Chemoresistant hepatoblastoma in a patient with mosaic trisomy 18 treated with orthotopic liver transplantation.

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.

High BAALC expression associates with other molecular prognostic markers, poor outcome, and a distinct gene-expression signature in cytogenetically normal patients younger than 60 years with acute myeloid leukemia: a Cancer and Leukemia Group B (CALGB) study.

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.

A Phase I and pharmacokinetic study of selenomethionine in combination with a fixed dose of irinotecan in solid tumors.

PURPOSE: We conducted a phase I study to determine the recommended dose of selenomethionine (SLM) in combination with irinotecan that consistently results in a protective plasma selenium (Se) concentrations > 15 microM after 1 week of SLM loading. EXPERIMENTAL DESIGN: A 3-3 standard escalation design was followed. SLM was given orally twice daily (BID) for one week (loading) followed by continuous once daily (QD) dosing (maintenance). Seven dose levels of selenomethionine were investigated. Irinotecan was given intravenously at a fixed standard weekly dose, starting on the first day of maintenance SLM. RESULTS: Thirty-one patients were treated on study. Dose limiting diarrhea complicated by sepsis was noted in one of six patients at each of the dose-levels 1 and 7. Dose-levels > or = 5 (4,800 mcg/dose loading maintenance) resulted in day 8 Se concentrations >15 microM while dose-level 7 (7,200 mcg/dose loading and maintenance) resulted in day 8 Se concentrations > 20 muM. No significant variations in SN-38 or biliary index were noted between weeks 1 and 4 of treatment. Despite achieving target Se concentrations, gastrointestinal and bone marrow toxicities were common and irinotecan dose modification was prevalent. Objective responses were seen in two patients and nine patients had disease control for 6 months or longer. CONCLUSIONS: Selenomethionine can be escalated safely to 7,200 mcg BID x 1 week followed by 7,200 mcg QD in combination with a standard dose of irinotecan. No major protection against irinotecan toxicity was established; however, interesting clinical benefits were noted-supporting the investigation of this combination in future efficacy trials.

Gene expression profiling of pediatric acute myelogenous leukemia.

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.

Classification of pediatric acute lymphoblastic leukemia by gene expression profiling.

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.

Classification, subtype discovery, and prediction of outcome in pediatric acute lymphoblastic leukemia by gene expression profiling.

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.