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.

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;

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-RAR␣], t(8;21)[AML1-ETO], inv 16 [CBF␤-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. IntroductionAcute myeloid leukemia (AML) is a relatively rare malignancy in the pediatric population, comprising only 15% to 20% of the acute leukemias diagnosed in this age group. 1 Nevertheless, it remains a challenging disease with an inferior treatment outcome compared with pediatric acute lymphoblastic leukemia (ALL). Despite the introduction of new drugs, the aggressive use of allogeneic and autologous bone marrow transplantation, and improvements in supportive care, overall cure rates of AML in most contemporary treatment protocols remain below 60%. [2][3][4][5] Further improvements in cure rates are likely to come from a better understanding of both the molecular abnormalities responsible for the formation and growth of the leukemic cells, and the mechanisms underlying drug resistance.Increasingly, contemporary treatment protocols are incorporating methods for both accurate diagnosis and subsequent risk stratification. To achieve this requires not only distinguishing myeloblasts from lymphoblasts, but also assessing the extent of lineage commitment and differentiation, as well as the presence of specific molecular lesions or chromosomal abnormalities. Efforts over the last several decades have revealed AML to be a heterogeneous disease, with marked differences in cure rates between various genetic subtypes. [6][7][8][9] Acute promyelocytic leukemia was the first clear example of a clinically distinct AML subtype, being characterized by FAB-M3 morphology and expression of the t(15;17)-encoded promyelocytic leukemia-retinoic acid receptor alpha (PML-RAR␣) fusion protein. [10][11][12][13][14] ...

BAALC expression is considered an independent prognostic factor in cytogenetically normal acute myeloid leukemia (CN-AML), but has yet to be investigated together with multiple other established prognostic molecular markers in CN-AML. We analyzed BAALC expression in 172 primary CN-AML patients younger than 60 years of age, treated similarly on CALGB protocols. High BAALC expression was associated with FLT3-ITD (P = .04), wild-type NPM1 (P < .001), mutated CEBPA (P = .003), MLL-PTD (P = .009), absent FLT3-TKD (P = .005), and high ERG expression (P = .05). In multivariable analysis, high BAALC expression independently predicted lower complete remission rates (P = .04) when adjusting for ERG expression and age, and shorter survival (P = .04) when adjusting for FLT3-ITD, NPM1, CEBPA, and white blood cell count. A gene-expression signature of 312 probe sets differentiating high from low BAALC expressers was identified. High BAALC expression was associated with overexpression of genes involved in drug resistance (MDR1) and stem cell markers (CD133, CD34, KIT). Global microRNA-expression analysis did not reveal significant differences between BAALC expression groups. However, an analysis of microRNAs that putatively target BAALC revealed a potentially interesting inverse association between expression of miR-148a and BAALC. We conclude that high BAALC expression is an independent adverse prognostic factor and is associated with a specific gene-expression profile.

We present a 9-month-old male with mosaic trisomy 18 with a right hepatic lobe mass. The tumor was completely resected and identified as pure fetal histology hepatoblastoma but contained increased mitotic activity. Adjuvant chemotherapy consisted of cisplatin, vincristine, and 5-fluorouracil. After the first and fourth cycles of chemotherapy, recurrent tumor developed. The patient underwent rescue orthotopic liver transplantation, and is currently alive without evidence of hepatoblastoma 28 months after transplantation. This report demonstrates the use of orthotopic liver transplantation in a child with mosaic trisomy 18 and hepatoblastoma.