiling to study the transcriptome of the hematopoietic stem cells of 125 MDS patients with a minimum 12 month follow up. The CD34+ cells obtained from MDS patients and healthy individuals were analyzed using Affymetrix U133 Plus2.0 arrays. The patients were split randomly in a training set (n=84) and a test set (n=41). Supervised principal components analysis was used to identify genes correlated with survival. Using the 84 patients in the training set, the Cox scores were computed for each gene, and the principal components calculated on the genes with the highest Cox scores. The first of the principal components was then used to generate a regression model to predict the survival in the test set. Finally, for each probe set an importance score was calculated equal to its correlation with the supervised principal component predictor. This approach returned a list of 150 top ranked probe sets correlated with survival. Patients in the training set were split into tertiles based on the predictor (low, medium and high score) and patients in the test set were assigned to their predicted class, and Kaplan-Meier plots were generated for both training and test set. The differences in survival for both training and test set were statistically significant (Figure 1). Top ranked genes showing lower expression levels in patients with shorter survival include CDH1, LEF1 and AKAP12/Gravin. Top ranked genes showing higher expression levels in patients with shorter survival include IL23A, WT1 and PTHR2. Figure 2 shows survival of patients divided into tertiles of expression for the individual genes CDH1, LEF1 and WT1. It is probable that the genes identified in this study will become the first validated molecular markers for MDS prognosis. Multivariate analysis is currently being performed. Figure 1 Figure 1. Figure 2 Figure 2. Disclosure: No relevant conflicts of interest to declare.