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Series GSE14853 Query DataSets for GSE14853
Status Public on Mar 01, 2010
Title Circulating endothelial cells in patients with chronic lymphocytic leukemia: clinical and biological characterization
Organism Homo sapiens
Experiment type Expression profiling by array
Summary In cancer patients, circulating endothelial cells (CEC) are increased and correlate with an aggressive course of the disease. However the clinical and biologic significance of CEC in chronic lymphocytic leukemia (CLL) is still uncertain. In this study we show that, in series of 171 CLL patients, CEC are increased in comparison to normal age and sex related controls. A higher level of CEC (> 20 ul) identifies a subset of patients with a more aggressive course of the disease characterized by a shorter time to first treatment both in univariate and multivariate analyses. CEC levels do not correlate with known markers of aggressiveness including stage, CD38 and ZAP70 positivity, and cytogenetics. By FISH analysis, in 7 cases a significant proportion of CEC presented the same cytogenetic lesion of neoplastic lymphocytes and immunophenotypic features of endothelial progenitor cells. The gene expression profile of sorted CEC showed a molecular pattern suggesting a derivation from CLL leukemic cells with increased cell survival and proliferation, diminished cell adhesion to extracellular matrix and enhanced pro-angiogenic function compared to their normal counterpart. These data suggest that in CLL, CEC are tumor-derived and may represent a new biologic marker of aggressiveness playing a role in disease evolution.
Overall design Large-scale GEP was performed on 37 samples including 12 CEC, 12 CD19+, 10 CD14+ cells purified from CLL patients as well as 2 CEC and 1 CD19+ samples collected from normal controls. Total RNAs were isolated from all samples using RNeasy Mini Kit (QIAGEN, Valencia, CA, USA). Then, high quality RNAs were amplified and Cy5-labeled using Low RNA Input Fluorescent Linear Amplification Kit (Agilent Technologies, Palo alto, CA, USA). Universal Human Reference RNA (UHR) (Stratagene, Cedar Creek, TX), consisted of equal amount of total RNA from 10 human cancer cell lines, was used as reference control in all microarray gene-profiling experiments. Amplified reference cRNA was labelled with cyanine 3-CTP (Agilent Technologies) in each experiment. Agilent RNA Two-Color Spike-In was added in each sample to provide positive controls for monitoring the microarray workflow from sample amplification and labelling to microarray processing. It contains 10 in vitro synthesized, polyadenylated transcripts derived from the Adenovirus E1A transcriptome that are premixed at various ratios. All cRNA products were purified using RNeasy columns (QIAGEN). Samples had to contain at least 10-15 pmole of cyanine dye/ug of cRNA to be considered suitable for subsequent hybridization. 825 ng of Cy5-labelled cRNA were mixed with the same amount of Cy3-labeled reference cRNA and then cRNA mixtures were fragmented to an average size of 50-100 nt by incubation at 60°C for 30 min using in situ Hybridization kit-plus (Agilent Technologies). Samples were hybridized for 17 h at 65°C on 4X44K Whole Human Genome Microarray (Agilent Technologies), comprising over 33’000 (60-mer) experimentally validated oligonucleotide probes and then scanned using a confocal laser scanner (Agilent Technologies).

Gene expression analyses
Fluorescence data were analyzed with Feature Extraction Software v.9.1 (Agilent Technologies). Result data from each scan (Log10 Cy5/Cy3) were imported into the gene expression analysis software Luminator (Rosetta Bio software, Seattle, WA, USA). Two-dimensional clustering analysis was performed using an agglomerative algorithm with an average link heuristics and a correlation with mean subtraction.The identification of genes differentially expressed between subgroups was performed using both Significant Analysis of Microarray (SAM) algorithm with false discovery ratio (FDR)<5% and enhanced Analysis of Variance (ANOVA) with p-value <0.001. To increase the statistical power, the enhanced ANOVA uses as input data both expression level and the estimated technology error associated with the expression level. As a result, the false-positive rate is reduced when the number of replicates is small and, then, sensitivity detection is increased. A complete description of statistical methods used is available in the technology section of Rosetta Bio software website ( PANTHER (Protein ANalysis THrough Evolutionary Relationships, Classification System (Applied Biosystems, Foster City, CA, USA) was used to determine cellular pathways of genes identified.
Contributor(s) Rigolin G, Maffei R, Rizzotto L, Ciccone M, Sofritti O, Daghia G, Cibien F, Viglione G, Ambrosio C, Cavazzini F, Marasca R, Castoldi G, Cuneo A
Citation(s) 20166207
Submission date Feb 17, 2009
Last update date Feb 22, 2018
Contact name Rossana Maffei
Phone +39 059 4222715
Organization name University of Modena and Reggio Emilia
Department Dept of Hematology and Oncology
Lab Lab of Molecular Hematology
Street address Via del Pozzo 71
City Modena
State/province Modena
ZIP/Postal code 41100
Country Italy
Platforms (1)
GPL4133 Agilent-014850 Whole Human Genome Microarray 4x44K G4112F (Feature Number version)
Samples (37)
GSM367059 nCEC BP
GSM367060 nCEC MM
BioProject PRJNA112133

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE14853_RAW.tar 514.1 Mb (http)(custom) TAR (of TXT)
Processed data included within Sample table

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