A Pilot Study of Intensified PEG-Asparaginase in High-risk Acute Lymphoblastic Leukemia: Children's Oncology Group Study AALL08P1.
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SUBMITTER: Rodriguez V
PROVIDER: S-EPMC4955695 | biostudies-literature | 2016 Aug
REPOSITORIES: biostudies-literature
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A Pilot Study of Intensified PEG-Asparaginase in High-risk Acute Lymphoblastic Leukemia: Children's Oncology Group Study AALL08P1.
Rodriguez Vilmarie V Kairalla John J Salzer Wanda L WL Raetz Elizabeth A EA Loh Mignon Lc ML Carroll Andrew J AJ Heerema Nyla A NA Wood Brent L BL Borowitz Michael J MJ Burke Michael J MJ Asselin Barbara L BL Devidas Meenakshi M Winick Naomi J NJ Carroll William L WL Hunger Stephen P SP Dreyer ZoAnn E ZE
Journal of pediatric hematology/oncology 20160801 6
AALL08P1 was designed to determine whether biweekly intensified pegaspargase (I-PEG) was feasible and safe in pediatric patients with newly diagnosed high-risk B-precursor lymphoblastic leukemia when given with Children's Oncology Group hemiaugmented BFM therapy. High-risk average (HR-Avg) patients received standard pegaspargase dosing (6 doses), whereas high-risk high (HR-High) patients received I-PEG biweekly from the start of Consolidation until day 1 of Maintenance. Feasibility and safety we ...[more]
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Project description:Gene expression profiling was performed on 97 cases of infant ALL from Children's Oncology Group Trial P9407. Statistical modeling of an outcome predictor revealed 3 genes highly predictive of event-free survival (EFS), beyond age and MLL status: FLT3, IRX2, and TACC2. Low FLT3 expression was found in a group of infants with excellent outcome (n = 11; 5-year EFS of 100%), whereas differential expression of IRX2 and TACC2 partitioned the remaining infants into 2 groups with significantly different survivals (5-year EFS of 16% vs 64%; P < .001). When infants with MLL-AFF1 were analyzed separately, a 7-gene classifier was developed that split them into 2 distinct groups with significantly different outcomes (5-year EFS of 20% vs 65%; P < .001). In this classifier, elevated expression of NEGR1 was associated with better EFS, whereas IRX2, EPS8, and TPD52 expression were correlated with worse outcome. This classifier also predicted EFS in an independent infant ALL cohort from the Interfant-99 trial. When evaluating expression profiles as a continuous variable relative to patient age, we further identified striking differences in profiles in infants less than or equal to 90 days of age and those more than 90 days of age. These age-related patterns suggest different mechanisms of leukemogenesis and may underlie the differential outcomes historically seen in these age groups.
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| S-EPMC4239306 | biostudies-literature
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.
2009-06-25 | GSE11877 | GEO
Project description:Gene expression profiling was performed on 97 cases of infant ALL from Children's Oncology Group Trial P9407. Statistical modeling of an outcome predictor revealed 3 genes highly predictive of event-free survival (EFS), beyond age and MLL status: FLT3, IRX2, and TACC2. Low FLT3 expression was found in a group of infants with excellent outcome (n = 11; 5-year EFS of 100%), whereas differential expression of IRX2 and TACC2 partitioned the remaining infants into 2 groups with significantly different survivals (5-year EFS of 16% vs 64%; P < .001). When infants with MLL-AFF1 were analyzed separately, a 7-gene classifier was developed that split them into 2 distinct groups with significantly different outcomes (5-year EFS of 20% vs 65%; P < .001). In this classifier, elevated expression of NEGR1 was associated with better EFS, whereas IRX2, EPS8, and TPD52 expression were correlated with worse outcome. This classifier also predicted EFS in an independent infant ALL cohort from the Interfant-99 trial. When evaluating expression profiles as a continuous variable relative to patient age, we further identified striking differences in profiles in infants less than or equal to 90 days of age and those more than 90 days of age. These age-related patterns suggest different mechanisms of leukemogenesis and may underlie the differential outcomes historically seen in these age groups. EXP-520 Assay Type: Gene Expression Provider: Affymetrix Array Designs: HG-U133_Plus_2 Organism: Homo sapiens (ncbitax)
2015-05-12 | E-GEOD-68720 | biostudies-arrayexpress
Project description:Durable remissions in children with acute lymphoblastic leukemia (ALL) require a 2-year maintenance phase that includes daily oral 6-mercaptopurine (6MP). Adherence to oral 6MP among Asian-American and African-American children with ALL is unknown. We enrolled 298 children with ALL (71 Asian Americans, 68 African Americans, and 159 non-Hispanic whites) receiving oral 6MP for the maintenance phase. Adherence was measured electronically for 39 803 person-days. Adherence declined from 95.0% (month 1) to 91.8% (month 5, P < .0001). Adherence rates were significantly (P < .0001) lower in Asian Americans (90.0% ± 4.9%) and African Americans (87.1% ± 4.4%), as compared with non-Hispanic whites (95.2% ± 1.3%). Race-specific sociodemographic characteristics helped explain poor adherence (African Americans: low maternal education [less than a college degree: 78.9%, vs at least college degree: 94.6%; P < .0001]; Asian Americans: low-income households [<$50 000: 84.5%, vs ≥$50 000: 96.7%; P = .04]; households without mothers as full-time caregivers [85.6%] vs households with mothers as full-time caregivers [97.2%; P = .05]). Adherence rate below 90% was associated with increased relapse risk (hazard ratio, 3.9; P = .01). Using an adherence rate <90% to define nonadherence, 20.5% of the participants were nonadherers. We identify race-specific determinants of adherence, and define a clinically relevant level of adherence needed to minimize relapse risk in a multiracial cohort of children with ALL. This trial was registered at www.clinicaltrials.gov as #NCT00268528.
| S-EPMC4192748 | biostudies-literature
Project description:The association between individual-level poverty and relapse in children receiving maintenance treatment for acute lymphoblastic leukemia (ALL) remains unclear. In a secondary analysis of COG-AALL03N1, we used data from US Census Bureau to categorize patients living below year-specific federal poverty thresholds, calculated using self-reported annual household income and size of household. Participants with federal poverty thresholds above 120% of their yearly household income were categorized as living in extreme poverty. Hazard of relapse was estimated using multivariable proportional subdistributional hazards regression for patients living in extreme poverty while receiving ALL maintenance therapy after adjusting for relevant predictors. Among 592 patients in this analysis, 12.3% of the patients were living in extreme poverty. After a median follow-up of 7.9 years, the cumulative incidence of relapse at 3 years from study enrollment among those living in extreme poverty was significantly higher (14.3%) than those not living in extreme poverty (7.6%). Multivariable analysis demonstrated that children living in extreme poverty had a 1.95-fold greater hazard of relapse than those not living in extreme poverty; this association was mitigated after the inclusion of race/ethnicity in the model, likely because of collinearity between race/ethnicity and poverty. A greater proportion of children living in extreme poverty were nonadherent to mercaptopurine (57.1% vs 40.9%); however, poor adherence did not completely explain the association between poverty and relapse risk. Future studies need to understand the mechanisms underlying the association between extreme poverty and relapse risk. This trial was registered at www.clinicaltrials.gov as #NCT00268528.
| S-EPMC10375268 | biostudies-literature
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.
2009-06-25 | E-GEOD-11877 | biostudies-arrayexpress