Genetic profiling in acute myeloid leukaemia--where are we and what is its role in patient management

Br J Haematol. 2013 Feb;160(3):303-20. doi: 10.1111/bjh.12135. Epub 2012 Dec 13.

Abstract

Genetic profiling in acute myeloid leukaemia (AML) is a moving target. Only 4 years ago, AML was re-classified, based on karyotypic abnormalities. However, numerous important new mutations and other genetic abnormalities that were not considered in this classification have been identified. Current cytogenetic-based classification is limited by the substantial number of intermediate-risk patients in whom the preferred therapy is debatable. In addition, the majority of AML patients co-express multiple mutations and cannot be easily categorized into predefined homogenous groups. The tremendous progress in mass sequencing allows parallel identification of multiple genetic aberrations in large cohorts. Thus, a new concept of genetic profiling has arisen. Genes and proteins biologically interact with each other; therefore, it should not be surprising that mutations in different genes interact. Prognosis is determined by the composition of mutations and aberrations in leukaemic stem cells. As a consequence, clinical decisions no longer rely on scant genetic data and require comprehensive genetic evaluation. Some non-genetic parameters are also important and should be incorporated into the clinical decision algorithm. Genetic interaction-based profiles are challenging and recent studies demonstrate an improvement in prognostic predictions with this model. Thus, genetic profiling is likely to have a major therapeutic impact, at least for intermediate-risk cytogenetics.

Publication types

  • Review

MeSH terms

  • Biomarkers, Tumor / genetics
  • Chromosome Aberrations
  • Epigenesis, Genetic
  • Gene Expression Profiling*
  • Gene Expression Regulation, Leukemic*
  • Humans
  • Leukemia, Myeloid, Acute / diagnosis
  • Leukemia, Myeloid, Acute / genetics*
  • MicroRNAs / genetics
  • Mutation
  • Point-of-Care Systems
  • Prognosis
  • Recurrence

Substances

  • Biomarkers, Tumor
  • MicroRNAs