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.

The von Hippel-Lindau tumor suppressor gene expression level has prognostic value in neuroblastoma.

Abstract: Deletions of the short arm of chromosome 3 are often observed in a specific subset of aggressive neuroblastomas (NBs) with loss of distal 11q and without MYCN amplification. The critical deleted region encompasses the locus of the von Hippel-Lindau gene (VHL, 3p25). Constitutional loss of function mutations in the VHL gene are responsible for the VHL syndrome, a dominantly inherited familial cancer syndrome predisposing to a variety of neoplasms, including pheochromocytoma. Pheochromocytomas are, like NB, derived from neural crest cells, but, unlike NB, consist of more mature chromaffin cells instead of immature neuroblasts. Further arguments for a putative role of VHL in NB are its function as oxygen sensitizer and the reported relation between hypoxia and dedifferentiation of NB cells, leading to a more aggressive phenotype. To test the possible involvement of VHL in NB, we did mRNA expression analysis and sought evidence for VHL gene inactivation. Although no evidence for a classic tumor suppressor role for VHL in NB could be obtained, a strong correlation was observed between reduced levels of VHL mRNA and low patient survival probability (p = 0.013). Furthermore, VHL appears to have predictive power in NTRK1 (TRKA) positive tumor samples with presumed favorable prognosis, which makes it a potentially valuable marker for more accurate risk assessment in this subgroup of patients. The significance of the reduced VHL expression levels in relation to NB tumor biology remains unexplained, as functional analysis demonstrated no clear effect of the reduction in VHL mRNA expression on protein stability of its downstream target hypoxia-inducible factor alpha. (c) 2006 Wiley-Liss, Inc. (Less)

Robust sequential biophysical fractionation of blood plasma to study variations in the biomolecular landscape of systemically circulating extracellular vesicles across clinical conditions.

Abstract: Separating extracellular vesicles (EV) from blood plasma is challenging and complicates their biological understanding and biomarker development. In this study, we fractionate blood plasma by combining size-exclusion chromatography (SEC) and OptiPrep density gradient centrifugation to study clinical context-dependent and time-dependent variations in the biomolecular landscape of systemically circulating EV. Using pooled blood plasma samples from breast cancer patients, we first demonstrate the technical repeatability of blood plasma fractionation. Using serial blood plasma samples from HIV and ovarian cancer patients (n = 10) we next show that EV carry a clinical context-dependent and/or time-dependent protein and small RNA composition, including miRNA and tRNA. In addition, differential analysis of blood plasma fractions provides a catalogue of putative proteins not associated with systemically circulating EV. In conclusion, the implementation of blood plasma fractionation allows to advance the biological understanding and biomarker development of systemically circulating EV.

Effective Alu Repeat Based RT-Qpcr Normalization in Cancer Cell Perturbation Experiments

Abstract: Background Measuring messenger RNA (mRNA) levels using the reverse transcription quantitative polymerase chain reaction (RT-qPCR) is common practice in many laboratories. A specific set of mRNAs as internal control reference genes is considered as the preferred strategy to normalize RT-qPCR data. Proper selection of reference genes is a critical issue, especially in cancer cells that are subjected to different in vitro manipulations. These manipulations may result in dramatic alterations in gene expression levels, even of assumed reference genes. In this study, we evaluated the expression levels of 11 commonly used reference genes as internal controls for normalization of 19 experiments that include neuroblastoma, T-ALL, melanoma, breast cancer, non small cell lung cancer (NSCL), acute myeloid leukemia (AML), prostate cancer, colorectal cancer, and cervical cancer cell lines subjected to various perturbations.

Circulating RNA biomarkers in diffuse large B-cell lymphoma: a systematic review

Abstract: Diffuse large B-cell lymphoma (DLBCL) is the most common histological subtype of non-Hodgkin’s lymphomas (NHL). DLBCL is an aggressive malignancy that displays a great heterogeneity in terms of morphology, genetics and biological behavior. While a sustained complete remission is obtained in the majority of patients with standard immunochemotherapy, patients with refractory of relapsed disease after first-line treatment have a poor prognosis. This patient group represents an important unmet need in lymphoma treatment. In recent years, improved understanding of the underlying molecular pathogenesis had led to new classification and prognostication tools, including the development of cell-free biomarkers in liquid biopsies. Although the majority of studies have focused on the use of cell-free fragments of DNA (cfDNA), there has been an increased interest in circulating-free coding and non-coding RNA, including messenger RNA (mRNA), microRNA (miRNA), long non-coding RNA (lncRNA) and circular RNA (circRNA), as well as RNA encapsulated in extracellular vesicles or tumor-educated platelets (TEPs). We performed a systematic search in PubMed to identify articles that evaluated circulating RNA as diagnostic, subtype, treatment response or prognostic biomarkers in a human DLBCL population. A total of 35 articles met the inclusion criteria. The aim of this systematic review is to present the current understanding of circulating RNA molecules as biomarker in DLBCL and to discuss their future potential.

DNA methylation profiling of primary neuroblastoma tumors using methyl-CpG-binding domain sequencing

Abstract: Comprehensive genome-wide DNA methylation studies in neuroblastoma (NB), a childhood tumor that originates from precursor cells of the sympathetic nervous system, are scarce. Recently, we profiled the DNA methylome of 102 well-annotated primary NB tumors by methyl-CpG-binding domain (MBD) sequencing, in order to identify prognostic biomarker candidates. In this data descriptor, we give details on how this data set was generated and which bioinformatics analyses were applied during data processing. Through a series of technical validations, we illustrate that the data are of high quality and that the sequenced fragments represent methylated genomic regions. Furthermore, genes previously described to be methylated in NB are confirmed. As such, these MBD sequencing data are a valuable resource to further study the association of NB risk factors with the NB methylome, and offer the opportunity to integrate methylome data with other -omic data sets on the same tumor samples such as gene copy number and gene expression, also publically available.

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.