Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children’s Oncology Group protocol AAML0531
| Autor: | Andrew P. Voigt, Lisa Eidenschink Brodersen, Todd A. Alonzo, Robert B. Gerbing, Andrew J. Menssen, Elisabeth R. Wilson, Samir Kahwash, Susana C. Raimondi, Betsy A. Hirsch, Alan S. Gamis, Soheil Meshinchi, Denise A. Wells, Michael R. Loken |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| Zdroj: | Haematologica, Vol 102, Iss 12 (2017) |
| Druh dokumentu: | article |
| ISSN: | 0390-6078 1592-8721 |
| DOI: | 10.3324/haematol.2017.169029 |
| Popis: | Diagnostic biomarkers can be used to determine relapse risk in acute myeloid leukemia, and certain genetic aberrancies have prognostic relevance. A diagnostic immunophenotypic expression profile, which quantifies the amounts of distinct gene products, not just their presence or absence, was established in order to improve outcome prediction for patients with acute myeloid leukemia. The immunophenotypic expression profile, which defines each patient’s leukemia as a location in 15-dimensional space, was generated for 769 patients enrolled in the Children’s Oncology Group AAML0531 protocol. Unsupervised hierarchical clustering grouped patients with similar immunophenotypic expression profiles into eleven patient cohorts, demonstrating high associations among phenotype, genotype, morphology, and outcome. Of 95 patients with inv(16), 79% segregated in Cluster A. Of 109 patients with t(8;21), 92% segregated in Clusters A and B. Of 152 patients with 11q23 alterations, 78% segregated in Clusters D, E, F, G, or H. For both inv(16) and 11q23 abnormalities, differential phenotypic expression identified patient groups with different survival characteristics (P |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
|