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Jo Vandesompele

Bio: Jo Vandesompele is an academic researcher from Ghent University. The author has contributed to research in topics: Neuroblastoma & microRNA. The author has an hindex of 88, co-authored 383 publications receiving 59368 citations. Previous affiliations of Jo Vandesompele include Washington University in St. Louis & Ghent University Hospital.


Papers
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Journal ArticleDOI
TL;DR: The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which opens up the possibility of studying the biological relevance of small expression differences.
Abstract: Gene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes. Given the increased sensitivity, reproducibility and large dynamic range of this methodology, the requirements for a proper internal control gene for normalization have become increasingly stringent. Although housekeeping gene expression has been reported to vary considerably, no systematic survey has properly determined the errors related to the common practice of using only one control gene, nor presented an adequate way of working around this problem. We outline a robust and innovative strategy to identify the most stably expressed control genes in a given set of tissues, and to determine the minimum number of genes required to calculate a reliable normalization factor. We have evaluated ten housekeeping genes from different abundance and functional classes in various human tissues, and demonstrated that the conventional use of a single gene for normalization leads to relatively large errors in a significant proportion of samples tested. The geometric mean of multiple carefully selected housekeeping genes was validated as an accurate normalization factor by analyzing publicly available microarray data. The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which, among other things, opens up the possibility of studying the biological relevance of small expression differences.

18,261 citations

Journal ArticleDOI
TL;DR: The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines target the reliability of results to help ensure the integrity of the scientific literature, promote consistency between laboratories, and increase experimental transparency.
Abstract: Background: Currently, a lack of consensus exists on how best to perform and interpret quantitative real-time PCR (qPCR) experiments. The problem is exacerbated by a lack of sufficient experimental detail in many publications, which impedes a reader’s ability to evaluate critically the quality of the results presented or to repeat the experiments. Content: The Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines target the reliability of results to help ensure the integrity of the scientific literature, promote consistency between laboratories, and increase experimental transparency. MIQE is a set of guidelines that describe the minimum information necessary for evaluating qPCR experiments. Included is a checklist to accompany the initial submission of a manuscript to the publisher. By providing all relevant experimental conditions and assay characteristics, reviewers can assess the validity of the protocols used. Full disclosure of all reagents, sequences, and analysis methods is necessary to enable other investigators to reproduce results. MIQE details should be published either in abbreviated form or as an online supplement. Summary: Following these guidelines will encourage better experimental practice, allowing more reliable and unequivocal interpretation of qPCR results.

12,469 citations

Journal ArticleDOI
TL;DR: Advanced and universally applicable models for relative quantification and inter-run calibration with proper error propagation along the entire calculation track are outlined in qBase, a free program for the management and automated analysis of qPCR data.
Abstract: Although quantitative PCR (qPCR) is becoming the method of choice for expression profiling of selected genes, accurate and straightforward processing of the raw measurements remains a major hurdle. Here we outline advanced and universally applicable models for relative quantification and inter-run calibration with proper error propagation along the entire calculation track. These models and algorithms are implemented in qBase, a free program for the management and automated analysis of qPCR data.

3,641 citations

Journal ArticleDOI
TL;DR: It is shown that miR-9, which is upregulated in breast cancer cells, directly targets CDH1, the E-cadherin-encoding messenger RNA, leading to increased cell motility and invasiveness, and a regulatory and signalling pathway involving a metastasis-promoting miRNA that is predicted to directly target expression of the key metastasis
Abstract: β-catenin signalling, which contributes to upregulated expression of the gene encoding vascular endothelial growth factor (VEGF); this leads, in turn, to increased tumour angiogenesis. Overexpression of miR-9 in otherwise non-metastatic breast tumour cells enables these cells to form pulmonary micrometastases in mice. Conversely, inhibiting miR-9 by using a ‘miRNA sponge’ in highly malignant cells inhibits metastasis formation. Expression of miR-9 is activated by MYC and MYCN, both of which directly bind to the mir-9-3 locus. Significantly, in human cancers, miR-9 levels correlate with MYCN amplification, tumour grade and metastatic status. These findings uncover a regulatory and signalling pathway involving a metastasis-promoting miRNA that is predicted to directly target expression of the key metastasis-suppressing protein E-cadherin. Metastases are responsible for more than 90% of cancer-related mortality. These secondary growths arise through a multistep process that begins when cancer cells within primary tumours break away from neighbouring cells and invade the basement membrane 1 . This local invasion may frequently be triggered by contextual signals that carcinoma cells receive from the nearby stroma, causing them to undergo an epithelial–mesenchymal transition (EMT) 2 . Subsequently, metastasizing cells enter the circulation either directly or through lymphatics. Size constraints in the microvasculature cause many of these cells to be arrested at distant sites, where they may extravasate and enter the foreign tissue parenchyma. There they may remain dormant or, with low efficiency, proliferate from occult micrometastases to form angiogenic, clinically detectable metastases. The absence of EMT-inducing signals in the foreign microenvironment may cause such disseminated cells to revert to an epithelial phenotype by means of a mesenchymal–epithelial transition. Critical regulators of the metastatic process include both proteins and miRNAs 3,4

