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1.
Blood ; 104(12): 3679-87, 2004 Dec 01.
Artigo em Inglês | MEDLINE | ID: mdl-15226186

RESUMO

Contemporary treatment of pediatric acute myeloid leukemia (AML) requires the assignment of patients to specific risk groups. To explore whether expression profiling of leukemic blasts could accurately distinguish between the known risk groups of AML, we analyzed 130 pediatric and 20 adult AML diagnostic bone marrow or peripheral blood samples using the Affymetrix U133A microarray. Class discriminating genes were identified for each of the major prognostic subtypes of pediatric AML, including t(15;17)[PML-RARalpha], t(8;21)[AML1-ETO], inv(16) [CBFbeta-MYH11], MLL chimeric fusion genes, and cases classified as FAB-M7. When subsets of these genes were used in supervised learning algorithms, an overall classification accuracy of more than 93% was achieved. Moreover, we were able to use the expression signatures generated from the pediatric samples to accurately classify adult de novo AMLs with the same genetic lesions. The class discriminating genes also provided novel insights into the molecular pathobiology of these leukemias. Finally, using a combined pediatric data set of 130 AMLs and 137 acute lymphoblastic leukemias, we identified an expression signature for cases with MLL chimeric fusion genes irrespective of lineage. Surprisingly, AMLs containing partial tandem duplications of MLL failed to cluster with MLL chimeric fusion gene cases, suggesting a significant difference in their underlying mechanism of transformation.


Assuntos
Perfilação da Expressão Gênica , Leucemia Mieloide Aguda/classificação , Leucemia Mieloide Aguda/genética , Adulto , Algoritmos , Sangue , Medula Óssea , Criança , Análise por Conglomerados , Proteínas de Ligação a DNA/genética , Histona-Lisina N-Metiltransferase , Humanos , Proteína de Leucina Linfoide-Mieloide , Proteínas de Fusão Oncogênica/genética , Prognóstico , Proto-Oncogenes/genética , Fatores de Risco , Sequências de Repetição em Tandem , Fatores de Transcrição/genética
2.
Blood ; 102(8): 2951-9, 2003 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-12730115

RESUMO

Contemporary treatment of pediatric acute lymphoblastic leukemia (ALL) requires the assignment of patients to specific risk groups. We have recently demonstrated that expression profiling of leukemic blasts can accurately identify the known prognostic subtypes of ALL, including T-cell lineage ALL (T-ALL), E2A-PBX1, TEL-AML1, MLL rearrangements, BCR-ABL, and hyperdiploid karyotypes with more than 50 chromosomes. As the next step toward developing this methodology into a frontline diagnostic tool, we have now analyzed leukemic blasts from 132 diagnostic samples using higher density oligonucleotide arrays that allow the interrogation of most of the identified genes in the human genome. Nearly 60% of the newly identified subtype discriminating genes are novel markers not identified in our previous study, and thus should provide new insights into the altered biology underlying these leukemias. Moreover, a proportion of the newly selected genes are highly ranked as class discriminators, and when incorporated into class-predicting algorithms resulted in an overall diagnostic accuracy of 97%. The performance of an array containing the identified discriminating genes should now be assessed in frontline clinical trials in order to determine the accuracy, practicality, and cost effectiveness of this methodology in the clinical setting.


Assuntos
Regulação Leucêmica da Expressão Gênica , Leucemia-Linfoma Linfoblástico de Células Precursoras/classificação , Leucemia-Linfoma Linfoblástico de Células Precursoras/genética , Algoritmos , Medula Óssea/metabolismo , Humanos , Cariotipagem , Redes Neurais de Computação , Análise de Sequência com Séries de Oligonucleotídeos , Filogenia , Leucemia-Linfoma Linfoblástico de Células Precursoras/diagnóstico , Prognóstico
3.
Cancer Cell ; 1(2): 133-43, 2002 Mar.
Artigo em Inglês | MEDLINE | ID: mdl-12086872

RESUMO

Treatment of pediatric acute lymphoblastic leukemia (ALL) is based on the concept of tailoring the intensity of therapy to a patient's risk of relapse. To determine whether gene expression profiling could enhance risk assignment, we used oligonucleotide microarrays to analyze the pattern of genes expressed in leukemic blasts from 360 pediatric ALL patients. Distinct expression profiles identified each of the prognostically important leukemia subtypes, including T-ALL, E2A-PBX1, BCR-ABL, TEL-AML1, MLL rearrangement, and hyperdiploid >50 chromosomes. In addition, another ALL subgroup was identified based on its unique expression profile. Examination of the genes comprising the expression signatures provided important insights into the biology of these leukemia subgroups. Further, within some genetic subgroups, expression profiles identified those patients that would eventually fail therapy. Thus, the single platform of expression profiling should enhance the accurate risk stratification of pediatric ALL patients.


Assuntos
Perfilação da Expressão Gênica , Leucemia-Linfoma Linfoblástico de Células Precursoras/diagnóstico , Leucemia-Linfoma Linfoblástico de Células Precursoras/genética , Algoritmos , Criança , Biologia Computacional , Humanos , Imunofenotipagem , Leucemia Mieloide Aguda/classificação , Leucemia Mieloide Aguda/diagnóstico , Leucemia Mieloide Aguda/genética , Leucemia Mieloide Aguda/patologia , Análise de Sequência com Séries de Oligonucleotídeos/métodos , Leucemia-Linfoma Linfoblástico de Células Precursoras/classificação , Leucemia-Linfoma Linfoblástico de Células Precursoras/patologia , Prognóstico , Recidiva , Fatores de Risco , Falha de Tratamento
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