Project description:PAPER 1:"Identification of novel subgroups of high-risk pediatric precursor B acute lymphoblastic leukemia (B-ALL) by unsupervised microarray analysis: clinical correlates and therapeutic implications. A Children's Oncology Group (COG) study." ABSTRACT We examined gene expression profiles of pre-treatment specimens from 207 patients from the COG P9906 study to identify signatures of children with high risk B-precursor acute lymphoblastic leukemia (ALL) and to determine whether the resulting clusters are associated with either specific clinical features or treatment response characteristics. Four unsupervised clustering methods were utilized to classify patients into similar groups. The different clustering algorithms showed significant overlap in cluster membership. Two clusters contained all cases with either t(1;19)(q23;p13) translocations or MLL rearrangements. The other six clusters were novel and had no recurring chromosomal abnormalities or distinctive clinical features. Members of two of these novel clusters had significant survival differences when compared to the overall 4-year relapse-free survival (RFS) of 61%. These included clusters of patients with either significantly better (94.7%) or worse (21.0%) RFS at 4 years. Children of Hispanic/Latino ethnicity were disproportionately present in the poor outcome cluster. The poor outcome cluster represents a novel biologically distinctive subset of B-precursor ALL that may occur at least as frequently as BCR/ABL. Further molecular characterization of this cluster may lead to the discovery of genomic abnormalities that can be targeted to improve the currently dismal outcome for children with this gene signature. The Sample data have also been used in another study: PAPER 2: "Gene expression classifiers for minimal residual disease and relapse free survival improve outcome prediction and risk classification in children with high risk acute lymphoblastic leukemia. A Children's Oncology Group study". ABSTRACT Background. Nearly 25% of children with B-precursor ALL present with "high-risk" disease (HR-ALL) that is resistant to current therapies. Gene expression profiling may yield molecular classifiers for outcome prediction that can be used to improve risk classification and therapeutic targeting. Methods. Expression profiles were obtained in pre-treatment leukemic samples from 207 uniformly treated children with HR-ALL. Relapse free survival (RFS) was 61% at 4 years and flow cytometric measures of minimal residual disease (MRD) at the end of induction (day 29) were predictive of outcome (P<0.001). Molecular classifiers predictive of RFS and MRD were developed using extensive cross-validation procedures. Results. A 38 gene molecular risk classifier predictive of RFS (MRC-RFS) distinguished two groups in HR-ALL with different relapse risks: low (4 yr RFS: 81%, n=109) vs. high (4 yr RFS: 50%, n=98) (P<0.0001). In multivariate analysis, the best predictor combined MRC-RFS and day 29 flow MRD data, classifying children into low (87% RFS), intermediate (62% RFS), or high risk (29% RFS) groups (P<0.0001). A 21 gene molecular classifier predictive of MRD could effectively substitute for day 29 flow MRD, yielding a combined classifier that similarly distinguished three risk groups at pre-treatment (low: 82% RFS; intermediate: 63% RFS; and high risk: 45% RFS) (P<0.0001). This combined molecular classifier was further validated on an independent cohort of 84 children with HR-ALL (P = 0.006). Conclusions. Molecular classifiers predictive of RFS and MRD can be used to distinguish distinct prognostic groups within HR-ALL, significantly improving risk classification schemes and the ability to prospectively identify children at diagnosis who will respond to or fail current treatment regimens. NOTE: Due to Children's Oncology Group (COG) restrictions, outcome and MRD data cannot be provided as part of the covariate data for this dataset at the present time. If you would like to arrange individual access to this data, please contact COG or the PI of this study, Dr. Cheryl Willman, at the University of New Mexico Cancer Center (cwillman@unm.edu) to arrange a collaboration. Unsupervised clustering and supervised risk classification analyses of 207 diagnostic samples and associated clinical covariate data. See the Summary for greater details. The data were analyzed using Microarray Suite version 5.0 (MAS 5.0) in the Affymetrix Gene Chip Operating Software Version 1.4. Probe masking was used (see 9906_TT207_Affymetrix_probe_mask.msk, linked below as a supplementary file). Otherwise all Affymetrix default parameter settings were used. Global scaling as the normalization method, with the default target intensity of 500, was used.

