Detection of minimal residual disease in B lymphoblastic leukemia using viSNE

BackgroundMinimal residual disease (MRD) following treatment is a robust prognostic marker in B lymphoblastic leukemia. However, the detection of MRD by flow cytometric immunophenotyping is technically challenging, and an automated method to detect MRD is therefore desirable. viSNE, a recently developed computational tool based on the t-Distributed Stochastic Neighbor Embedding (t-SNE) algorithm, has been shown to be capable of detecting synthetic MRD-like populations of leukemic cells created in vitro, but whether viSNE can facilitate the immunophenotypic detection of MRD in clinical samples has not been evaluated. MethodsWe applied viSNE retrospectively to 8-color flow cytometric immunophenotyping data from normal bone marrow samples, and samples from B lymphoblastic leukemia patients with or without suspected MRD on the basis of conventional manual gating. ResultsIn each of 14 bone marrow specimens containing MRD or suspected MRD, viSNE identified a putative MRD population; an abnormal composite immunophenotype was confirmed for the putative MRD in each case. MRD populations were not identified by viSNE in control bone marrow samples from patients with increased normal B-cell precursors, or in post-treatment samples from B lymphoblastic leukemia patients who did not have detectable MRD by manual gating. ConclusionviSNE shows promise as an automated method to facilitate immunophenotypic MRD detection in patients treated for B lymphoblastic leukemia. (c) 2015 International Clinical Cytometry Society