Expression data from pediatric AML patients
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE17855 | GEO | 2010/10/21
SECONDARY ACCESSION(S): PRJNA120095
REPOSITORIES: GEO
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Project description:Pediatric acute myeloid leukemia (AML) is a heterogeneous disease characterized by non-random genetic aberrations related to outcome. Detecting these aberrations however still lead to failures or false negative results. Therefore, we focused on the potential of gene expression profiles (GEP) to classify pediatric AML. Gene expression microarray data of 237 children with AML were generated and cases were split into a discovery cohort (n=157) and an independent validation cohort (n=80). Next, a double-loop cross validation approach was used to generate a subtype-predictive GEP in the discovery cohort which was then tested for its true predictive value in the independent validation cohort. 237 bone marrow and peripheral blood samples were collected at diagnosis and frozen. They were later thawed and hybridized to Affymetrix U133 Plus 2.0 arrays.
2010-10-21 | E-GEOD-17855 | biostudies-arrayexpress
Project description:Many researchers have reported the prognostic significance of various DNA methylation changes in patients with acute myeloid leukemia (AML). We aimed for a comprehensive evaluation of these epigenetic aberrations that would refine the AML prognostication. We designed a sequencing panel targeting 239 regions described in literature as having a prognostic impact or being commonly associated with AML pathogenesis and analyzed 178 diagnostic samples of AML patients divided into test (n=128) and validation cohort (n=50).
2021-01-26 | GSE165435 | GEO
Project description:A previously predictive CEBPA double mutant (CEBPAdm) signature was hampered by the recently reported CEBPA silenced AML cases that carry a similar gene expression profile (GEP). Two independent AML cohorts were used to train and evaluate the predictive value of the CEBPAdm signature in terms of sensitivity and specificity. A predictive signature was created, containing 25-probe sets by using a logistic regression model with Lasso regularization, which selects discriminative probe sets between the classes, CEBPAdm and all other AML cases, CEBPA wild type (CEBPAwt) and CEBPA single mutant (CEBPAsm). Subsequently, a classifier was trained on the entire HOVON-SAKK cohort based on a two-class approach; CEBPAdm versus all other cases (CEBPAwt and CEBPAsm). This trained classifier subsequently classified 16 candidate CEBPAdm cases in the AMLSG-cohort out of 154 AML cases. This approach showed perfect sensitivity and specificity (both 100%). In addition, we have performed a classification between CEBPAdm ,CEBPAsm, and CEBPAwt to infer if we were able to accurately classify CEBPAsm cases. We observed that all CEBPAsm cases were classified as CEBPAwt, thus CEBPAsm cases do not have a consistent gene expression pattern and are different from the CEBPAdm group.
2011-08-04 | GSE22845 | GEO
Project description:A previously predictive CEBPA double mutant (CEBPAdm) signature was hampered by the recently reported CEBPA silenced AML cases that carry a similar gene expression profile (GEP). Two independent AML cohorts were used to train and evaluate the predictive value of the CEBPAdm signature in terms of sensitivity and specificity. A predictive signature was created, containing 25-probe sets by using a logistic regression model with Lasso regularization, which selects discriminative probe sets between the classes, CEBPAdm and all other AML cases, CEBPA wild type (CEBPAwt) and CEBPA single mutant (CEBPAsm). Subsequently, a classifier was trained on the entire HOVON-SAKK cohort based on a two-class approach; CEBPAdm versus all other cases (CEBPAwt and CEBPAsm). This trained classifier subsequently classified 16 candidate CEBPAdm cases in the AMLSG-cohort out of 154 AML cases. This approach showed perfect sensitivity and specificity (both 100%). In addition, we have performed a classification between CEBPAdm ,CEBPAsm, and CEBPAwt to infer if we were able to accurately classify CEBPAsm cases. We observed that all CEBPAsm cases were classified as CEBPAwt, thus CEBPAsm cases do not have a consistent gene expression pattern and are different from the CEBPAdm group. All samples were obtained from untreated patients at the time of diagnosis. Cells used for microarray analysis were collected from the purified fraction of mononuclear cells after Ficoll density centrifugation. Routine diagnostic algorithms, including the characterization of molecular markers are performed.
2011-08-03 | E-GEOD-22845 | biostudies-arrayexpress
Project description:We performed genome wide miRNA expression analysis to investigate the ability of miRNAs in predicting leukemia relapse from 33 t(8;21) pediatric AMLs at diagnosis divided into a training and a validation cohort. COX regression analysis and ROC curves were used to identify a powerful miRNA signature able to predict relapse in t(8;21) AML patients. miRNA profiling showed that patients with high- or low- risk of relapse had different expression profiles. We support the role of microRNAs in modulating the prognosis of t(8;21)-AML and the use of a miRNA expression signature at diagnosis to better define standard risk cases in pediatric AML.
