209 research outputs found

    A detailed inventory of DNA copy number alterations in four commonly used Hodgkin's lymphoma cell lines

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    Background and Objectives Classical Hodgkin's lymphoma (cHL) is a common malignant lymphoma characterized by the presence of large, usually multinucleated malignant Hodgkin and Reed Sternberg (HRS) cells which are thought to be derived from germinal center B-cells. In cHL, the HRS cells constitute less than 1% of the tumor volume; consequently the profile of genetic aberrations in cHL is still poorly understood. Design and Methods In this study, we subjected four commonly used cHL cell lines to array comparative genomic hybridization (aCGH) in order to delineate known chromosomal aberrations in more detail and to search for small hitherto undetected genomic imbalances. Results The aCGH profiles of the four cell lines tested confirmed the complex patterns of rearrangements previously demonstrated with multicolor fluorescence in situ hybridization and chromosomal CGH (cCGH). Importantly, aCGH allowed a much more accurate delineation of imbalances as compared to previous studies performed at a chromosomal level of resolution. Furthermore, we detected 35 hitherto undetected aberrations including a homozygous deletion of chromosomal region 15q26.2 in the cell line HDLM2 encompasing RGMA and CHD2 and an amplification of the STAT6 gene in cell line L1236 leading to STAT6 overexpression. Finally, in cell line KM-H2 we found a 2.35 Mb deletion at 16q12.1 putatively defining a small critical region for the recurrent 16q deletion in cHL. This region contains the CYLD gene, a known suppressor gene of the NF-kappa B pathway. Interpretation and Conclusions aCGH was performed on four cHL cell lines leading to the improved delineation of known chromosomal imbalances and the detection of 35 hitherto undetected aberrations. More specifically, our results highlight STAT6 as a potential transcriptional target and identified RGMA, CHD2 and CYLD as candidate tumor suppressors in cHL

    Positional gene enrichment analysis of gene sets for high-resolution identification of overrepresented chromosomal regions

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    The search for feature enrichment is a widely used method to characterize a set of genes. While several tools have been designed for nominal features such as Gene Ontology annotations or KEGG Pathways, very little has been proposed to tackle numerical features such as the chromosomal positions of genes. For instance, microarray studies typically generate gene lists that are differentially expressed in the sample subgroups under investigation, and when studying diseases caused by genome alterations, it is of great interest to delineate the chromosomal regions that are significantly enriched in these lists. In this article, we present a positional gene enrichment analysis method (PGE) for the identification of chromosomal regions that are significantly enriched in a given set of genes. The strength of our method relies on an original query optimization approach that allows to virtually consider all the possible chromosomal regions for enrichment, and on the multiple testing correction which discriminates truly enriched regions versus those that can occur by chance. We have developed a Web tool implementing this method applied to the human genome (http://www.esat.kuleuven.be/~bioiuser/pge). We validated PGE on published lists of differentially expressed genes. These analyses showed significant overrepresentation of known aberrant chromosomal regions

    Genome-wide study of the effect of blood collection tubes on the cell-free DNA methylome

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    The methylation pattern of cfDNA, isolated from liquid biopsies, is gaining substantial interest for diagnosis and monitoring of diseases. We have evaluated the impact of type of blood collection tube and time delay between blood draw and plasma preparation on bisulphite-based cfDNA methylation profiling. Fifteen tubes of blood were drawn from three healthy volunteer subjects (BD Vacutainer K2E EDTA spray tubes, Streck Cell-Free DNA BCT tubes, PAXgene Blood ccfDNA tubes, Roche Cell-Free DNA Collection tubes and Biomatrica LBgard blood tubes in triplicate). Samples were either immediately processed or stored at room temperature for 24 or 72 hours before plasma preparation. DNA fragment size was evaluated by capillary electrophoresis. Reduced representation bisulphite sequencing was performed on the cell-free DNA isolated from these plasma samples. We evaluated the impact of blood tube and time delay on several quality control metrics. All preservation tubes performed similar on the quality metrics that were evaluated. Furthermore, a considerable increase in cfDNA concentration and the fraction of it derived from NK cells was observed after a 72-hour time delay in EDTA tubes. The methylation pattern of cfDNA is robust and reproducible in between the different preservation tubes. EDTA tubes processed as soon as possible, preferably within 24 hours, are the most cost effective. If immediate processing is not possible, preservation tubes are valid alternatives