Project description:PAPER 1:"Identification of novel subgroups of high-risk pediatric precursor B acute lymphoblastic leukemia (B-ALL) by unsupervised microarray analysis: clinical correlates and therapeutic implications. A Children's Oncology Group (COG) study." ABSTRACT We examined gene expression profiles of pre-treatment specimens from 207 patients from the COG P9906 study to identify signatures of children with high risk B-precursor acute lymphoblastic leukemia (ALL) and to determine whether the resulting clusters are associated with either specific clinical features or treatment response characteristics. Four unsupervised clustering methods were utilized to classify patients into similar groups. The different clustering algorithms showed significant overlap in cluster membership. Two clusters contained all cases with either t(1;19)(q23;p13) translocations or MLL rearrangements. The other six clusters were novel and had no recurring chromosomal abnormalities or distinctive clinical features. Members of two of these novel clusters had significant survival differences when compared to the overall 4-year relapse-free survival (RFS) of 61%. These included clusters of patients with either significantly better (94.7%) or worse (21.0%) RFS at 4 years. Children of Hispanic/Latino ethnicity were disproportionately present in the poor outcome cluster. The poor outcome cluster represents a novel biologically distinctive subset of B-precursor ALL that may occur at least as frequently as BCR/ABL. Further molecular characterization of this cluster may lead to the discovery of genomic abnormalities that can be targeted to improve the currently dismal outcome for children with this gene signature. The Sample data have also been used in another study: PAPER 2: "Gene expression classifiers for minimal residual disease and relapse free survival improve outcome prediction and risk classification in children with high risk acute lymphoblastic leukemia. A Children's Oncology Group study". ABSTRACT Background. Nearly 25% of children with B-precursor ALL present with "high-risk" disease (HR-ALL) that is resistant to current therapies. Gene expression profiling may yield molecular classifiers for outcome prediction that can be used to improve risk classification and therapeutic targeting. Methods. Expression profiles were obtained in pre-treatment leukemic samples from 207 uniformly treated children with HR-ALL. Relapse free survival (RFS) was 61% at 4 years and flow cytometric measures of minimal residual disease (MRD) at the end of induction (day 29) were predictive of outcome (P<0.001). Molecular classifiers predictive of RFS and MRD were developed using extensive cross-validation procedures. Results. A 38 gene molecular risk classifier predictive of RFS (MRC-RFS) distinguished two groups in HR-ALL with different relapse risks: low (4 yr RFS: 81%, n=109) vs. high (4 yr RFS: 50%, n=98) (P<0.0001). In multivariate analysis, the best predictor combined MRC-RFS and day 29 flow MRD data, classifying children into low (87% RFS), intermediate (62% RFS), or high risk (29% RFS) groups (P<0.0001). A 21 gene molecular classifier predictive of MRD could effectively substitute for day 29 flow MRD, yielding a combined classifier that similarly distinguished three risk groups at pre-treatment (low: 82% RFS; intermediate: 63% RFS; and high risk: 45% RFS) (P<0.0001). This combined molecular classifier was further validated on an independent cohort of 84 children with HR-ALL (P = 0.006). Conclusions. Molecular classifiers predictive of RFS and MRD can be used to distinguish distinct prognostic groups within HR-ALL, significantly improving risk classification schemes and the ability to prospectively identify children at diagnosis who will respond to or fail current treatment regimens. NOTE: Due to Children's Oncology Group (COG) restrictions, outcome and MRD data cannot be provided as part of the covariate data for this dataset at the present time. If you would like to arrange individual access to this data, please contact COG or the PI of this study, Dr. Cheryl Willman, at the University of New Mexico Cancer Center (cwillman@unm.edu) to arrange a collaboration.

