Dataset features


Application: Gene expression microarray analysis
Number of samples: 136
Release date: Oct 12 2012
Last update date: Jul 26 2018
Access: Public
Diseases: Neoplasms, Leukemia, Lymphocytic, Chronic, B-Cell
Dataset link Relevance of Chromosome 2p Gain in Early Binet Stage A Chronic Lymphocytic Leukemia (expression)

Experimental Protocol

This series of microarray experiments contains the gene expression profiles of purified B-cell chronic lymphocytic leukemia (B-CLL) cells obtained from 136 patients (Binet stage A) showing 2p gain alteration. Peripheral blood mononuclear cells from B-CLL patients were isolated by Ficoll-Hypaque density-gradient centrifugation and the proportion of CD5/CD19/CD23 triple positive B cells in the suspension was determined by direct immunofluorescence performed using a FACS-sort flow cytometer with antibodies to: CD19 FITC/PE, CD23 PE and CD5 Cy-Chrome. If B-CLL cells were less than 90%, T cells, NK cells and monocytes were removed by negative selection using CD3, CD56, CD16, and CD14 monoclonal antibody treatment followed by magnetic beads. 5.5 micrograms of single-stranded DNA target obtained from 100 ng of purified total RNA was fragmented and then labeled using the WT Terminal Labeling Kit according to the standard Affymetrix protocol (GeneChip® Whole Transcript (WT) Sense Target Labeling Assay Manual). The fragmented labeled single-stranded DNA target was hybridized for 16 hours and 30 minutes at 45°C on GeneChip® Gene 1.0 ST array according to the standard Affymetrix protocol. Washing and scanning were performed using GeneChip System of Affymetrix (GeneChip Hybridization Oven 640, GeneChip Fluidics Station 450 and GeneChip Scanner 7G). Log2-transformed expression values were extracted from CEL files and normalized using NetAffx Transcript Cluster Annotations, Release 31 and robust multi-array average (RMA) procedure in Expression Console software (Affymetrix Inc.). The expression values of transcript cluster ID specific for loci representing naturally occurring read-through transcriptions were summarized as median value for each sample.










Luca Agnelli
Antonino Neri