DNA methylation adds prognostic value to minimal residual disease status in pediatric T-cell acute lymphoblastic leukemia
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ORGANISM(S): Homo sapiens
PROVIDER: GSE69954 | GEO | 2016/03/30
SECONDARY ACCESSION(S): PRJNA287282
REPOSITORIES: GEO
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Project description:Background: Despite increased knowledge about genetic aberrations in pediatric T-cell acute lymphoblastic leukemia (T-ALL), no clinically feasible treatment-stratifying marker exists at diagnosis. Instead patients are enrolled in intensive induction therapies with substantial side effects. In modern protocols, therapy response is monitored by minimal residual disease (MRD) analysis, and used for post-induction risk group stratification. DNA methylation profiling is a candidate for subtype discrimination at diagnosis and we investigated its role as a prognostic marker in pediatric T-ALL. Procedure: Sixty-five diagnostic T-ALL samples from Nordic pediatric patients treated according to the NOPHO-ALL2008 protocol were analyzed by HumMeth450K genome wide DNA methylation arrays. Methylation status was analyzed in relation to clinical data and early T-cell precursor (ETP) phenotype. Results: Two distinct CpG Island Methylator Phenotype (CIMP) groups were identified. Patients with a CIMP negative profile had an inferior response to treatment compared to CIMP positive patients (3-year cumulative incidence of relapse (CIR3y) rate: 29% vs. 6%, p=0.01). Most importantly, CIMP classification at diagnosis allowed subgrouping of high risk T-ALL patients (MRD â?¥0.1% at day 29) into two groups with significant differences in outcome (CIR3y rates: CIMP negative 50% vs CIMP positive 12%; p=0.02). These groups did not differ regarding ETP-phenotype, but the CIMP negative group was younger (p=0.02) and had higher white blood cell count at diagnosis (p=0.004) compared with the CIMP positive group. Conclusions: CIMP classification at diagnosis in combination with MRD during induction therapy is a strong candidate for further risk classification and could confer important information in treatment decision-making. Bisulphite converted DNA from T-ALL samples were hybridised to the Illumina Infinium 450k Human Methylation Beadchip
2016-03-30 | E-GEOD-69954 | biostudies-arrayexpress
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
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:The outcome of patients with anaplastic gliomas varies considerably depending on histology and single molecular markers such as codeletion of 1p/19q and mutations of the isocitrate dehydrogenase (IDH) gene. Whether a molecularly-based classification of anaplastic gliomas based on large scale genomic or epigenomic analyses is superior to histopathology, may reflect distinct biological subtypes, predict outcome and guide therapy decisions had yet to be determined. Epigenome-wide DNA methylation analysis, which also allows for the detection of copy-number aberrations, was performed in a cohort of 228 patients with anaplastic gliomas (astrocytomas, oligoastrocytomas and oligodendrogliomas), including 115 patients of the NOA-04 trial. We further compared these tumors with a group of 55 glioblastomas. Unsupervised clustering demonstrated two main groups based on IDH mutation status: CpG island methylator phenotype (CIMP) positive (77.5%) or negative (22.5%). CIMP+ (IDH mutant) tumors showed a further separation based on copy-number status of chromosome arms 1p and 19q, but not based on histopathology. CIMP- (IDH wild type) tumors on the other hand showed hallmark copy-number alterations of glioblastomas. These tumors clustered together with CIMP- glioblastomas without forming separate groups based on WHO grade. There was no Tumor classification based on CIMP and 1p/19q status was significantly associated with survival allowing a better prediction of outcome than the current histopathological classification alone: Patients with CIMP+ tumors with 1p/19q codeletion had the best prognosis, followed by patients with CIMP+ but intact 1p/19q status. Patients with CIMP- anaplastic gliomas had the worst prognosis. Collectively, our data suggest that anaplastic gliomas can be grouped into three molecular subtypes with clear association to underlying biology and clinical outcome based on IDH and 1p/19q status. The data do not provide a molecular basis for the diagnosis of anaplastic oligoastrocytoma. We investigated a subset of 228 anaplastic gliomas using the Illumina 450k methylation array.