Project description:BackgroundWhether social determinants of health are associated with survival in the context of pediatric oncology-targeted immunotherapy trials is not known. We examined the association between poverty and event-free survival (EFS) and overall survival (OS) for children with high-risk neuroblastoma treated in targeted immunotherapy trials.MethodsWe conducted a retrospective cohort study of 371 children with high-risk neuroblastoma treated with GD2-targeted immunotherapy in the Children's Oncology Group trial ANBL0032 or ANBL0931 at a Pediatric Health Information System center from 2005 to 2014. Neighborhood poverty exposure was characterized a priori as living in a zip code with a median household income within the lowest quartile for the cohort. Household poverty exposure was characterized a priori as sole coverage by public insurance. Post hoc analyses examined the joint effect of neighborhood and household poverty using a common reference. All statistical tests were 2-sided.ResultsIn multivariable Cox regressions adjusted for disease and treatment factors, household poverty-exposed children experienced statistically significantly inferior EFS (hazard ratio [HR] = 1.90, 95% confidence interval [CI] = 1.28 to 2.82, P = .001) and OS (HR = 2.79, 95% CI = 1.63 to 4.79, P < .001) compared with unexposed children. Neighborhood poverty was not independently associated with EFS or OS. In post hoc analyses exploring the joint effect of neighborhood and household poverty, children with dual-poverty exposure (neighborhood poverty and household poverty) experienced statistically significantly inferior EFS (HR = 2.21, 95% CI = 1.48 to 3.30, P < .001) and OS (HR = 3.70, 95% CI = 2.08 to 6.59, P < .001) compared with the unexposed group.ConclusionsPoverty is independently associated with increased risk of relapse and death among neuroblastoma patients treated with targeted immunotherapy. Incorporation of social and environmental factors in future trials as health-care delivery intervention targets may increase the benefit of targeted therapies.

Project description:A semiquantitative 123I-metaiodobenzylguanidine (123I-MIBG) scoring method (the Curie score, or CS) was previously examined in the Children's Oncology Group (COG) high-risk neuroblastoma trial, COG A3973, with a postinduction CS of more than 2 being associated with poor event-free survival (EFS). The validation of the CS in an independent dataset, International Society of Paediatric Oncology European Neuroblastoma/High-Risk Neuroblastoma 1 (SIOPEN/HR-NBL1), is now reported. Methods: A retrospective analysis of 123I-MIBG scans obtained from patients who had been prospectively enrolled in SIOPEN/HR-NBL1 was performed. All patients exhibited 123I-MIBG-avid, International Neuroblastoma Staging System stage 4 neuroblastoma. 123I-MIBG scans were evaluated at 2 time points, diagnosis (n = 345) and postinduction (n = 330), before consolidation myeloablative therapy. Scans of 10 anatomic regions were evaluated, with each region being scored 0-3 on the basis of disease extent and a cumulative CS generated. Cut points for outcome analysis were identified by Youden methodology. CSs from patients enrolled in COG A3973 were used for comparison. Results: The optimal cut point for CS at diagnosis was 12 in SIOPEN/HR-NBL1, with a significant outcome difference by CS noted (5-y EFS, 43.0% ± 5.7% [CS ? 12] vs. 21.4% ± 3.6% [CS > 12], P < 0.0001). The optimal CS cut point after induction was 2 in SIOPEN/HR-NBL1, with a postinduction CS of more than 2 being associated with an inferior outcome (5-y EFS, 39.2% ± 4.7% [CS ? 2] vs. 16.4% ± 4.2% [CS > 2], P < 0.0001). The postinduction CS maintained independent statistical significance in Cox models when adjusted for the covariates of age and MYCN gene copy number. Conclusion: The prognostic significance of postinduction CSs has now been validated in an independent cohort of patients (SIOPEN/HR-NBL1), with a postinduction CS of more than 2 being associated with an inferior outcome in 2 independent large, cooperative group trials.

