Classification of pediatric acute lymphoblastic leukemia by gene expression profiling

Abstract

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. (Blood. 2003;

Expression of Late Cell Cycle Genes and an Increased Proliferative Capacity Characterize Very Early Relapse of Childhood Acute Lymphoblastic Leukemia

“…For these analyses, we focused on the 52 patients with B-lineage ALL to avoid a distortion of results solely based on gene expression differences between ALL immunophenotypes. Pronounced differences in gene expression profiles between B-and T-lineage ALL have been described before and were confirmed by our data, supporting the notion that these ALL subtypes represent distinct biological and clinical entities (10,12).…”

“…Therefore, we asked whether those gene expression signatures that predict genetic and immunologic subtypes in initial ALL (10,12) could also faithfully classify relapse samples based on the present analysis. To this end, published data from 104 initial ALL patients (10) were used as training set to recalculate the diagnostic signatures of the ALL subtypes shown in Table 1.…”

“…For classification of microarray expression profiles into discrete ALL subtypes, we used the nearest shrunken centroid methods by Tibshirani et al (24). The diagnostic signatures of initial ALL published by Ross et al (10) were recalculated on the jointly normalized data. For predicting the fraction of S and G 2 -M phase cells in samples based on gene expression profiles, we used least angle regression (25).…”

The heterogeneity of pediatric MLL-rearranged acute myeloid leukemia

“…61 In gene expression profiling (GEP) studies, MLL-rearranged cases clustered together as one group in AML as well as in ALL. 13,[62][63][64] However, our laboratory showed that within MLL-rearranged infant ALL each type of MLL translocation is associated with a translocation-specific gene expression signature. 65 We identified a specific gene expression signature for the total group of MLL-rearranged AML cases, 12 but were also able to identify a specific signature for t(9;11)(p22;q23).…”

Trisomy of chromosome 21 in leukemogenesis

“…Three (trisomy) or four (tetrasomy) copies of chromosome 21 is common in childhood acute lymphoblastic leukemia (ALL) [2][3][4]. Children with Down syndrome (DS) who carry trisomy 21 in all their cells have a 20-fold increased risk for childhood ALL and 600-fold risk for acute megakaryocytic leukemia (AMKL) [5].…”