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: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: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:ImportanceWhether population-based racial and ethnic survival disparities for children with high-risk neuroblastoma persist in the clinical trial setting is unknown.ObjectiveTo investigate racial and ethnic survival disparities among children with high-risk neuroblastoma treated on frontline clinical trials.Design, setting, and participantsThis retrospective cohort study used data from Children's Oncology Group (COG) high-risk neuroblastoma trials from January 1, 2007, to December 31, 2016, with a data freeze on June 30, 2021. Children with high-risk neuroblastoma were analyzed in 2 cohorts: induction/consolidation trial participants and post-consolidation trial participants. Statistical analyses were performed from September 2, 2021, to December 30, 2024.ExposuresRace and ethnicity were the primary exposures, categorized as Hispanic, non-Hispanic Black, non-Hispanic other (American Indian or Alaska Native, Asian, and Native Hawaiian or Other Pacific Islander), or non-Hispanic White.Main outcomes and measuresPrimary outcomes included overall survival (OS) and event-free survival (EFS) from time of trial enrollment, estimated by Kaplan-Meier methods. Associations with race and ethnicity were evaluated by log-rank tests and Cox proportional hazards regression models. Secondary outcomes included induction delays, early trial withdrawal, relapse as first event, death as first event, postrelapse OS, and early phase trial enrollment.ResultsThe induction/consolidation cohort (median follow-up, 8.3 years [IQR, 6.1-9.8 years]) included 696 patients (404 males [58.1%]; 79 Hispanic patients [11.4%], 109 non-Hispanic Black patients [15.7%], 27 patients of non-Hispanic other race [3.9%], and 481 non-Hispanic White patients [69.1%]). The post-consolidation cohort (median follow-up, 7.5 years [IQR, 5.8-9.4 years]) included 935 patients (567 males [60.6%]; 87 Hispanic patients [9.3%], 145 non-Hispanic Black patients [15.5%], 41 patients of non-Hispanic other race [4.4%], and 662 non-Hispanic White patients [70.8%]). In multivariable Cox proportional hazards regression models, Hispanic children experienced significantly inferior OS (hazard ratio [HR], 1.78; 95% CI, 1.25-2.53; P = .01) on induction/consolidation studies compared with non-Hispanic White children; EFS did not differ. Non-Hispanic Black (HR, 1.54; 95% CI, 1.13-2.11) and Hispanic children (HR, 1.63; 95% CI, 1.09-2.43) experienced inferior OS on post-consolidation studies compared with non-Hispanic White children (P = .009); Hispanic children in post-consolidation studies experienced inferior EFS (HR, 1.68; 95% CI, 1.14-2.47; P = .02). Death as first event and postrelapse OS also differed by race and ethnicity.Conclusions and relevanceThis study suggests that Black and Hispanic children with high-risk neuroblastoma experienced inferior OS despite uniform planned treatment on frontline COG clinical trials. Investigated mechanisms did not completely explain survival disparities. Future evaluation of disparate treatment-related toxicities and postrelapse care as explanatory mechanisms are key next steps to promote equity.

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.

Dataset Information

Prospective Evaluation of Radiation Dose Escalation in Patients With High-Risk Neuroblastoma and Gross Residual Disease After Surgery: A Report From the Children's Oncology Group ANBL0532 Study.

Purpose

Patients and methods

Results

Conclusion

Publications

Prospective Evaluation of Radiation Dose Escalation in Patients With High-Risk Neuroblastoma and Gross Residual Disease After Surgery: A Report From the Children's Oncology Group ANBL0532 Study.

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