    Combined subtractive cDNA cloning and array CGH: an efficient approach for identification of overexpressed genes in DNA amplicons

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    BACKGROUND: Activation of proto-oncogenes by DNA amplification is an important mechanism in the development and maintenance of cancer cells. Until recently, identification of the targeted genes relied on labour intensive and time consuming positional cloning methods. In this study, we outline a straightforward and efficient strategy for fast and comprehensive cloning of amplified and overexpressed genes. RESULTS: As a proof of principle, we analyzed neuroblastoma cell line IMR-32, with at least two amplification sites along the short arm of chromosome 2. In a first step, overexpressed cDNA clones were isolated using a PCR based subtractive cloning method. Subsequent deposition of these clones on a custom microarray and hybridization with IMR-32 DNA, resulted in the identification of clones that were overexpressed due to gene amplification. Using this approach, amplification of all previously reported amplified genes in this cell line was detected. Furthermore, four additional clones were found to be amplified, including the TEM8 gene on 2p13.3, two anonymous transcripts, and a fusion transcript, resulting from 2p13.3 and 2p24.3 fused sequences. CONCLUSIONS: The combinatorial strategy of subtractive cDNA cloning and array CGH analysis allows comprehensive amplicon dissection, which opens perspectives for improved identification of hitherto unknown targeted oncogenes in cancer cells

    Genome wide expression profiling of p53 regulated miRNAs in neuroblastoma

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    Restoration of the antitumor activity of p53 could offer a promising approach for the treatment of neuroblastoma. MicroRNAs (miRNAs) are important mediators of p53 activity, but their role in the p53 response has not yet been comprehensively addressed in neuroblastoma. Therefore, we set out to characterize alterations in miRNA expression that are induced by p53 activation in neuroblastoma cells. Genome-wide miRNA expression analysis showed that miR-34a-5p, miR-182-5p, miR-203a, miR-222-3p, and miR-432-5p are upregulated following nutlin-3 treatment in a p53 dependent manner. The function of miR-182-5p, miR-203a, miR-222-3p, and miR-432-5p was analyzed by ectopic overexpression of miRNA mimics. We observed that these p53-regulated miRNAs inhibit the proliferation of neuroblastoma cells to varying degrees, with the most profound growth inhibition recorded for miR-182-5p. Overexpression of miR-182-5p promoted apoptosis in some neuroblastoma cell lines and induced neuronal differentiation of NGP cells. Using Chromatin Immunoprecipitation-qPCR (ChIP-qPCR), we did not observe direct binding of p53 to MIR182, MIR203, MIR222, and MIR432 in neuroblastoma cells. Taken together, our findings yield new insights in the network of p53-regulated miRNAs in neuroblastoma

    Robust selection of cancer survival signatures from high-throughput genomic data using two-fold subsampling

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    Identifying relevant signatures for clinical patient outcome is a fundamental task in high-throughput studies. Signatures, composed of features such as mRNAs, miRNAs, SNPs or other molecular variables, are often non-overlapping, even though they have been identified from similar experiments considering samples with the same type of disease. The lack of a consensus is mostly due to the fact that sample sizes are far smaller than the numbers of candidate features to be considered, and therefore signature selection suffers from large variation. We propose a robust signature selection method that enhances the selection stability of penalized regression algorithms for predicting survival risk. Our method is based on an aggregation of multiple, possibly unstable, signatures obtained with the preconditioned lasso algorithm applied to random (internal) subsamples of a given cohort data, where the aggregated signature is shrunken by a simple thresholding strategy. The resulting method, RS-PL, is conceptually simple and easy to apply, relying on parameters automatically tuned by cross validation. Robust signature selection using RS-PL operates within an (external) subsampling framework to estimate the selection probabilities of features in multiple trials of RS-PL. These probabilities are used for identifying reliable features to be included in a signature. Our method was evaluated on microarray data sets from neuroblastoma, lung adenocarcinoma, and breast cancer patients, extracting robust and relevant signatures for predicting survival risk. Signatures obtained by our method achieved high prediction performance and robustness, consistently over the three data sets. Genes with high selection probability in our robust signatures have been reported as cancer-relevant. The ordering of predictor coefficients associated with signatures was well-preserved across multiple trials of RS-PL, demonstrating the capability of our method for identifying a transferable consensus signature. The software is available as an R package rsig at CRAN (http://cran.r-project.org)
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