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.

Targeted Therapy of TERT-Rearranged Neuroblastoma with BET Bromodomain Inhibitor and Proteasome Inhibitor Combination Therapy

Abstract: Purpose: TERT gene rearrangement with transcriptional superenhancers leads to TERT overexpression and neuroblastoma. No targeted therapy is available for clinical trials in patients with TERT-rearranged neuroblastoma. Experimental Design: Anticancer agents exerting the best synergistic anticancer effects with BET bromodomain inhibitors were identified by screening an FDA-approved oncology drug library. The synergistic effects of the BET bromodomain inhibitor OTX015 and the proteasome inhibitor carfilzomib were examined by immunoblot and flow cytometry analysis. The anticancer efficacy of OTX015 and carfilzomib combination therapy was investigated in mice xenografted with TERT-rearranged neuroblastoma cell lines or patient-derived xenograft (PDX) tumor cells, and the role of TERT reduction in the anticancer efficacy was examined through rescue experiments in mice. Results: The BET bromodomain protein BRD4 promoted TERT-rearranged neuroblastoma cell proliferation through upregulating TERT expression. Screening of an approved oncology drug library identified the proteasome inhibitor carfilzomib as the agent exerting the best synergistic anticancer effects with BET bromodomain inhibitors including OTX015. OTX015 and carfilzomib synergistically reduced TERT protein expression, induced endoplasmic reticulum stress, and induced TERT-rearranged neuroblastoma cell apoptosis which was blocked by TERT overexpression and endoplasmic reticulum stress antagonists. In mice xenografted with TERT-rearranged neuroblastoma cell lines or PDX tumor cells, OTX015 and carfilzomib synergistically blocked TERT expression, induced tumor cell apoptosis, suppressed tumor progression, and improved mouse survival, which was largely reversed by forced TERT overexpression. Conclusions: OTX015 and carfilzomib combination therapy is likely to be translated into the first clinical trial of a targeted therapy in patients with TERT-rearranged neuroblastoma.

Positional and functional mapping of a neuroblastoma differentiation gene on chromosome 11

Abstract: Loss of chromosome 11q defines a subset of high-stage aggressive neuroblastomas. Deletions are typically large and mapping efforts have thus far not lead to a well defined consensus region, which hampers the identification of positional candidate tumour suppressor genes. In a previous study, functional evidence for a neuroblastoma suppressor gene on chromosome 11 was obtained through microcell mediated chromosome transfer, indicated by differentiation of neuroblastoma cells with loss of distal 11q upon introduction of chromosome 11. Interestingly, some of these microcell hybrid clones were shown to harbour deletions in the transferred chromosome 11. We decided to further exploit this model system as a means to identify candidate tumour suppressor or differentiation genes located on chromosome 11. In a first step, we performed high-resolution arrayCGH DNA copy-number analysis in order to evaluate the chromosome 11 status in the hybrids. Several deletions in both parental and transferred chromosomes in the investigated microcell hybrids were observed. Subsequent correlation of these deletion events with the observed morphological changes lead to the delineation of three putative regions on chromosome 11: 11q25, 11p13->11p15.1 and 11p15.3, that may harbour the responsible differentiation gene. Using an available model system, we were able to put forward some candidate regions that may be involved in neuroblastoma. Additional studies will be required to clarify the putative role of the genes located in these chromosomal segments in the observed differentiation phenotype specifically or in neuroblastoma pathogenesis in general.

When DNA gets in the way: A cautionary note for DNA contamination in extracellular RNA-seq studies.

Abstract: With great interest, we read the paper by Zhou et al. (1) describing a methodology that enables extracellular RNA sequencing (exRNA-seq) from extremely low input (Small Input Liquid Volume Extracellular RNA Sequencing [SILVER-seq]). We were intrigued by the high number of detected genes compared to our previous studies (2, 3) and noticed low reproducibility. We hypothesized that these observations could originate from substantial DNA contamination. Therefore, we reanalyzed the SILVER-seq data (4) to determine the extent of DNA signal in the sequencing reads. First, we analyzed the fraction of reads mapping to the different genomic regions. We noticed that these fractions closely resembled the distributions in the genome (Fig. 1 A ). Specifically, fewer than 5% of the reads mapped to exonic regions, while our own exRNA-seq data (3) showed an average of 35% exonic reads. Secondly, we analyzed reads mapping to spliced sequences, expecting them to be … [↵][1]1To whom correspondence may be addressed. Email: Jasper.verwilt{at}ugent.be. [1]: #xref-corresp-1-1

CASP8 SNP D302H (rs1045485) is associated with worse survival in MYCN-amplified neuroblastoma patients.

Abstract: Background: Neuroblastoma is a pediatric cancer that exhibits a wide clinical spectrum ranging from spontaneous regression in low-risk patients to fatal disease in high-risk patients. The identification of single nucleotide polymorphisms (SNPs) may help explain the heterogeneity of neuroblastoma and assist in identifying patients at higher risk for poor survival. SNPs in the TP53 pathway are of special importance, as several studies have reported associations between TP53 pathway SNPs and cancer. Of note, less than 2% of neuroblastoma tumors have a TP53 mutation at diagnosis. Patients and Methods: We selected 21 of the most frequently studied SNPs in the TP53 pathway and evaluated their association with outcome in 500 neuroblastoma patients using TaqMan allelic discrimination assays. Results and Conclusion: We investigated the impact of 21 SNPs on overall survival, event-free survival, age at diagnosis, MYCN status, and stage of the disease in 500 neuroblastoma patients. A missense SNP in exon 10 of the CASP8 gene SNP D302H was associated with worse overall and event-free survival in patients with MYCN-amplified neuroblastoma tumors.

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.