Expression data from pediatric AML patients
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Brian Balgobind
PROVIDER: E-GEOD-17855 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
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.
2010-10-21 | GSE17855 | GEO
Project description:In high income countries 90% of the patients achieve complete remission after induction chemotherapy. However, 30-40% of these patients suffer from relapse. These patients face a dismal prognosis, as the majority (>60%) of relapsed patients die within 5 years. As a result, outcome for pediatric acute myeloid leukemia (AML) patients remains poor and has stabilized over the past 15 years. To prevent or better treat relapse of AML is the best option to improve outcome. Despite patient specific differences, most patients do respond to initial therapy. This suggests that at relapse, mechanisms are active that cause the altered response to chemotherapy. Detailed understanding of mechanisms that cause relapse remain largely elusive. To gain insight in the molecular pathways that characterize relapsed AML, we performed genome wide gene expression profiling on paired initial diagnosis and relapsed AML samples of 23 pediatric AML patients. We used pathway analysis to find which molecular pathways are involved in altered gene expression between diagnosis and relapse samples of individual AML patients. 23 paired diagnosis and relapse bone marrow or peripheral blood samples were collected and cryo-preserved. They were later thawed and processed for hybridization to Affymetrix U133 Plus 2.0 arrays.
2015-05-07 | E-GEOD-52891 | biostudies-arrayexpress
Project description:High VEGFC mRNA expression of AML blasts is related to increased in vitro and in vivo drug resistance. The prognostic significance of VEGFC on long-term outcome and its associated gene expression profiles remain to be defined. We studied the effect of VEGFC on treatment outcome and investigated gene expression profiles associated with VEGFC using microarray data of 525 adult and 100 pediatric AML patients. High VEGFC expression appeared strongly associated with reduced complete remission rate, reduced overall and event-free survival (OS and EFS) in adult AML. Multivariable analysis established high VEGFC as prognostic indicator independent of cytogenetic risk, FLT3-ITD, NPM1, CEBPA, age and WBC. Also in pediatric AML high VEGFC was related to reduced OS. A unique series of differentially expressed genes was identified that distinguished AML with high VEGFC from AML with low VEGFC, i.e., 331 upregulated genes (representative of proliferation, VEGF-receptor activity, signal transduction) and 44 downregulated genes (e.g. related to apoptosis) consistent with a role in enhanced chemoresistance. In conclusion, high VEGFC predicts adverse long-term prognosis and provides prognostic information in addition to well-known prognostic factors. 98 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.
2010-06-09 | E-GEOD-22056 | 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:Acute Myeloid Leukemia (AML) is a heterogeneous disease with several recurrent cytogenetic abnormalities. Despite genomics and transcriptomics profiling efforts to understand AML’s heterogeneity, studies focused on the proteomic profiles associated with pediatric AML cytogenetic features remain limited. Furthermore, the majority of biological functions within cells are operated by proteins (i.e., enzymes) and most drugs target the proteome rather than the genome or transcriptome, thus, highlighting the significance of studying proteomics.
2023-09-26 | PXD043982 | Pride
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:Extensive molecular and prognostic characterization of wild-type MLL infant ALL. Background: Approximately 20% of all infant ALL cases carry wild-type (or germline) MLL genes. To date, wild-type MLL infant ALL patients are generally regarded as young pediatric precursor B-ALL patients, but extensive characterization of this specific patient group largely remains unacknowledged. Methods: We here studied a relatively large cohort of 78 wild-type MLL infant ALL samples, using clinical parameters, array-comparative genomic hybridization analysis, gene expression profiling, multiplex ligation-dependent probe amplification, and conventional sequencing. Findings: Wild-type MLL infant ALL patients are generally characterized by a lower incidence of favourable prognostic factors than pediatric (non-infant) B-ALL patients, and patients at high risk of therapy failure typically display an immature pro-B immunophenotype or respond poorly to prednisone. Using gene expression profiling, we found MEIS1 expression to additionally be highly predictive for clinical outcome in wild-type MLL infant ALL with a favourable prognosis in the wild-type MLL infants with low MEIS1 expression (DFS 88%% versus 50%, p=0•01). Overall the incidence of DNA copy number variations and genetic abnormalities in genes involved in B-cell differentiation is lower in wild-type MLL infant ALL patients as compared with pediatric precursor B-ALL patients. Interpretation: Wild-type MLL infant ALL represents a highly heterogeneous patient group, which cannot be unified by one or a few known recurrent genomic aberrations. High-level MEIS1 expression and an immature pro-B immunophenotype in high-risk wild-type MLL infant ALL patients shows parallel with the unfavourable prognosis of MLL-rearranged infant ALL patients. In contrast, wild-type MLL infant ALL patients expressing lower levels of MEIS1 and displaying more differentiated (pre-B or common) phenotypes may well be more related to pediatric precursor B-ALL patients older than 1 year of age. We advocate that a treatment strategy in wild-type MLL infant ALL based on MEIS1 expression could be beneficial for improving survival. Gene expression profiling of wild-type MLL infant ALL. Additional wild-type MLL infant ALL patient samples (n=17) to the earlier samples published under GSE19475 (GSM485309 to GSM485322).
2014-10-01 | E-GEOD-58565 | biostudies-arrayexpress
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