2014-06-06 | E-GEOD-58218 | biostudies-arrayexpress
Project description:The outcome of patients with anaplastic gliomas varies considerably depending on histology and single molecular markers such as codeletion of 1p/19q and mutations of the isocitrate dehydrogenase (IDH) gene. Whether a molecularly-based classification of anaplastic gliomas based on large scale genomic or epigenomic analyses is superior to histopathology, may reflect distinct biological subtypes, predict outcome and guide therapy decisions had yet to be determined. Epigenome-wide DNA methylation analysis, which also allows for the detection of copy-number aberrations, was performed in a cohort of 228 patients with anaplastic gliomas (astrocytomas, oligoastrocytomas and oligodendrogliomas), including 115 patients of the NOA-04 trial. We further compared these tumors with a group of 55 glioblastomas. Unsupervised clustering demonstrated two main groups based on IDH mutation status: CpG island methylator phenotype (CIMP) positive (77.5%) or negative (22.5%). CIMP+ (IDH mutant) tumors showed a further separation based on copy-number status of chromosome arms 1p and 19q, but not based on histopathology. CIMP- (IDH wild type) tumors on the other hand showed hallmark copy-number alterations of glioblastomas. These tumors clustered together with CIMP- glioblastomas without forming separate groups based on WHO grade. There was no Tumor classification based on CIMP and 1p/19q status was significantly associated with survival allowing a better prediction of outcome than the current histopathological classification alone: Patients with CIMP+ tumors with 1p/19q codeletion had the best prognosis, followed by patients with CIMP+ but intact 1p/19q status. Patients with CIMP- anaplastic gliomas had the worst prognosis. Collectively, our data suggest that anaplastic gliomas can be grouped into three molecular subtypes with clear association to underlying biology and clinical outcome based on IDH and 1p/19q status. The data do not provide a molecular basis for the diagnosis of anaplastic oligoastrocytoma.
2014-06-06 | GSE58218 | GEO
Project description:In short: The objective with the gene expression array (Illumina HT-12 v.4) analysis of 17 T-ALL samples was to correlate gene expression levels with DNA promoter methylation status. Manuscript Abstract: Background: Treatment of pediatric T-cell acute lymphoblastic leukemia (T-ALL) has improved, but there is a considerable fraction of patients experiencing a poor outcome. There is a need for better prognostic markers and aberrant DNA methylation is a candidate in other malignancies, but its potential prognostic significance in T-ALL is hitherto undecided. Design and Methods: Genome wide promoter DNA methylation analysis was performed in pediatric T-ALL samples (n=43) using arrays covering >27000 CpG sites. Clinical outcome was evaluated in relation to methylation status and compared with a contemporary T-ALL group not tested for methylation (n= 32). Results: Based on CpG island methylator phenotype (CIMP), T-ALL samples were subgrouped as CIMP+ (high methylation) and CIMP- (low methylation). CIMP- T-ALL patients had significantly worse overall and event free survival (p=0.02 and p=0.001, respectively) compared to CIMP+ cases. CIMP status was an independent factor for survival in multivariate analysis including age, gender and white blood cell count. Analysis of differently methylated genes in the CIMP subgroups showed an overrepresentation of transcription factors, ligands and polycomb target genes. Conclusions: We identified global promoter methylation profiling as being of relevance for subgrouping and prognostication of pediatric T-ALL. RNA was extracted with TRIZOL according to manufacturer instructions. Total RNA was amplified bu the Illumina TotalPrep RNA Amplification kit. Gene expression array analysis was performed on the 17/43 pediatric T-ALL samples from which RNA was availible. 2 control samples of stimulted T-cells were included and one replicate.
2013-07-01 | E-GEOD-41621 | biostudies-arrayexpress
Project description:In short: Genome wide promoter DNA methylation profiling of 43 T-ALL samples and 5 T-cell controls (normal bone marrow and stimulated T-cells) . The Illumina Infinium 27k Human DNA methylation Beadchip v1.2 was used to obtain DNA methylation profiles across approximately 27,000 CpGs. Manuscript abstract: Background: Treatment of pediatric T-cell acute lymphoblastic leukemia (T-ALL) has improved, but there is a considerable fraction of patients experiencing a poor outcome. There is a need for better prognostic markers and aberrant DNA methylation is a candidate in other malignancies, but its potential prognostic significance in T-ALL is hitherto undecided. Design and Methods: Genome wide promoter DNA methylation analysis was performed in pediatric T-ALL samples (n=43) using arrays covering >27000 CpG sites. Clinical outcome was evaluated in relation to methylation status and compared with a contemporary T-ALL group not tested for methylation (n= 32). Results: Based on CpG island methylator phenotype (CIMP), T-ALL samples were subgrouped as CIMP+ (high methylation) and CIMP- (low methylation). CIMP- T-ALL patients had significantly worse overall and event free survival (p=0.02 and p=0.001, respectively) compared to CIMP+ cases. CIMP status was an independent factor for survival in multivariate analysis including age, gender and white blood cell count. Analysis of differently methylated genes in the CIMP subgroups showed an overrepresentation of transcription factors, ligands and polycomb target genes. Conclusions: We identified global promoter methylation profiling as being of relevance for subgrouping and prognostication of pediatric T-ALL. Bisulphite converted DNA from the 48 samples were hybridised to the Illumina Infinium 27k Human Methylation Beadchip v1.2
