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Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children’s Oncology Group protocol AAML0531
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 establis...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Ferrata Storti Foundation
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5709105/ https://www.ncbi.nlm.nih.gov/pubmed/28883080 http://dx.doi.org/10.3324/haematol.2017.169029 |
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author | Voigt, Andrew P. Brodersen, Lisa Eidenschink Alonzo, Todd A. Gerbing, Robert B. Menssen, Andrew J. Wilson, Elisabeth R. Kahwash, Samir Raimondi, Susana C. Hirsch, Betsy A. Gamis, Alan S. Meshinchi, Soheil Wells, Denise A. Loken, Michael R. |
author_facet | Voigt, Andrew P. Brodersen, Lisa Eidenschink Alonzo, Todd A. Gerbing, Robert B. Menssen, Andrew J. Wilson, Elisabeth R. Kahwash, Samir Raimondi, Susana C. Hirsch, Betsy A. Gamis, Alan S. Meshinchi, Soheil Wells, Denise A. Loken, Michael R. |
author_sort | Voigt, Andrew P. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-5709105 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Ferrata Storti Foundation |
record_format | MEDLINE/PubMed |
spelling | pubmed-57091052017-12-12 Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children’s Oncology Group protocol AAML0531 Voigt, Andrew P. Brodersen, Lisa Eidenschink Alonzo, Todd A. Gerbing, Robert B. Menssen, Andrew J. Wilson, Elisabeth R. Kahwash, Samir Raimondi, Susana C. Hirsch, Betsy A. Gamis, Alan S. Meshinchi, Soheil Wells, Denise A. Loken, Michael R. Haematologica Article 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. Ferrata Storti Foundation 2017-12 /pmc/articles/PMC5709105/ /pubmed/28883080 http://dx.doi.org/10.3324/haematol.2017.169029 Text en Copyright© 2017 Ferrata Storti Foundation Material published in Haematologica is covered by copyright. All rights are reserved to the Ferrata Storti Foundation. Use of published material is allowed under the following terms and conditions: https://creativecommons.org/licenses/by-nc/4.0/legalcode. Copies of published material are allowed for personal or internal use. Sharing published material for non-commercial purposes is subject to the following conditions: https://creativecommons.org/licenses/by-nc/4.0/legalcode, sect. 3. Reproducing and sharing published material for commercial purposes is not allowed without permission in writing from the publisher. |
spellingShingle | Article Voigt, Andrew P. Brodersen, Lisa Eidenschink Alonzo, Todd A. Gerbing, Robert B. Menssen, Andrew J. Wilson, Elisabeth R. Kahwash, Samir Raimondi, Susana C. Hirsch, Betsy A. Gamis, Alan S. Meshinchi, Soheil Wells, Denise A. Loken, Michael R. Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children’s Oncology Group protocol AAML0531 |
title | Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children’s Oncology Group protocol AAML0531 |
title_full | Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children’s Oncology Group protocol AAML0531 |
title_fullStr | Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children’s Oncology Group protocol AAML0531 |
title_full_unstemmed | Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children’s Oncology Group protocol AAML0531 |
title_short | Phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from Children’s Oncology Group protocol AAML0531 |
title_sort | phenotype in combination with genotype improves outcome prediction in acute myeloid leukemia: a report from children’s oncology group protocol aaml0531 |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5709105/ https://www.ncbi.nlm.nih.gov/pubmed/28883080 http://dx.doi.org/10.3324/haematol.2017.169029 |
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