• Media type: E-Article
  • Title: Analysis of Subset Chimerism for MRD-Detection and Pre-Emptive Treatment in AML
  • Contributor: Georgi, Julia-Annabell [Author]; Stasik, Sebastian [Author]; Bornhäuser, Martin [Author]; Platzbecker, Uwe [Author]; Thiede, Christian [Author]
  • imprint: Lausanne : Frontiers Research Foundation, [2023]
  • Language: English
  • Keywords: AML ; pre-emptive treatment ; detection ; subset chimerism ; relapse ; allogeneic cell transplantation ; medicine ; Medizin
  • Origination:
  • Footnote: Hinweis: Link zur Erstveröffentlichung URL: https://doi.org/10.3389/fonc.2022.841608
  • Description: Allogeneic hematopoietic stem cell transplantation (alloHCT) represents the only potentially curative treatment in high-risk AML patients, but up to 40% of patients suffer from relapse after alloHCT. Treatment of overt relapse poses a major therapeutic challenge and long-term disease control is achieved only in a minority of patients. In order to avoid post-allograft relapse, maintenance as well as pre-emptive therapy strategies based on MRD-detection have been used. A prerequisite for the implementation of pre-emptive therapy is the accurate identification of patients at risk for imminent relapse. Detection of measurable residual disease (MRD) represents an effective tool for early relapse prediction in the post-transplant setting. However, using established MRD methods such as multicolor flow cytometry or quantitative PCR, sensitive MRD monitoring is only applicable in about half of the patients with AML and advanced MDS undergoing alloHCT. Donor chimerism analysis, in particular when performed on enriched leukemic stem and progenitor cells, e.g. CD34+ cells, is a sensitive method and has emerged as an alternative option in the post alloHCT setting. In this review, we will focus on the current strategies for lineage specific chimerism analysis, results of pre-emptive treatment using this technology as well as future developments in this field.
  • Access State: Open Access
  • Rights information: Attribution (CC BY)