Flow cytometric detection of minimal residual disease in acute lymphoblastic leukemia

Leuk Lymphoma. 2003 Sep;44(9):1445-55. doi: 10.3109/10428190309178763.

Abstract

Assessment of minimal residual disease (MRD) during the first months of therapy gives information on the timely response to treatment, and proves to be a powerful and independent indicator of treatment outcome in patients with acute lymphoblastic leukemia (ALL). Immunological evaluation by flow cytometry (FCM) is one of the most attractive approaches to this. The present review summarizes the historical development of this approach over the last 20 years, and shows that current methodology is based on the existence of leukemia-associated patterns of derangement in antigen expression with respect to normal differentiation or location of occurrence. Recent clinical studies are summarized which proved that FCM is applicable to more than 90% of patients with ALL and gives prognostic information comparable to polymerase chain-reaction (PCR)-based technology. Ongoing efforts based on parallel application of both technologies are explained which are designed to clarify which approach bears the best cost-relevance ratio in order to be broadly used in the future for risk assessment and tailoring of treatment modalities. Concluding perspectives relate to further technical developments like usage of peripheral blood (PB) instead of bone marrow (BM), absolute quantification, or strategic placement of investigative time-points, which may allow to simplify the MRD approach and thus augment it's economic efficiency.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Adult
  • Biomarkers, Tumor / analysis
  • Bone Marrow / pathology
  • Child
  • DNA, Neoplasm / analysis
  • Flow Cytometry / methods*
  • Flow Cytometry / trends
  • Humans
  • Immunophenotyping / methods
  • Neoplasm, Residual
  • Polymerase Chain Reaction
  • Precursor Cell Lymphoblastic Leukemia-Lymphoma / pathology*
  • Sensitivity and Specificity

Substances

  • Biomarkers, Tumor
  • DNA, Neoplasm