Identification of biomarkers for the prediction of relapse-free survival in pediatric B-precursor acute lymphoblastic leukemia

Abstract

B-precursor acute lymphoblastic leukemia (B-ALL) is the most common cancer diagnosed in children and adolescents. Despite the fact that the 5-year survival rate has increased from 60 to 90%, approximately a quarter of children suffer from relapse with poor outcome. To improve the clinical management of B-ALL, there is an urgent need for prognostic biomarkers for the prediction of B-ALL outcomes. In the present study, we performed a comprehensive analysis of the gene expression data of 456 samples from five independent cohorts. We first sought to identify B-ALL-associated genes by differential gene expression analysis by applying linear models. Then, the statistical modelling was applied to identify candidates related to relapse-free survival. We identified a total of 1,273 B-ALL-associated genes that have functions relevant to chemokine signaling. From these genes, 59 genes were identified as prognostic biomarkers. Based on expression patterns of these genes, we successfully distinguished high-.and low-risk groups of B-ALL patients (log-rank test, P-value=0.025). We further investigated the 59-gene expression levels in ALL chemotherapy-treated cohorts and identified 4 genes as potential drug targets associated with drug sensitivity. Our results provided a novel biomarker panel. By leveraging the large scale of data and statistical modelling, we believe this 59-gene biomarker could help to unveil the mechanisms underlying B-ALL progression and become potential drug targets.