2017-09-14 | GSE97135 | GEO
Project description:We hypothesized that DNA methylation distributes into specific patterns in cancer cells, which reflect critical biological differences. We therefore examined the methylation profiles of 344 patients with acute myeloid leukemia (AML). Clustering of these patients by methylation data segregated patients into 16 groups. Five of these groups defined new AML subtypes that shared no other known feature. In addition, DNA methylation profiles segregated patients with CEBPA aberrations from other subtypes of leukemia, defined four epigenetically distinct forms of AML with NPM1 mutations, and showed that established AML1-ETO, CBFb-MYH11 and PML-RARA leukemia entities are associated with specific methylation profiles. We report a 15-gene methylation classifier predictive of overall survival in an independent patient cohort (p<0.001, adjusted for known covariates). Keywords: DNA methylation profiling DNA methylation profiling of a cohort of 344 AML patients from Erasmus Medical Center and enrolled in clinical trials from the Dutch-German cooperative group HOVON. Additionally, a control group consisting of 8 CD34+ bone marrow samples from healthy donors was also studied.
2010-01-12 | E-GEOD-18700 | biostudies-arrayexpress
Project description:Pediatric acute myeloid leukemia (AML) is a heterogeneous disease with respect to biology as well as outcome. In this study, we investigated whether known biological subgroups of pediatric AML are reflected by a common microRNA (miRNA) expression pattern. We assayed 665 miRNAs in 165 pediatric AML samples. First, unsupervised clustering was performed to identify patient clusters with common miRNA expression profiles. Our analysis unraveled 14 clusters, seven of which had a known (cyto-)genetic denominator. Finally, a robust classifier was constructed to discriminate six known molecular aberration groups: 11q23-rearrangements, t(8;21)(q22;q22), inv(16)(p13q22), t(15;17)(q21;q22), NPM1 and CEBPA mutations. The classifier achieved accuracies of 89%, 95%, 95%, 98%, 91% and 96%, respectively. Although lower sensitivities were obtained for the NPM1 and CEBPA (32% and 66%), relatively high sensitivities (84%-94%) were attained for the rest. Specificity was high in all groups (87%-100%). Due to a robust double-loop cross validation procedure we employed, the classifier only used expression of 47 miRNAs to generate the aforementioned accuracies. To validate the 47 miRNA signatures, we applied them to a publicly available adult AML dataset. Despite partial overlap of miRNA platforms and known molecular differences between pediatric and adult AML, the signatures performed reasonably well. This corroborates our claim that the reported miRNA signatures are not dominated by sample size bias in the pediatric AML dataset. We conclude that cytogenetic subtypes of pediatric AML have distinct miRNA expression patterns. Note that, reproducibility of the miRNA signatures in adult dataset suggests that the respective aberrations have a similar biology both in pediatric and adult AML
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2022-09-30 | PXD031004 | Pride
Project description:The pathogenesis of multiple sclerosis (MS) remains to be elucidated. Pediatric-onset MS (POMS) represents the earliest stage of the disease. CSF proteins in POMS may therefore provide causal information. Therefore, the aim of the current study was to analyze CSF proteins in children with an initial CNS acquired demyelinating syndrome (ADS) and to make a comparison between POMS and monophasic ADS (mADS). Patients were selected from two prospective pediatric ADS studies. Liquid chromatography-mass spectrometry was performed in a Dutch discovery cohort (POMS n=28; mADS n=39). Parallel reaction monitoring-mass spectrometry was performed on selected proteins more abundant in POMS with ≥ 8 unique peptides in a combined Dutch and Canadian validation cohort (POMS n=48; mADS n=106).
2022-09-30 | PXD031022 | Pride
Project description:Thalidomide-dexamethasone (TD) combination is an effective induction therapy for newly diagnosed multiple myeloma patients, candidates for subsequent autologous stem cell transplantation (ASCT). Since maximization of tumor response before ASCT may favorably affect the clinical outcomes, we designed a study to identify a gene expression profile (GEP) signature predictive of attainment of complete response to TD induction therapy. CD138+ bone marrow samples obtained at diagnosis from 112/311 patients were analyzed. Two subsequent time phases were planned. Firstly, a GEP supervised analysis, performed on a training set of 32 patients, allowed to identify 157 probe sets differentially expressed in complete responder + near complete responder (CR+nCR) versus ≤partial responder patients. Than, we generated an 8-gene GEP signature predicting at diagnosis the probability to achieve CR+nCR to TD induction therapy. The performance of this assay was subsequently validated in an 80 patients training set. The 8-gene signature provide a negative predictive value of 93% and a positive predictive value of 44%. The 8 genes were down-regulated in patients who achieved at least a nCR. These results could be an important first step to adopting a diagnostic assay, used to determine, at diagnosis, patients who will respond more favourably to a particular treatment strategy.
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