Dataset: Genomic approach in B-cell Chronic Lymphocytic Leukemia: molecularly distinct subgroups of patients with 13q14 deletion

B-cell chronic lymphocytic leukemia (B-CLL) is characterized by a highly variable clinical course that reflects its heterogeneous genomic pattern. To better define molecular subtypes of the disease, we performed SNP and gene expression profiling microarray analyses in a panel of early stage (Binet A) patients. A clustering analysis of genomic profiles identified four significant groups mainly driven by del(13)(q14) and trisomy 12. Notably, patients with del(13)(q14) were grouped in two separate clusters based on the presence of a biallelic loss and the extension of the deletion. The shorter monoallelic deleted 13q14 region was found to be 635 kb in length, not encompassing the mir-15a/16-1 locus. Interestingly, the mir-15a and mir-16 expression was found to be significantly down-regulated only in patients with biallelic loss. Furthermore, a multiclass supervised analysis identified a different transcriptional signatures in the two genomic subgroups with del(13)(q14). Finally, an integrative approach identified 93 transcripts, mainly mapped to chromosome 12 and 13q12-q14.3, whose expression was significantly correlated with the DNA copy number. Overall, our data further support the notion that transcription deregulation in B-CLL could be mostly due to a gene dosage effect and underscore the presence of two distinct molecular types of 13q14 deleted patients with potential clinical relevance. Transcriptional analysis of 60 B-CLL patients, and genotyping analysis of 100 B-CLL patients, in early stage disease (Binet A). This series of microarray experiments contains the gene expression profiles of purified B-cell chronic lymphocytic leukemia (B-CLL) cells obtained from 60 newly diagnosed patients (Binet stage A). 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. 3 micrograms of total RNA was processed and, in accordance with the manufacturer's protocols, 15 micrograms of fragmented biotin-labelled cRNA were hybridized on GeneChip Human Genome U133A Arrays (Affymetrix Inc.). The arrays were scanned using the GeneChip Scanner 3000 7G. The images were acquired using Affymetrix GeneChip Operating Software (GCOS version 1.4) and the probe level data converted to expression values using the Bioconductor function for the Robust Multi-Array average (RMA) procedure (Irizarry et al, 2003), in which perfect match intensities are background adjusted and quantile-quantile normalised. This series of microarray experiments contains the genome-wide profiles of purified B-cell chronic lymphocytic leukemia (B-CLL) cells obtained from 100 newly diagnosed patients (Binet stage A). 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. 250 nanograms of genomic DNA was processed and, in accordance with the manufacturer's protocols, 90 micrograms of fragmented biotin-labeled DNA were hybridized on GeneChip Human Mapping 250K NspI Arrays (Affymetrix Inc.). The arrays were scanned using the GeneChip Scanner 3000 7G. The images were acquired using Affymetrix GeneChip Operating Software (GCOS version 1.4). The raw data for individual SNPs were extracted from CEL files and converted into signal intensities using GTYPE 4.1 and Affymetrix Copy Number Analysis Tool (CNAT 4.0.1) softwares using the Hidden Markov Model algorithm with a genomic smoothing window set to 0. After the pre-processing, piecewise constant estimates of the underlying local DNA copy number (CN) variation was calculated using the DNAcopy Bioconductor package, which looks for optimal breakpoints using circular binary segmentation (CBS).

Species:

human

Samples:

60

Source:

E-GEOD-16746

Updated:

Jan.20, 2015

Registered:

Jan.20, 2015