TY - JOUR
T1 - Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia
T2 - A report from children’s oncology group protocol AAML0531
AU - Voigt, Andrew P.
AU - Brodersen, Lisa Eidenschink
AU - Alonzo, Todd A.
AU - Gerbing, Robert B.
AU - Menssen, Andrew J.
AU - Wilson, Elisabeth R.
AU - Kahwash, Samir
AU - Raimondi, Susana C.
AU - Hirsch, Betsy A.
AU - Gamis, Alan S.
AU - Meshinchi, Soheil
AU - Wells, Denise A.
AU - Loken, Michael R.
N1 - Publisher Copyright:
© 2017 Ferrata Storti Foundation.
PY - 2017/11/30
Y1 - 2017/11/30
N2 - 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<0.05). Clinical outcome analysis revealed that Cluster B (predominantly t(8;21)) was associated with favorable outcome (P<0.001) and Clusters E, G, H, and K were associated with adverse outcomes (P<0.05). Multivariable regression analysis revealed that Clusters E, G, H, and K were independently associated with worse survival (P range <0.001 to 0.008). The Children’s Oncology Group AAML0531 trial: clinicaltrials.gov Identifier: 00372593.
AB - 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<0.05). Clinical outcome analysis revealed that Cluster B (predominantly t(8;21)) was associated with favorable outcome (P<0.001) and Clusters E, G, H, and K were associated with adverse outcomes (P<0.05). Multivariable regression analysis revealed that Clusters E, G, H, and K were independently associated with worse survival (P range <0.001 to 0.008). The Children’s Oncology Group AAML0531 trial: clinicaltrials.gov Identifier: 00372593.
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U2 - 10.3324/haematol.2017.169029
DO - 10.3324/haematol.2017.169029
M3 - Article
C2 - 28883080
AN - SCOPUS:85037046295
SN - 0390-6078
VL - 102
SP - 2058
EP - 2068
JO - Haematologica
JF - Haematologica
IS - 12
ER -