Routine use of microarray-based gene expression profiling to identify patients with low cytogenetic risk acute myeloid leukemia: accurate results can be obtained even with suboptimal samples
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ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Philippe Guardiola
PROVIDER: E-GEOD-34823 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Background: Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified. Methods: Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n=101) and/or poor quality control criteria (n=10) (test set). Results: With 10-marker classifiers, all training set samples as well as 97 of the 101 test samples with a low blast load, and all 10 samples with poor quality control criteria were correctly classified. Regarding test set samples, the overall error rate of the class prediction was below 4 percent, even though the leukemic blast load was as low as 2%. Sensitivity, specificity, negative and positive predictive values of the class assignments ranged from 91% to 100%. Of note, for acute promyelocytic leukemia and leukemias with t(8;21) or inv(16), the confidence level of the class assignment was influenced by the leukemic blast load. Conclusion: Gene expression profiling and a supervised method requiring 10-marker classifiers enable the identification of favorable cytogenetic risk acute myeloid leukemia even when samples contain low leukemic blast loads or display poor quality control criterion. Training set.
2011-12-21 | E-GEOD-34577 | biostudies-arrayexpress
Project description:Background: Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified. Methods: Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n=101) and/or poor quality control criteria (n=10) (test set). Results: With 10-marker classifiers, all training set samples as well as 97 of the 101 test samples with a low blast load, and all 10 samples with poor quality control criteria were correctly classified. Regarding test set samples, the overall error rate of the class prediction was below 4 percent, even though the leukemic blast load was as low as 2%. Sensitivity, specificity, negative and positive predictive values of the class assignments ranged from 91% to 100%. Of note, for acute promyelocytic leukemia and leukemias with t(8;21) or inv(16), the confidence level of the class assignment was influenced by the leukemic blast load. Conclusion: Gene expression profiling and a supervised method requiring 10-marker classifiers enable the identification of favorable cytogenetic risk acute myeloid leukemia even when samples contain low leukemic blast loads or display poor quality control criterion. Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n=101) and/or poor quality control criteria (n=10) (test set).
2011-12-24 | E-GEOD-34714 | biostudies-arrayexpress
Project description:Effect of expression of dipeptidyl peptidase-IV (DPP-IV) in U373 cell line on uncontrolled cell proliferation and aberrant interactions with the brain extracellular matrix.
2011-12-31 | E-MTAB-583 | biostudies-arrayexpress
Project description:The aim of this study was to identify EZH2 targets in myeloid malignancies. RNA samples from control F-36P, MOLM-13 and OCI-M2 cells (secondary AML after MDS; EZH2 wild type) treated with random shRNA (n = 4, each) and test F-36P, MOLM-13 and OCI-M2 cells treated with either one of two EZH2-targeting shRNAs (n = 4, each) were screened for differential gene expression. RNA from EZH2 wild type (n = 12) and mutant (n = 12) MDS/MPN patients was also analyzed by microarray transcriptome analysis.
2017-06-15 | E-MTAB-5766 | biostudies-arrayexpress
Project description:In this study, we have analyzed DNA methylation changes upon aging of human dermal fibroblasts by using the HumanMethylation27 BeadChip assessing 27,578 unique CpG sites. Cells were isolated from skin samples donated by young (6-23 years) and elderly (60-73 years) patients undergoing surgical interventions. Strikingly, global DNA-methylation profiles of fibroblasts from the same anatomical site clustered closely together indicating that fibroblasts maintain positional memory even after in vitro culture. Skin samples from younger or elderly donors were treated with dispase (Roche Diagnostics, Mannheim, Germany) for 12 hours to separate the dermis from the epidermis. The dermis was digested with 0,2% collagenase and 1,5% BSA in collagenase buffer (100mM HEPES, 120mM NaCl, 50mM KCl, 1mM CaCl2, 5mM Glucose) for 45 minutes. Dermal remnants were removed by filtering the digest through a 100µm nylon strainer (Falcon, Becton Dickinson [BD], San Jose, USA). The cells were subsequently washed and expanded in standard medium consisting of DMEM (PAA; 1g/L glucose) supplemented with glutamine (PAA), penicillin/sptrepamycin (PAA) and 10% fetal calf serum (Biochrom, Berlin, Germany) in a humidified atmosphere at 5% CO2. Cells were always replated when grown to 80% confluency. For methylation profiles upon aging we have isolated DNA from the samples of passage 3 of younger and elderly donors. For methylation profiles upon long-term culture we have isolated DNA from the samples of early passage (P3) and late passage (P21)
2012-02-14 | E-GEOD-22595 | biostudies-arrayexpress
Project description:Products of conception that were diagnosed either euploid or aneuploid during routine cytogenetic analysis were analysed by a novel CGH+SNP array for the evaluation of its usefulness in clinical diagnostics.
