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Expression data from patients with large granular lymphocyte leukemia

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NIAID Data Ecosystem2026-03-11 收录
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https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE39838
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Our results suggest that STAT3 can be activated independent of key oncogenic driver mutations in its SH2 domain in a subset of patients with large granular lymphocyte disorders. We examined the gene expression pattern in T-LGL leukemias compared to controls, and the impact of the presence of STAT3 mutations on the transcriptional regulation of a specific set of genes previously described. Mononuclear cells were separated from peripheral blood by density gradient sedimentation (Mediatech, Herndon, VA, USA). LGL cells were separated by flow cytometric sorting using anti-VB and CD8 mAb as described previously. Healthy, donor-derived CD8+CD57+ cells were isolated by flow cytometric sorting using CD3, CD8, and CD57 mAb. Total RNA was extracted from cells using Trizol (Invitrogen, Carlsbad, CA, USA) Phase-Lock gel tubes (Eppendorf, Hamburg, Germany), cleaned RNAeasy columns (Qiagen, Valencia CA, USA), and dissolved diethylpyrocarbonate water. Total cRNA was prepared using the in vitro-transcribed (Affymetrix, Santa Clara, CA, USA) and hybridized to U133 arrays, according to the manufacturer's instructions (Affymetrix). All microarrays were examined for surface defects, grid placement, background intensity, housekeeping gene expression, and a 3:5 ratio of probe from genes of varying length. Expression analysis was conducted using standard Affymetrix analysis software algorithms (Microarray Suite 5.0). Comparative analysis between expression profiles was carried out on GeneSpring' software, Version 7.1 (Agilent, Clara, CA, USA). Scanned images of Affymetrix chips were converted spreadsheet numbers using Affymetrix proprietary GeneChip Operating software (GCOS).
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2019-03-25
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