title: Detection of minimal residual disease in B lymphoblastic leukemia using viSNE.
abstract: BACKGROUND
  Minimal 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.
  
  
  METHODS
  We 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.
  
  
  RESULTS
  In 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.
  
  
  CONCLUSIONS
  viSNE shows promise as an automated method to facilitate immunophenotypic MRD detection in patients treated for B lymphoblastic leukemia.
authors.affiliation: Department of Pathology & Laboratory Medicine, Hartford Hospital, Hartford, Connecticut.
authors.forename: Joseph A
authors.initials: JA
authors.lastname: DiGiuseppe
authors.affiliation: Department of Biological Sciences, Columbia University, New York, New York.|Department of Systems Biology, Columbia University, New York, New York.
authors.forename: Michelle D
authors.initials: MD
authors.lastname: Tadmor
authors.affiliation: Department of Biological Sciences, Columbia University, New York, New York.|Department of Systems Biology, Columbia University, New York, New York.
authors.forename: Dana
authors.initials: D
authors.lastname: Pe'er
mesh_terms: D000465:Algorithms; D057205:Automation, Laboratory; D014408:Biomarkers, Tumor / Q000032:analysis*; D001856:Bone Marrow Examination / Q000379:methods*; D005434:Flow Cytometry / Q000379:methods*; D006801:Humans; D016130:Immunophenotyping / Q000379:methods*; D015448:Leukemia, B-Cell / Q000139:chemically induced* / Q000276:immunology / Q000473:pathology / Q000628:therapy; D018365:Neoplasm, Residual; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes; D016896:Treatment Outcome
chemical_list: D014408:Biomarkers, Tumor
keywords: ALL; B lymphoblastic leukemia; flow cytometry; minimal residual disease; viSNE