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Status |
Public on Nov 04, 2013 |
Title |
bone_marrow_TA+_B-ALL_pat3 |
Sample type |
RNA |
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Source name |
TEL-AML1 positive B-ALL
|
Organism |
Homo sapiens |
Characteristics |
disease state: TEL-AML1 positive B-ALL tissue: bone marrow timepoint of sample collection: diagnosis
|
Growth protocol |
Bone marrow samples of TEL-AML1 positive patients were collected at time of diagnosis. After isolation of mononuclear cells, samples were frozen and stored in the gas-phase of liquid nitrogen until RNA isolation. Peripheral blood samples were taken from TEL-AML1 negative healthy donors. The isolated mononuclear cells were sorted for CD19+ cells and stored until RNA isolation.
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Extracted molecule |
total RNA |
Extraction protocol |
Total RNA was isolated using Trizol (Invitrogen) according to manufacturer's protocol. Quality of the RNA was checked via the Agilent 2100 Bioanalyzer platform (Agilent Technologies).
|
Label |
Cy3
|
Label protocol |
10 ng of each total RNA sample was used for linear T7-based amplification. To produce Cy3-labeled cRNA, the RNA samples were amplified and labeled using the Agilent Low Input Quick Amp Labeling Kit (Agilent Technologies) following the manufacturer's protocol. Yields of cRNA and the dye-incorporation rate were measured with the ND-1000 Spectrophotometer (NanoDrop Technologies).
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Hybridization protocol |
The hybridization procedure was performed according to the Agilent 60-mer oligo microarray processing protocol using the Agilent Gene Expression Hybridization Kit (Agilent Technologies). 600 ng Cy3-labeled fragmented cRNA in hybridization buffer was hybridized overnight (17 hours, 65 °C) to Agilent Whole Human Genome Oligo Microarrays 8x60K using Agilent's recommended hybridization chamber and oven.
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Scan protocol |
Fluorescence signals of the hybridized Agilent Microarrays were detected using Agilent's Microarray Scanner System (Agilent Technologies).
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Description |
TEL-AML1 expression
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Data processing |
The Agilent Feature Extraction Software (FES) was used to read out and process the microarray image files. The software determines feature intensities (including background subtraction), rejects outliers and calculates statistical confidences. For determination of differential gene expression FES derived output data files were further analyzed using the Rosetta Resolver® gene expression data analysis system (Rosetta Biosoftware).
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Submission date |
Sep 10, 2013 |
Last update date |
Nov 05, 2013 |
Contact name |
Pablo Landgraf |
E-mail(s) |
pablo.landgraf@gmx.de
|
Organization name |
Heinrich-Heine University Düsseldorf
|
Department |
Clinic of Pediatric Oncology, Hematology and Clinical Immunology
|
Street address |
Moorenstraße 5
|
City |
Düsseldorf |
ZIP/Postal code |
40225 |
Country |
Germany |
|
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Platform ID |
GPL13607 |
Series (2) |
GSE50734 |
TEL-AML1 (ETV6-RUNX1) in B-cells and leukemia (part 5) |
GSE50736 |
TEL-AML1 (ETV6-RUNX1) in B-cells and leukemia |
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