Project description:PurposeInfants with stage 4S neuroblastoma usually have favorable outcomes with observation or minimal chemotherapy. However, young infants with symptoms secondary to massive hepatomegaly or with unfavorable tumor biology are at high risk of death. Our aim was to improve outcomes for patients with symptomatic and/or unfavorable biology 4S neuroblastoma with a uniform treatment approach using a biology- and response-based algorithm.Patients and methodsThe subset of patients with 4S disease with MYCN-not amplified tumors with impaired or impending organ dysfunction, or with unfavorable histology and/or diploid DNA index, were eligible. Patients were assigned to receive two, four, or eight cycles of chemotherapy on the basis of histology, diploid DNA index, chromosome arm 1p or 11q loss of heterozygosity (LOH) status, and symptoms.ResultsForty-nine eligible patients were enrolled: 41 were symptomatic and 28 had unfavorable biology. Seventeen patients (symptomatic, favorable biology) were assigned two cycles, 21 patients (any unfavorable biologic feature without 1p or 11q LOH) were assigned four cycles, and 11 patients (unfavorable biology including 1p and/or 11q LOH [n = 7] or symptomatic with unknown biology [n = 4]), were assigned eight cycles. The 3-year overall survival was 81.4% ± 5.8%. Eight of nine deaths were in patients younger than 2 months of age at diagnosis (median, 9 days [range, 1 to 68 days]): five acute deaths were a result of hepatomegaly and associated toxicities; two were a result of late relapse in patients with unfavorable biology; and two were a result of treatment complications. No deaths occurred after protocol-mandated pre-emptive treatment of infants younger than 2 months with hepatomegaly, regardless of symptoms. A new scoring algorithm for emergent chemotherapy in patients with 4S disease was developed on the basis of this experience.ConclusionThe outcome for 4S neuroblastoma can be improved with pre-emptive chemotherapy for evolving hepatomegaly or other baseline comorbidities in infants younger than 2 months of age.

Project description:PURPOSE:The primary objective of the Children's Oncology Group study ANBL0531 (ClinicalTrials.gov identifier: NCT00499616) was to reduce therapy for subsets of patients with intermediate-risk neuroblastoma using a biology- and response-based algorithm to assign treatment duration while maintaining a 3-year overall survival (OS) of 95% or more for the entire cohort. PATIENTS AND METHODS:Children younger than age 12 years with intermediate-risk stage 2A/2B or stage 3 tumors with favorable histology; infants younger than age 365 days with stage 3, 4 or 4S disease; and toddlers from 365 to younger than 547 days with favorable histology, hyperdiploid stage 4, or unfavorable histology stage 3 tumors were eligible. Patients with MYCN-amplified tumors were excluded. Patients were assigned to initially receive two (group 2), four (group 3), or eight (group 4) cycles of chemotherapy with or without surgery on the basis of prognostic markers, including allelic status of chromosomes 1p and 11q; ultimate duration of therapy was determined by overall response. RESULTS:Between 2007 and 2011, 404 evaluable patients were enrolled. Compared with legacy Children's Oncology Group studies, subsets of patients had a reduction in treatment. The 3-year event-free survival and OS rates were 83.2% (95% CI, 79.4% to 87.0%) and 94.9% (95% CI, 92.7% to 97.2%), respectively. Infants with stage 4 tumors with favorable biology (n = 61) had superior 3-year event-free survival compared with patients with one or more unfavorable biologic features (n = 47; 86.9% [95% CI, 78.3% to 95.4%] v 66.8% [95% CI, 53.1% to 80.6%]; P = .02), with a trend toward OS advantage (95.0% [95% CI, 89.5% to 100%] v 86.7% [95% CI, 76.6% to 96.7%], respectively; P = .08). OS for patients with localized disease was 100%. CONCLUSION:Excellent survival was achieved with this treatment algorithm, with reduction of therapy for subsets of patients. More-effective treatment strategies still are needed for infants with unfavorable biology stage 4 disease.

Dataset Information

Ototoxicity in children with high-risk neuroblastoma: prevalence, risk factors, and concordance of grading scales--a report from the Children's Oncology Group.

Publications

Ototoxicity in children with high-risk neuroblastoma: prevalence, risk factors, and concordance of grading scales--a report from the Children's Oncology Group.

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