1,238 citations

Journal ArticleDOI
Martin Peifer1, Lynnette Fernandez-Cuesta1, Martin L. Sos1, Julie George1, Danila Seidel1, Lawryn H. Kasper, Dennis Plenker1, Frauke Leenders1, Ruping Sun2, Thomas Zander1, Roopika Menon3, Mirjam Koker1, Ilona Dahmen1, Christian Müller1, Vincenzo Di Cerbo2, Hans Ulrich Schildhaus1, Janine Altmüller1, Ingelore Baessmann1, Christian Becker1, Bram De Wilde4, Jo Vandesompele4, Diana Böhm3, Sascha Ansén1, Franziska Gabler1, Ines Wilkening1, Stefanie Heynck1, Johannes M. Heuckmann1, Xin Lu1, Scott L. Carter5, Kristian Cibulskis5, Shantanu Banerji5, Gad Getz5, Kwon-Sik Park6, Daniel Rauh7, Christian Grütter7, Matthias Fischer1, Laura Pasqualucci8, Gavin M. Wright9, Zoe Wainer9, Prudence A. Russell10, Iver Petersen11, Yuan Chen11, Erich Stoelben, Corinna Ludwig, Philipp A. Schnabel, Hans Hoffmann, Thomas Muley, Michael Brockmann, Walburga Engel-Riedel, Lucia Anna Muscarella12, Vito Michele Fazio12, Harry J.M. Groen13, Wim Timens13, Hannie Sietsma13, Erik Thunnissen14, Egber Smit14, Daniëlle A M Heideman14, Peter J.F. Snijders14, Federico Cappuzzo, C. Ligorio15, Stefania Damiani15, John K. Field16, Steinar Solberg17, Odd Terje Brustugun17, Marius Lund-Iversen17, Jörg Sänger, Joachim H. Clement11, Alex Soltermann18, Holger Moch18, Walter Weder18, Benjamin Solomon19, Jean-Charles Soria20, Pierre Validire, Benjamin Besse20, Elisabeth Brambilla21, Christian Brambilla21, Sylvie Lantuejoul21, Philippe Lorimier21, Peter M. Schneider1, Michael Hallek1, William Pao22, Matthew Meyerson23, Matthew Meyerson5, Julien Sage6, Jay Shendure24, Robert Schneider2, Robert Schneider25, Reinhard Büttner1, Jürgen Wolf1, Peter Nürnberg1, Sven Perner3, Lukas C. Heukamp1, Paul K. Brindle, Stefan A. Haas2, Roman K. Thomas1 
TL;DR: This study implicates histone modification as a major feature of SCLC, reveals potentially therapeutically tractable genomic alterations and provides a generalizable framework for the identification of biologically relevant genes in the context of high mutational background.
Abstract: Small-cell lung cancer (SCLC) is an aggressive lung tumor subtype with poor prognosis(1-3). We sequenced 29 SCLC exomes, 2 genomes and 15 transcriptomes and found an extremely high mutation rate of 7.4 +/- 1 protein-changing mutations per million base pairs. Therefore, we conducted integrated analyses of the various data sets to identify pathogenetically relevant mutated genes. In all cases, we found evidence for inactivation of TP53 and RB1 and identified recurrent mutations in the CREBBP, EP300 and MLL genes that encode histone modifiers. Furthermore, we observed mutations in PTEN, SLIT2 and EPHA7, as well as focal amplifications of the FGFR1 tyrosine kinase gene. Finally, we detected many of the alterations found in humans in SCLC tumors from Tp53 and Rb1 double knockout mice(4). Our study implicates histone modification as a major feature of SCLC, reveals potentially therapeutically tractable genomic alterations and provides a generalizable framework for the identification of biologically relevant genes in the context of high mutational background.

1,177 citations


Cited by
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Journal ArticleDOI
TL;DR: The philosophy and design of the limma package is reviewed, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
Abstract: limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.

22,147 citations

Journal ArticleDOI
TL;DR: The command-line tool cutadapt is developed, which supports 454, Illumina and SOLiD (color space) data, offers two adapter trimming algorithms, and has other useful features.
Abstract: When small RNA is sequenced on current sequencing machines, the resulting reads are usually longer than the RNA and therefore contain parts of the 3' adapter. That adapter must be found and removed error-tolerantly from each read before read mapping. Previous solutions are either hard to use or do not offer required features, in particular support for color space data. As an easy to use alternative, we developed the command-line tool cutadapt, which supports 454, Illumina and SOLiD (color space) data, offers two adapter trimming algorithms, and has other useful features. Cutadapt, including its MIT-licensed source code, is available for download at http://code.google.com/p/cutadapt/

20,255 citations

28 Jul 2005
TL;DR: PfPMP1)与感染红细胞、树突状组胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作�ly.
Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1(PfPMP1)与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用,在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员,通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

18,940 citations

Journal ArticleDOI
TL;DR: The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which opens up the possibility of studying the biological relevance of small expression differences.
Abstract: Gene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes. Given the increased sensitivity, reproducibility and large dynamic range of this methodology, the requirements for a proper internal control gene for normalization have become increasingly stringent. Although housekeeping gene expression has been reported to vary considerably, no systematic survey has properly determined the errors related to the common practice of using only one control gene, nor presented an adequate way of working around this problem. We outline a robust and innovative strategy to identify the most stably expressed control genes in a given set of tissues, and to determine the minimum number of genes required to calculate a reliable normalization factor. We have evaluated ten housekeeping genes from different abundance and functional classes in various human tissues, and demonstrated that the conventional use of a single gene for normalization leads to relatively large errors in a significant proportion of samples tested. The geometric mean of multiple carefully selected housekeeping genes was validated as an accurate normalization factor by analyzing publicly available microarray data. The normalization strategy presented here is a prerequisite for accurate RT-PCR expression profiling, which, among other things, opens up the possibility of studying the biological relevance of small expression differences.

18,261 citations