Project description:BackgroundAnthracycline-related cardiomyopathy is a leading cause of late morbidity in childhood cancer survivors. Glutathione S-transferases (GSTs) are a class of phase II detoxification enzymes that facilitate the elimination of anthracyclines. As free-radical scavengers, GSTs could play a role in oxidative damage-induced cardiomyopathy. Associations between the GSTμ1 (GSTM1) null genotype and iron-overload-related cardiomyopathy have been reported in patients with thalassemia.MethodsThe authors sought to identify an association between the GSTM1 null genotype and anthracycline-related cardiomyopathy in childhood cancer survivors and to corroborate the association by examining GSTM1 gene expression in peripheral blood and human-induced pluripotent stem cell cardiomyocytes (hiPSC-CMs) from survivors with and without cardiomyopathy. GSTM1 gene deletion was examined by polymerase chain reaction in 75 survivors who had clinically validated cardiomyopathy (cases) and in 92 matched survivors without cardiomyopathy (controls). Conditional logistic regression analysis adjusting for sex, age at cancer diagnosis, chest radiation, and anthracycline dose was used to assess the association between genotype and cardiomyopathy. Proprietary bead array technology and quantitative real-time polymerase chain reaction were used to measure GSTM1 expression levels in samples from 20 cases and 20 matched controls. hiPSC-CMs from childhood cancer survivors (3 with cardiomyopathy, 3 without cardiomyopathy) also were examined for GSTM1 gene expression levels.ResultsA significant association was observed between the risk of cardiomyopathy and the GSTM1 null genotype (odds ratio, 2.7; 95% CI, 1.3-5.9; P = .007). There was significant downregulation of GSTM1 expression in cases compared with controls (average relative expression, 0.67 ± 0.57 vs 1.33 ± 1.33, respectively; P = .049). hiPSC-CMs from patients who had cardiomyopathy revealed reduced GSTM1 expression (P = .007).ConclusionsThe current findings could facilitate the identification of childhood cancer survivors who are at risk for anthracycline-related cardiomyopathy.

Project description:PurposeCarbonyl reductases (CBRs) catalyze reduction of anthracyclines to cardiotoxic alcohol metabolites. Polymorphisms in CBR1 and CBR3 influence synthesis of these metabolites. We examined whether single nucleotide polymorphisms in CBR1 (CBR1 1096G>A) and/or CBR3 (CBR3 V244M) modified the dose-dependent risk of anthracycline-related cardiomyopathy in childhood cancer survivors.Patients and methodsOne hundred seventy survivors with cardiomyopathy (patient cases) were compared with 317 survivors with no cardiomyopathy (controls; matched on cancer diagnosis, year of diagnosis, length of follow-up, and race/ethnicity) using conditional logistic regression techniques.ResultsA dose-dependent association was observed between cumulative anthracycline exposure and cardiomyopathy risk (0 mg/m(2): reference; 1 to 100 mg/m(2): odds ratio [OR], 1.65; 101 to 150 mg/m(2): OR, 3.85; 151 to 200 mg/m(2): OR, 3.69; 201 to 250 mg/m(2): OR, 7.23; 251 to 300 mg/m(2): OR, 23.47; > 300 mg/m(2): OR, 27.59; P(trend) < .001). Among individuals carrying the variant A allele (CBR1:GA/AA and/or CBR3:GA/AA), exposure to low- to moderate-dose anthracyclines (1 to 250 mg/m(2)) did not increase the risk of cardiomyopathy. Among individuals with CBR3 V244M homozygous G genotypes (CBR3:GG), exposure to low- to moderate-dose anthracyclines increased cardiomyopathy risk when compared with individuals with CBR3:GA/AA genotypes unexposed to anthracyclines (OR, 5.48; P = .003), as well as exposed to low- to moderate-dose anthracyclines (OR, 3.30; P = .006). High-dose anthracyclines (> 250 mg/m(2)) were associated with increased cardiomyopathy risk, irrespective of CBR genotype status.ConclusionThis study demonstrates increased anthracycline-related cardiomyopathy risk at doses as low as 101 to 150 mg/m(2). Homozygosis for G allele in CBR3 contributes to increased cardiomyopathy risk associated with low- to moderate-dose anthracyclines, such that there seems to be no safe dose for patients homozygous for the CBR3 V244M G allele. These results suggest a need for targeted intervention for those at increased risk of cardiomyopathy.

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.

Dataset Information

CELF4 Variant and Anthracycline-Related Cardiomyopathy: A Children's Oncology Group Genome-Wide Association Study.

Publications

CELF4 Variant and Anthracycline-Related Cardiomyopathy: A Children's Oncology Group Genome-Wide Association Study.

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