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.

SURVEY AND SUMMARY RDML: structured language and reporting guidelines for real-time quantitative PCR data

Abstract: The XML-based Real-Time PCR Data Markup Language (RDML) has been developed by the RDML consortium (http://www.rdml.org) to enable straightforward exchange of qPCR data and related information between qPCR instruments and third party data analysis software, between colleagues and collaborators and between experimenters and journals or public repositories. We here also propose data related guidelines as a subset of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) to guarantee inclusion of key data information when reporting experimental results.

Molecular dissection of isolated disease features in mosaic neurofibromatosis type 1.

Abstract: Elucidation of the biological framework underlying the development of neurofibromatosis type 1 (NF1)–related symptoms has proved to be difficult. Complicating factors include the large size of the NF1 gene, the presence of several NF1 pseudogenes, the complex interactions between cell types, and the NF1-haploinsufficient state of all cells in the body. Here, we investigate three patients with distinct NF1-associated clinical manifestations (neurofibromas only, pigmentary changes only, and association of both symptoms). For each patient, various tissues and cell types were tested with comprehensive and quantitative assays capable of detecting low-percentage NF1 mutations. This approach confirmed the biallelic NF1 inactivation in Schwann cells in neurofibromas and, for the first time, demonstrated biallelic NF1 inactivation in melanocytes in NF1-related cafe-au-lait macules. Interestingly, both disease features arise even within a background of predominantly NF1 wild-type cells. Together, the data provide molecular evidence that (1) the distinct clinical picture of the patients is due to mosaicism for the NF1 mutation and (2) the mosaic phenotype reflects the embryonic timing and, accordingly, the neural crest–derived cell type involved in the somatic NF1 mutation. The study of the affected cell types provides important insight into developmental concepts underlying particular NF1-related disease features and opens avenues for improved diagnosis and genetic counseling of individuals with mosaic NF1.

Small-molecule MDM2 antagonists as a new therapy concept for neuroblastoma.

Abstract: Circumvention of the p53 tumor suppressor barrier in neuroblastoma is rarely caused by TP53 mutation but might arise from inappropriately increased activity of its principal negative regulator MDM2. We show here that targeted disruption of the p53-MDM2 interaction by the small-molecule MDM2 antagonist nutlin-3 stabilizes p53 and selectively activates the p53 pathway in neuroblastoma cells with wild-type p53, resulting in a pronounced antiproliferative and cytotoxic effect through induction of G(1) cell cycle arrest and apoptosis. A nutlin-3 response was observed regardless of MYCN amplification status. Remarkably, surviving SK-N-SH cells adopted a senescence-like phenotype, whereas CLB-GA and NGP cells underwent neuronal differentiation. p53 dependence of these alternative outcomes of nutlin-3 treatment was evidenced by abrogation of the effects when p53 was knocked down by lentiviral-mediated short hairpin RNA interference. The diversity of cellular responses reveals pleiotropic mechanisms of nutlins to disable neuroblastoma cells and exemplifies the feasibility of exploiting, by a single targeted intervention, the multiplicity of anticancer activities exerted by a key tumor suppressor as p53. The observed treatment effects without the need of imposing a genotoxic burden suggest that selective MDM2 antagonists might be beneficial for treatment of neuroblastoma patients with and without MYCN amplification.

DNA methylation silences miR-132 in prostate cancer

Abstract: Silencing of microRNAs (miRNAs) by promoter CpG island methylation may be an important mechanism in prostate carcinogenesis. To screen for epigenetically silenced miRNAs in prostate cancer (PCa), we treated prostate normal epithelial and carcinoma cells with 5-aza-2'-deoxycytidine (AZA) and subsequently examined expression changes of 650 miRNAs by megaplex stemloop reverse transcription-quantitative PCR. After applying a selection strategy, we analyzed the methylation status of CpG islands upstream to a subset of miRNAs by methylation-specific PCR. The CpG islands of miR-18b, miR-132, miR-34b/c, miR-148a, miR-450a and miR-542-3p showed methylation patterns congruent with their expression modulations in response to AZA. Methylation analysis of these CpG islands in a panel of 50 human prostate carcinoma specimens and 24 normal controls revealed miR-132 to be methylated in 42% of human cancer cases in a manner positively correlated to total Gleason score and tumor stage. Expression analysis of miR-132 in our tissue panel confirmed its downregulation in methylated tumors. Re-expression of miR-132 in PC3 cells induced cell detachment followed by cell death (anoikis). Two pro-survival proteins-heparin-binding epidermal growth factor and TALIN2-were confirmed as direct targets of miR-132. The results of this study point to miR-132 as a methylation-silenced miRNA with an antimetastatic role in PCa controlling cellular adhesion.

limma powers differential expression analyses for RNA-sequencing and microarray studies

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.

Cutadapt removes adapter sequences from high-throughput sequencing reads

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/

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

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。

Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes

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.