2013-07-01 | E-GEOD-42079 | biostudies-arrayexpress
Project description:In short: The objective with the gene expression array (Illumina HT-12 v.4) analysis of 17 T-ALL samples was to correlate gene expression levels with DNA promoter methylation status. Manuscript Abstract: Background: Treatment of pediatric T-cell acute lymphoblastic leukemia (T-ALL) has improved, but there is a considerable fraction of patients experiencing a poor outcome. There is a need for better prognostic markers and aberrant DNA methylation is a candidate in other malignancies, but its potential prognostic significance in T-ALL is hitherto undecided. Design and Methods: Genome wide promoter DNA methylation analysis was performed in pediatric T-ALL samples (n=43) using arrays covering >27000 CpG sites. Clinical outcome was evaluated in relation to methylation status and compared with a contemporary T-ALL group not tested for methylation (n= 32). Results: Based on CpG island methylator phenotype (CIMP), T-ALL samples were subgrouped as CIMP+ (high methylation) and CIMP- (low methylation). CIMP- T-ALL patients had significantly worse overall and event free survival (p=0.02 and p=0.001, respectively) compared to CIMP+ cases. CIMP status was an independent factor for survival in multivariate analysis including age, gender and white blood cell count. Analysis of differently methylated genes in the CIMP subgroups showed an overrepresentation of transcription factors, ligands and polycomb target genes. Conclusions: We identified global promoter methylation profiling as being of relevance for subgrouping and prognostication of pediatric T-ALL.
2013-07-01 | GSE41621 | GEO
Project description:In short: Genome wide promoter DNA methylation profiling of 43 T-ALL samples and 5 T-cell controls (normal bone marrow and stimulated T-cells) . The Illumina Infinium 27k Human DNA methylation Beadchip v1.2 was used to obtain DNA methylation profiles across approximately 27,000 CpGs. Manuscript abstract: Background: Treatment of pediatric T-cell acute lymphoblastic leukemia (T-ALL) has improved, but there is a considerable fraction of patients experiencing a poor outcome. There is a need for better prognostic markers and aberrant DNA methylation is a candidate in other malignancies, but its potential prognostic significance in T-ALL is hitherto undecided. Design and Methods: Genome wide promoter DNA methylation analysis was performed in pediatric T-ALL samples (n=43) using arrays covering >27000 CpG sites. Clinical outcome was evaluated in relation to methylation status and compared with a contemporary T-ALL group not tested for methylation (n= 32). Results: Based on CpG island methylator phenotype (CIMP), T-ALL samples were subgrouped as CIMP+ (high methylation) and CIMP- (low methylation). CIMP- T-ALL patients had significantly worse overall and event free survival (p=0.02 and p=0.001, respectively) compared to CIMP+ cases. CIMP status was an independent factor for survival in multivariate analysis including age, gender and white blood cell count. Analysis of differently methylated genes in the CIMP subgroups showed an overrepresentation of transcription factors, ligands and polycomb target genes. Conclusions: We identified global promoter methylation profiling as being of relevance for subgrouping and prognostication of pediatric T-ALL.
2013-07-01 | GSE42079 | GEO
Project description:Gene expression analyses, were performed on 121 consecutive childhood leukemias (87 B-lineage acute lymphoblastic leukemias (ALLs), 11 T-cell ALLs, and 23 acute myeloid leukemias; AMLs), investigated during an 8-year period at a single center. The supervised learning algorithm k-nearest neighbor (k-NN) was utilized to build gene expression predictors that could classify the ALLs/AMLs according to clinically important subtypes with high accuracy. Validation experiments in an independent data set verified the high prediction accuracies of our classifiers. B-lineage ALLs with uncharacteristic cytogenetic aberrations or with a normal karyotype displayed heterogeneous gene expression profiles, resulting in low prediction accuracies. Minimal residual disease status (MRD) in T-cell ALLs with a high (>0.1%) MRD at day 29 could be classified with 100% accuracy already at the time of diagnosis. In pediatric leukemias with uncharacteristic cytogenetic aberrations or a normal karyotype, unsupervised analysis identified two novel subgroups: one consisting mainly of cases remaining in complete remission (CR) and one containing a few patients in CR and all but one of the patients who relapsed. This study of a consecutive series of childhood leukemias confirm and further extend previous reports demonstrating that global gene expression profiling provides a valuable tool for genetic and clinical classification of childhood leukemias. Keywords: supervised classification, Pediatric leukemia, AML, B-ALL, T-ALL, Normal bone marrow
2007-04-15 | GSE7186 | GEO