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: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:Purpose: In 2010, a Children's Oncology Group (COG) phase III randomized trial for patients with high-risk neuroblastoma (ANBL0032) demonstrated improved event-free survival (EFS) and overall survival (OS) following treatment with an immunotherapy regimen of dinutuximab, GM-CSF, IL2, and isotretinoin compared with treatment with isotretinoin alone. Dinutuximab, a chimeric anti-GD2 monoclonal antibody, acts in part via natural killer (NK) cells. Killer immunoglobulin-like receptors (KIR) on NK cells and their interactions with KIR-ligands can influence NK cell function. We investigated whether KIR/KIR-ligand genotypes were associated with EFS or OS in this trial.Experimental Design: We genotyped patients from COG study ANBL0032 and evaluated the effect of KIR/KIR-ligand genotypes on clinical outcomes. Cox regression models and log-rank tests were used to evaluate associations of EFS and OS with KIR/KIR-ligand genotypes.Results: In this trial, patients with the "all KIR-ligands present" genotype as well as patients with inhibitory KIR2DL2 with its ligand (HLA-C1) together with inhibitory KIR3DL1 with its ligand (HLA-Bw4) were associated with improved outcome if they received immunotherapy. In contrast, for patients with the complementary KIR/KIR-ligand genotypes, clinical outcome was not significantly different for patients who received immunotherapy versus those receiving isotretinoin alone.Conclusions: These data show that administration of immunotherapy is associated with improved outcome for neuroblastoma patients with certain KIR/KIR-ligand genotypes, although this was not seen for patients with other KIR/KIR-ligand genotypes. Further investigation of KIR/KIR-ligand genotypes may clarify their role in cancer immunotherapy and may enable KIR/KIR-ligand genotyping to be used prospectively for identifying patients likely to benefit from certain cancer immunotherapy regimens. Clin Cancer Res; 24(1); 189-96. ©2017 AACRSee related commentary by Cheung and Hsu, p. 3.

Project description:BACKGROUND:Early-phase trials in patients with recurrent neuroblastoma historically used an objective "response" of measureable disease (Response Evaluation Criteria In Solid Tumors [RECIST], without bone/bone marrow assessment) to select agents for further study. Historical cohorts may be small and potentially biased; to the authors' knowledge, disease recurrence studies from international registries are outdated. Using a large recent cohort of patients with recurrent/refractory neuroblastoma from Children's Oncology Group (COG) modern-era early-phase trials, the authors determined outcome and quantified parameters for designing future studies. METHODS:The first early-phase COG trial enrollment (sequential) of 383 distinct patients with recurrent/refractory neuroblastoma on 23 phase 1, 3 phase 1/2, and 9 phase 2 trials (August 2002 to January 2014) was analyzed for progression-free survival (PFS), overall survival (OS), and time to disease progression (TTP). Planned frontline therapy for patients with high-risk neuroblastoma included hematopoietic stem cell transplantation (approximately two-thirds of patients underwent ?1 hematopoietic stem cell transplantation); 13.2% of patients received dinutuximab. RESULTS:From the time of the patient's first early-phase trial enrollment (383 patients), the 1-year and 4-year PFS rates (?±?standard error) were 21%?±?2% and 6%?±?1%, respectively, whereas the 1-year and 4-year OS rates were 57%?±?3% and 20%?±?2%, respectively. The median TTP was 58 days (interquartile range, 31-183 days [350 patients]); the median follow-up was 25.3 months (33 patients were found to be without disease recurrence/progression). The median time from diagnosis to first disease recurrence/progression was 18.7 months (range, 1.4-64.8 months) (176 patients). MYCN amplification and 11q loss of heterozygosity were prognostic of worse PFS and OS (P?=?.003 and P<.0001, respectively, and P?=?.02 and P?=?.03, respectively) after early-phase trial enrollment. CONCLUSIONS:This recent COG cohort of patients with recurrent/refractory neuroblastoma is inclusive and representative. To the authors' knowledge, the current study is the first meta-analysis of PFS, TTP, and OS within the context of modern therapy. These results will inform the design of future phase 2 studies by providing a) historical context during the search for more effective agents; and, b) factors prognostic of PFS and OS after disease recurrence to stratify randomization. Cancer 2017;123:4914-23. © 2017 American Cancer Society.

Dataset Information

Poverty and Targeted Immunotherapy: Survival in Children's Oncology Group Clinical Trials for High-Risk Neuroblastoma.

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