2014-01-23 | E-MTAB-1725 | biostudies-arrayexpress
Project description:Background: The differential expression pattern of microRNAs (miRNAs) during mammary gland development might provide insights into their role in regulating the homeostasis of the breast epithelium. Our aim was to analyse these regulatory functions by deriving a comprehensive tissue-specific combined miRNA and mRNA expression profile of post-natal mouse mammary gland development. We measured the expression of 318 individual murine miRNAs by bead-based flow-cytometric profiling of whole mouse mammary glands throughout a 16-point developmental time course, including juvenile, puberty, mature virgin, gestation, lactation, and involution stages. In parallel whole-genome mRNA expression data were obtained. Results: One third (n = 102) of all murine miRNAs analysed were present during mammary gland development. MicroRNAs were represented in seven temporally co-expressed clusters, which were enriched for both miRNAs belonging to the same family and breast cancer-associated miRNAs. Global miRNA and mRNA expression was significantly reduced during lactation and the early stages of involution after weaning. For most detected miRNA families we did not observe systematic changes in the expression of predicted targets. For miRNA families whose targets did show significant changes, we observed inverse patterns of miRNA and target expression. The datasets are made publicly available and the combined expression profiles represent an important community resource for mammary gland biology research. Conclusions: MicroRNAs were expressed in co-regulated clusters during mammary gland development. Breast cancer-associated miRNAs were significantly enriched in these clusters. The mechanism and functional consequences of this miRNA co-regulation and its correlation with mRNA expression provide new avenues for research into mammary gland biology and generates candidates for functional validation. Developmental time course over 17 time points with 2-3 independent biological replicates per time point and four pairs of technical replicates, 48 samples in total
2010-06-25 | E-GEOD-15054 | biostudies-arrayexpress
Project description:Molecular subtypes of breast cancer are characterized by patterns of gene expression, which can be used to predict response to therapy and overall clinical outcome. The luminal breast cancer subtypes are defined by the expression of ER-alpha (ERa) and a set of ERa-associated genes. The transcription factor activator protein 2C (TFAP2C, AP-2C, AP-2g) transcription factor plays a critical role in regulating cell growth and differentiation during ectodermal development and has been implicated in the regulation of ERa and other luminal-associated genes in breast cancer. While TFAP2C has been established as a prognostic factor in human breast cancer, the role of TFAP2C in development of the luminal epithelial cells in the normal mammary gland and in breast cancer have remained elusive. Herein, we demonstrate a critical role of TFAP2C in maintaining the luminal differentiation phenotype during normal mammary development and in luminal breast carcinoma cell lines. Total RNA from MCF7 cells with and without knockdown of TFAP2c. 3 biological replicates, with 2 technical replicates each, were performed for each sample type.
2014-02-01 | E-GEOD-44203 | biostudies-arrayexpress
Project description:Transcriptome of D. shibae 5 h in the light after 18,24 and 30 days in coculture with the dinoflagellate P. minimum two biological replicates
2014-05-01 | E-GEOD-55371 | biostudies-arrayexpress
Project description:We previously characterized zinc finger protein gene HZF1 (ZNF16) and demonstrated its important roles in erythroid and megakaryocytic differentiation of K562 cells by loss-function assay. However its effect in erythroid and megakaryocytic differentiation of hematopoietic stem/progenitor cells (HSPCs) and the mechanisms by which it functions have not been understood. In this study, we detected up-regulation of ZNF16 during erythroid and megakaryocytic differentiation of K562 cells and normal CD34+ HSPCs, and demonstrated that ZNF16 promotes erythroid and megakaryocytic differentiation by gain-of-function and loss-of-function experiments. Gene expression profiling by mRNA array and PCR validation in the K562 transforments with ZNF16 over-expression suggested that cell division cycle-associated 7-like gene (JPO2) and v-kit Hardy-Zuckerman 4 feline sarcoma viral oncogene homolog gene (c-KIT) were among the genes regulated possibly by ZNF16. Luciferase reporter assay and Chromatin Immunoprecipitation demonstrated that ZNF16 binds to JPO2 and c-KIT promoters and inhibits their expression in K562 cells. A significant decrease of JPO2 and c-KIT levels was observed during erythroid and megakaryocytic differentiation of K562 and CD34+ cells. The knockdown of either JPO2 or c-KIT partially rescued the differentiation inhibition caused by ZNF16 knockdown. We also found that ZNF16 inhibits c-KIT/c-Raf/MEK/ERK/c-Jun/HEY1 signal pathways, which finally up-regulated expression of GATA1, a central regulator of erthroid and megakaryocyte differentiation. By lentivirus-mediated gene transfer, we demonstrated that enforced expression and knockdown of ZNF16 in HSPCs down-regulated and up-regulated expression of its targets respectively. Our data collectively demonstrate that ZNF16 promotes erythropoiesis and megakaryocytopoiesis via its regulation on JPO2 and c-KIT. 4 samples are analyzed, H4-1 and H4-2 are two stable K562 transductants with ZNF16 over-expression, PC1 and PC2 are stable control K562 transductants. Stable K562 transductants were obtained for RNA extraction and hybridization on an Illumina HumanHT-12 V4.0 expression beadchipe xpression Array platform.
2016-03-29 | E-GEOD-46593 | biostudies-arrayexpress