Description
ALL is the most common form of childhood cancer with >80% cured with contemporary treatment protocols. Accurate risk stratification in childhood ALL is essential to avoid under- and over-treatment. Currently, we use presenting clinical, biological features, and minimal residual disease (MRD) quantitation to risk stratify patients. Although whole genome gene expression profiling (GEP) can accurately classify patients with ALL into various WHO 2008 defined subgroups, its value in predicting relapse remained to be defined. We hypothesized that global time-series GEPs of bone marrow (BM) samples at diagnosis and specific points during initial remission-induction therapy can measure the success of cytoreduction and be used for relapse prediction.